Perspectives

In 2016, Gupta and Cahill challenged the field of psychiatry to reexamine prescribing patterns.¹ They warned against the use of polypharmacy when not attached to improved patient functioning. They were concerned with the limited evidence for polypharmacy as well as DSM diagnostic criteria. In their inspiring article, they described a process of deprescribing.

In an effort to study and practice their recommendations, we have noticed a lack of literature examining the elimination of diagnostic labels. While there have been some studies looking at comorbidity, especially with substance use disorders,² there is a paucity of scientific evidence on patients with numerous diagnoses. Yet our practices are filled with patients who have been labeled with multiple conflicting or redundant diagnoses throughout their lives depending on the setting or the orientation of the practitioner.

The DSM-5 warns against diagnosing disorders when “the occurrence … is not better explained by” another disorder.³ A mix of diagnoses creates confusion for patients as well as clinicians trying to sort through their reported psychiatric histories.

A routine example would include a patient presenting for an initial evaluation and stating “I’ve been diagnosed as manic-depressive, high anxiety, split personality, posttraumatic stress, insomnia, ADD, and depression.” A review of the medical record will reveal a list of diagnoses, including bipolar II, generalized anxiety disorder, borderline personality disorder, posttraumatic stress disorder, unspecified insomnia, attention-deficit/hyperactivity disorder, and major depressive disorder. The medication list includes lamotrigine, valproic acid, citalopram, bupropion, buspirone, prazosin, methylphenidate, clonazepam, hydroxyzine, and low-dose quetiapine at night as needed.

This is an example of polypharmacy treating multiple, and at times conflicting, diagnoses. While an extreme case, in our experience, cases like this are not uncommon. It was actually in our efforts to examine deprescribing that we noticed this quandary. When inquiring about patients on many psychotropic medications, we often receive this retort: the patient is only prescribed one medication per disorder. Some providers have the belief that multiple disorders justify multiple medications, and that this tautological thinking legitimizes polypharmacy.

A patient who has varying moods, some fears, a fluctuating temperament, past traumas, occasional difficulty sleeping, intermittent inattention, and some sadness may be given all the diagnoses listed above and the resulting medication list. The multiplication of diagnoses, “polydiagnosing,” is a convenient justification for future polypharmacy. A lack of careful assessment and thinking in the application of new diagnoses permits the use of increasing numbers of pharmacological agents. A constellation of symptoms of anxiety, concentration deficits, affective dysregulation, and psychosis may justify the combination of benzodiazepines, stimulants, mood stabilizers, and antipsychotics, while a patient with “just” schizophrenia who is sometimes sad, scared, or distracted is more likely to be kept on just one medication, likely an antipsychotic.

Contrary to most medical disorders (for example, tuberculosis) but similar to others (for example, chronic pain), psychiatric disorders are based on the opinion of a “modest number of ‘expert’ classifications.”⁴ While the broad categories of disorders are justifiable, individual diagnoses are burdened with high rates of comorbidity; lack of treatment specificity; and evidence that distinct syndromes share a genetic basis. Those concerns were exemplified in the study examining the inter-rater reliability of DSM-5 diagnoses, where many disorders were found to have questionable validity.⁵

A psychiatric diagnosis should be based on biological, psychological, and social factors, which align with our understanding of the natural course of an illness. A patient presenting with transient symptoms of sadness in the context of significant social factors like homelessness and/or significant biological factors associated with schizophrenia should not reflexively receive an additional diagnosis of a depressive disorder. A patient reporting poor concentration in the context of a manic episode should not receive an additional diagnosis of attention-deficit disorder. An older patient with depression on multiple antipsychotics for adjunctive treatment should not necessarily receive a diagnosis of cognitive disorder at the first sign of memory problems.

The cavalier and inconsistent use of diagnoses renders the patients with no clear narrative of who they are. They end up integrating the varying providers’ opinions as a cacophony of labels of unclear significance. Many patients have contradictory diagnoses like major depressive disorder and bipolar disorder, or schizophrenia and schizoaffective disorder. Those inaccurate diagnoses could not only lead to treatment mistakes, but also psychological harm.⁶

A clearer diagnostic picture is not only more scientifically sound but also more coherent to the patient. This in turn can lead to an improved treatment alliance and buy-in from the patient. Assisting a patient in sorting out and understanding the vast arrays of diagnostic labels they may hear throughout their treatment can serve as a tool for psychoeducation, empowerment, and control over their own care and themselves.

How should a provider practice de-diagnosing? Based on the work of Reeve, et al.,⁷ on the principles crucial to deprescribing, and subsequent research by Gupta and Cahill,⁸ we compiled a list of considerations for practitioners wishing to engage in this type of work with their patients.
 

Choose the right time. While insurance companies require diagnostic findings from the first visit, abrupt de-diagnosing for the sake of simplifying the record from that first visit could be detrimental. Patients can become attached to and find meaning in their diagnostic labels. This was exemplified with the removal of Asperger’s syndrome from the DSM-5.⁹ Acute symptomatology may be an opportune time to revisit the core pathology of a patient, or a poor time for a patient to have this discussion.

Compile a list of all the patient’s diagnoses. Our initial visits are often illuminated when patients enumerate the vast number of diagnoses they have been given by different providers. Patients will often list half a dozen diagnoses. The patterns often follow life courses with ADHD, conduct disorder, and learning disability in childhood; with anxiety, depression, and/or bipolar disorder in early adulthood; to complicated grief, depression with pseudodementia, and neurocognitive disorders in older adults. Yet patients rarely appreciate the temporary or episodic nature of mental disorders and instead accumulate diagnoses at each change of provider.

Initiate discussion with the patient. It is meaningful to see if patients resonate with the question, “Do you ever feel like every psychiatrist you have seen has given you a different diagnosis?” In our experience, patients’ reactions to this question usually exemplify the problematic nature of the vast array of diagnoses our patients are given. The majority of them are unable to confidently explain the meaning of those diagnoses, the context in which they were given, or their significance. This simple exercise has a powerful effect on raising awareness to patients of the problematic nature of polydiagnosing.

Introduce de-diagnosing. The engagement of patients in the diagnostic process has a significant effect. Reviewing not only diagnostic criteria but also nosology and debates in our understanding of diagnoses can provide patients with further engagement in their care. A simple review of the debate of the bereavement exclusion may permit a patient to not only understand the complexity, but also the changing nature of diagnoses. Suddenly, they are no longer bystanders, but informed participants in their care.

Identify diagnoses most appropriate for removal. Contradictory diagnoses are common in the clinical settings we work in. We routinely see patients carrying multiple mood diagnoses, despite our diagnostic systems not permitting one to have both unipolar and bipolar depression. Superfluous diagnoses are also frequent, with patients receiving depressive, or anxious labels when in an acute state of psychosis or mania. This is exemplified by patients suffering from thought blocking and receiving cognitive or attention-related diagnoses. Concurrent yet different diagnoses are also common in patients with a different list of diagnoses by their primary care provider, their therapist, and their psychiatrist. This is particularly problematic as it forces the patient to alternate their thinking or choose between their providers.

Create a new narrative for the patient. Once diagnoses are explained, clarified, and understood, patients with the help of their providers can reexamine their life story under a new and simplified construct. This process often leads to a less confusing sense of self, an increased dedication to the treatment process, whether behavioral, social, psychological, or pharmacologic.

Consider deprescribing. With a more straightforward and more grounded list of diagnoses (or simply one diagnosis), we find the process of deprescribing to be simpler and more engaging for patients. For example, patients can clearly understand the lack of necessity of an antipsychotic prescription for a resolved substance-induced psychosis. Patients are more engaged in their care, leading to improved medication compliance and less attachment to discontinued medications.

Monitor and adapt. One should of course reevaluate diagnoses as the course of illness provides us with additional information. However, we suggest waiting for a manic episode to emerge prior to diagnosing bipolar rather than suggesting the diagnosis because a patient was wearing red shoes, spoke multiple languages, had multiple degrees and was creative.¹⁰ The contextual basis and progression of the symptoms should lead to continual reassessment of diagnoses.

Physicians are aware of the balance between Occam’s razor, which promotes the simplest single explanation for a problem, versus Hickam’s dictum that reminds us that patients can have as many diseases as they please. However, similarly to polypharmacy, “polydiagnosing” has negative effects. While the field of psychiatry’s advancing knowledge may encourage providers to diagnose their patients with the growing number of diagnoses, patients still need and benefit from a coherent and clear medical narrative. Psychiatry would be wise to recognize this concerning trend, in its attempt at rectifying polypharmacy.

Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. He has no conflicts of interest. Dr. Lehman is a professor of psychiatry at the University of California, San Diego. He is codirector of all acute and intensive psychiatric treatment at the Veterans Affairs Medical Center in San Diego, where he practices clinical psychiatry. He has no conflicts of interest.

References

1. Gupta S & Cahill JD. A prescription for “deprescribing” in psychiatry. Psychiatr Serv. 2016 Aug 1;67(8):904-7. doi: 10.1176/appi.ps.201500359.

2. Schuckit MA. Comorbidity between substance use disorders and psychiatric conditions. Addiction. 2006 Sep;101 Suppl 1:76-88. doi: 10.1111/j.1360-0443.2006.01592.x.

3. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR). American Psychiatric Association, 2022. https://psychiatry.org/psychiatrists/practice/dsm.

4. Kendler KS. An historical framework for psychiatric nosology. Psychol Med. 2009 Dec;39(12):1935-41. doi: 10.1017/S0033291709005753.

5. Regier DA et al. DSM-5 field trials in the United States and Canada. Am J Psychiatry. 2013 Jan;170(1):59-70. doi: 10.1176/appi.ajp.2012.12070999.

6. Bhattacharya R et al. When good news is bad news: psychological impact of false-positive diagnosis of HIV. AIDS Care. 2008 May;20(5):560-4. doi: 10.1080/09540120701867206.

7. Reeve E et al. Review of deprescribing processes and development of an evidence‐based, patient‐centred deprescribing process. Br J Clin Pharmacol. 2014 Oct;78(4):738-47. doi: 10.1111/bcp.12386.

8. Gupta S and Cahill JD. A prescription for “deprescribing” in psychiatry.

9. Solomon M. “On the appearance and disappearance of Asperger’s syndrome” in Kendler and Parnas (eds.) Philosophical Issues in Psychiatry IV: Classification of Psychiatric Illness. Oxford University Press, 2017. doi: 10.1093/med/9780198796022.003.0023.

10. Akiskal HS. Searching for behavioral indicators of bipolar II in patients presenting with major depressive episodes: The “red sign,” the “rule of three,” and other biographic signs of temperamental extravagance, activation, and hypomania. J Affect Disord. 2005 Feb;84(2-3):279-90. doi: 10.1016/j.jad.2004.06.002.

In 2016, Gupta and Cahill challenged the field of psychiatry to reexamine prescribing patterns.¹ They warned against the use of polypharmacy when not attached to improved patient functioning. They were concerned with the limited evidence for polypharmacy as well as DSM diagnostic criteria. In their inspiring article, they described a process of deprescribing.

In an effort to study and practice their recommendations, we have noticed a lack of literature examining the elimination of diagnostic labels. While there have been some studies looking at comorbidity, especially with substance use disorders,² there is a paucity of scientific evidence on patients with numerous diagnoses. Yet our practices are filled with patients who have been labeled with multiple conflicting or redundant diagnoses throughout their lives depending on the setting or the orientation of the practitioner.

The DSM-5 warns against diagnosing disorders when “the occurrence … is not better explained by” another disorder.³ A mix of diagnoses creates confusion for patients as well as clinicians trying to sort through their reported psychiatric histories.

A routine example would include a patient presenting for an initial evaluation and stating “I’ve been diagnosed as manic-depressive, high anxiety, split personality, posttraumatic stress, insomnia, ADD, and depression.” A review of the medical record will reveal a list of diagnoses, including bipolar II, generalized anxiety disorder, borderline personality disorder, posttraumatic stress disorder, unspecified insomnia, attention-deficit/hyperactivity disorder, and major depressive disorder. The medication list includes lamotrigine, valproic acid, citalopram, bupropion, buspirone, prazosin, methylphenidate, clonazepam, hydroxyzine, and low-dose quetiapine at night as needed.

This is an example of polypharmacy treating multiple, and at times conflicting, diagnoses. While an extreme case, in our experience, cases like this are not uncommon. It was actually in our efforts to examine deprescribing that we noticed this quandary. When inquiring about patients on many psychotropic medications, we often receive this retort: the patient is only prescribed one medication per disorder. Some providers have the belief that multiple disorders justify multiple medications, and that this tautological thinking legitimizes polypharmacy.

A patient who has varying moods, some fears, a fluctuating temperament, past traumas, occasional difficulty sleeping, intermittent inattention, and some sadness may be given all the diagnoses listed above and the resulting medication list. The multiplication of diagnoses, “polydiagnosing,” is a convenient justification for future polypharmacy. A lack of careful assessment and thinking in the application of new diagnoses permits the use of increasing numbers of pharmacological agents. A constellation of symptoms of anxiety, concentration deficits, affective dysregulation, and psychosis may justify the combination of benzodiazepines, stimulants, mood stabilizers, and antipsychotics, while a patient with “just” schizophrenia who is sometimes sad, scared, or distracted is more likely to be kept on just one medication, likely an antipsychotic.

Contrary to most medical disorders (for example, tuberculosis) but similar to others (for example, chronic pain), psychiatric disorders are based on the opinion of a “modest number of ‘expert’ classifications.”⁴ While the broad categories of disorders are justifiable, individual diagnoses are burdened with high rates of comorbidity; lack of treatment specificity; and evidence that distinct syndromes share a genetic basis. Those concerns were exemplified in the study examining the inter-rater reliability of DSM-5 diagnoses, where many disorders were found to have questionable validity.⁵

A psychiatric diagnosis should be based on biological, psychological, and social factors, which align with our understanding of the natural course of an illness. A patient presenting with transient symptoms of sadness in the context of significant social factors like homelessness and/or significant biological factors associated with schizophrenia should not reflexively receive an additional diagnosis of a depressive disorder. A patient reporting poor concentration in the context of a manic episode should not receive an additional diagnosis of attention-deficit disorder. An older patient with depression on multiple antipsychotics for adjunctive treatment should not necessarily receive a diagnosis of cognitive disorder at the first sign of memory problems.

The cavalier and inconsistent use of diagnoses renders the patients with no clear narrative of who they are. They end up integrating the varying providers’ opinions as a cacophony of labels of unclear significance. Many patients have contradictory diagnoses like major depressive disorder and bipolar disorder, or schizophrenia and schizoaffective disorder. Those inaccurate diagnoses could not only lead to treatment mistakes, but also psychological harm.⁶

A clearer diagnostic picture is not only more scientifically sound but also more coherent to the patient. This in turn can lead to an improved treatment alliance and buy-in from the patient. Assisting a patient in sorting out and understanding the vast arrays of diagnostic labels they may hear throughout their treatment can serve as a tool for psychoeducation, empowerment, and control over their own care and themselves.

How should a provider practice de-diagnosing? Based on the work of Reeve, et al.,⁷ on the principles crucial to deprescribing, and subsequent research by Gupta and Cahill,⁸ we compiled a list of considerations for practitioners wishing to engage in this type of work with their patients.
 

Choose the right time. While insurance companies require diagnostic findings from the first visit, abrupt de-diagnosing for the sake of simplifying the record from that first visit could be detrimental. Patients can become attached to and find meaning in their diagnostic labels. This was exemplified with the removal of Asperger’s syndrome from the DSM-5.⁹ Acute symptomatology may be an opportune time to revisit the core pathology of a patient, or a poor time for a patient to have this discussion.

Compile a list of all the patient’s diagnoses. Our initial visits are often illuminated when patients enumerate the vast number of diagnoses they have been given by different providers. Patients will often list half a dozen diagnoses. The patterns often follow life courses with ADHD, conduct disorder, and learning disability in childhood; with anxiety, depression, and/or bipolar disorder in early adulthood; to complicated grief, depression with pseudodementia, and neurocognitive disorders in older adults. Yet patients rarely appreciate the temporary or episodic nature of mental disorders and instead accumulate diagnoses at each change of provider.

Initiate discussion with the patient. It is meaningful to see if patients resonate with the question, “Do you ever feel like every psychiatrist you have seen has given you a different diagnosis?” In our experience, patients’ reactions to this question usually exemplify the problematic nature of the vast array of diagnoses our patients are given. The majority of them are unable to confidently explain the meaning of those diagnoses, the context in which they were given, or their significance. This simple exercise has a powerful effect on raising awareness to patients of the problematic nature of polydiagnosing.

Introduce de-diagnosing. The engagement of patients in the diagnostic process has a significant effect. Reviewing not only diagnostic criteria but also nosology and debates in our understanding of diagnoses can provide patients with further engagement in their care. A simple review of the debate of the bereavement exclusion may permit a patient to not only understand the complexity, but also the changing nature of diagnoses. Suddenly, they are no longer bystanders, but informed participants in their care.

Identify diagnoses most appropriate for removal. Contradictory diagnoses are common in the clinical settings we work in. We routinely see patients carrying multiple mood diagnoses, despite our diagnostic systems not permitting one to have both unipolar and bipolar depression. Superfluous diagnoses are also frequent, with patients receiving depressive, or anxious labels when in an acute state of psychosis or mania. This is exemplified by patients suffering from thought blocking and receiving cognitive or attention-related diagnoses. Concurrent yet different diagnoses are also common in patients with a different list of diagnoses by their primary care provider, their therapist, and their psychiatrist. This is particularly problematic as it forces the patient to alternate their thinking or choose between their providers.

Create a new narrative for the patient. Once diagnoses are explained, clarified, and understood, patients with the help of their providers can reexamine their life story under a new and simplified construct. This process often leads to a less confusing sense of self, an increased dedication to the treatment process, whether behavioral, social, psychological, or pharmacologic.

Consider deprescribing. With a more straightforward and more grounded list of diagnoses (or simply one diagnosis), we find the process of deprescribing to be simpler and more engaging for patients. For example, patients can clearly understand the lack of necessity of an antipsychotic prescription for a resolved substance-induced psychosis. Patients are more engaged in their care, leading to improved medication compliance and less attachment to discontinued medications.

Monitor and adapt. One should of course reevaluate diagnoses as the course of illness provides us with additional information. However, we suggest waiting for a manic episode to emerge prior to diagnosing bipolar rather than suggesting the diagnosis because a patient was wearing red shoes, spoke multiple languages, had multiple degrees and was creative.¹⁰ The contextual basis and progression of the symptoms should lead to continual reassessment of diagnoses.

Physicians are aware of the balance between Occam’s razor, which promotes the simplest single explanation for a problem, versus Hickam’s dictum that reminds us that patients can have as many diseases as they please. However, similarly to polypharmacy, “polydiagnosing” has negative effects. While the field of psychiatry’s advancing knowledge may encourage providers to diagnose their patients with the growing number of diagnoses, patients still need and benefit from a coherent and clear medical narrative. Psychiatry would be wise to recognize this concerning trend, in its attempt at rectifying polypharmacy.

Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. He has no conflicts of interest. Dr. Lehman is a professor of psychiatry at the University of California, San Diego. He is codirector of all acute and intensive psychiatric treatment at the Veterans Affairs Medical Center in San Diego, where he practices clinical psychiatry. He has no conflicts of interest.

References

1. Gupta S & Cahill JD. A prescription for “deprescribing” in psychiatry. Psychiatr Serv. 2016 Aug 1;67(8):904-7. doi: 10.1176/appi.ps.201500359.

2. Schuckit MA. Comorbidity between substance use disorders and psychiatric conditions. Addiction. 2006 Sep;101 Suppl 1:76-88. doi: 10.1111/j.1360-0443.2006.01592.x.

3. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR). American Psychiatric Association, 2022. https://psychiatry.org/psychiatrists/practice/dsm.

4. Kendler KS. An historical framework for psychiatric nosology. Psychol Med. 2009 Dec;39(12):1935-41. doi: 10.1017/S0033291709005753.

5. Regier DA et al. DSM-5 field trials in the United States and Canada. Am J Psychiatry. 2013 Jan;170(1):59-70. doi: 10.1176/appi.ajp.2012.12070999.

6. Bhattacharya R et al. When good news is bad news: psychological impact of false-positive diagnosis of HIV. AIDS Care. 2008 May;20(5):560-4. doi: 10.1080/09540120701867206.

7. Reeve E et al. Review of deprescribing processes and development of an evidence‐based, patient‐centred deprescribing process. Br J Clin Pharmacol. 2014 Oct;78(4):738-47. doi: 10.1111/bcp.12386.

8. Gupta S and Cahill JD. A prescription for “deprescribing” in psychiatry.

9. Solomon M. “On the appearance and disappearance of Asperger’s syndrome” in Kendler and Parnas (eds.) Philosophical Issues in Psychiatry IV: Classification of Psychiatric Illness. Oxford University Press, 2017. doi: 10.1093/med/9780198796022.003.0023.

10. Akiskal HS. Searching for behavioral indicators of bipolar II in patients presenting with major depressive episodes: The “red sign,” the “rule of three,” and other biographic signs of temperamental extravagance, activation, and hypomania. J Affect Disord. 2005 Feb;84(2-3):279-90. doi: 10.1016/j.jad.2004.06.002.

In 2016, Gupta and Cahill challenged the field of psychiatry to reexamine prescribing patterns.¹ They warned against the use of polypharmacy when not attached to improved patient functioning. They were concerned with the limited evidence for polypharmacy as well as DSM diagnostic criteria. In their inspiring article, they described a process of deprescribing.

In an effort to study and practice their recommendations, we have noticed a lack of literature examining the elimination of diagnostic labels. While there have been some studies looking at comorbidity, especially with substance use disorders,² there is a paucity of scientific evidence on patients with numerous diagnoses. Yet our practices are filled with patients who have been labeled with multiple conflicting or redundant diagnoses throughout their lives depending on the setting or the orientation of the practitioner.

The DSM-5 warns against diagnosing disorders when “the occurrence … is not better explained by” another disorder.³ A mix of diagnoses creates confusion for patients as well as clinicians trying to sort through their reported psychiatric histories.

A routine example would include a patient presenting for an initial evaluation and stating “I’ve been diagnosed as manic-depressive, high anxiety, split personality, posttraumatic stress, insomnia, ADD, and depression.” A review of the medical record will reveal a list of diagnoses, including bipolar II, generalized anxiety disorder, borderline personality disorder, posttraumatic stress disorder, unspecified insomnia, attention-deficit/hyperactivity disorder, and major depressive disorder. The medication list includes lamotrigine, valproic acid, citalopram, bupropion, buspirone, prazosin, methylphenidate, clonazepam, hydroxyzine, and low-dose quetiapine at night as needed.

This is an example of polypharmacy treating multiple, and at times conflicting, diagnoses. While an extreme case, in our experience, cases like this are not uncommon. It was actually in our efforts to examine deprescribing that we noticed this quandary. When inquiring about patients on many psychotropic medications, we often receive this retort: the patient is only prescribed one medication per disorder. Some providers have the belief that multiple disorders justify multiple medications, and that this tautological thinking legitimizes polypharmacy.

A patient who has varying moods, some fears, a fluctuating temperament, past traumas, occasional difficulty sleeping, intermittent inattention, and some sadness may be given all the diagnoses listed above and the resulting medication list. The multiplication of diagnoses, “polydiagnosing,” is a convenient justification for future polypharmacy. A lack of careful assessment and thinking in the application of new diagnoses permits the use of increasing numbers of pharmacological agents. A constellation of symptoms of anxiety, concentration deficits, affective dysregulation, and psychosis may justify the combination of benzodiazepines, stimulants, mood stabilizers, and antipsychotics, while a patient with “just” schizophrenia who is sometimes sad, scared, or distracted is more likely to be kept on just one medication, likely an antipsychotic.

Contrary to most medical disorders (for example, tuberculosis) but similar to others (for example, chronic pain), psychiatric disorders are based on the opinion of a “modest number of ‘expert’ classifications.”⁴ While the broad categories of disorders are justifiable, individual diagnoses are burdened with high rates of comorbidity; lack of treatment specificity; and evidence that distinct syndromes share a genetic basis. Those concerns were exemplified in the study examining the inter-rater reliability of DSM-5 diagnoses, where many disorders were found to have questionable validity.⁵

A psychiatric diagnosis should be based on biological, psychological, and social factors, which align with our understanding of the natural course of an illness. A patient presenting with transient symptoms of sadness in the context of significant social factors like homelessness and/or significant biological factors associated with schizophrenia should not reflexively receive an additional diagnosis of a depressive disorder. A patient reporting poor concentration in the context of a manic episode should not receive an additional diagnosis of attention-deficit disorder. An older patient with depression on multiple antipsychotics for adjunctive treatment should not necessarily receive a diagnosis of cognitive disorder at the first sign of memory problems.

The cavalier and inconsistent use of diagnoses renders the patients with no clear narrative of who they are. They end up integrating the varying providers’ opinions as a cacophony of labels of unclear significance. Many patients have contradictory diagnoses like major depressive disorder and bipolar disorder, or schizophrenia and schizoaffective disorder. Those inaccurate diagnoses could not only lead to treatment mistakes, but also psychological harm.⁶

A clearer diagnostic picture is not only more scientifically sound but also more coherent to the patient. This in turn can lead to an improved treatment alliance and buy-in from the patient. Assisting a patient in sorting out and understanding the vast arrays of diagnostic labels they may hear throughout their treatment can serve as a tool for psychoeducation, empowerment, and control over their own care and themselves.

How should a provider practice de-diagnosing? Based on the work of Reeve, et al.,⁷ on the principles crucial to deprescribing, and subsequent research by Gupta and Cahill,⁸ we compiled a list of considerations for practitioners wishing to engage in this type of work with their patients.
 

Choose the right time. While insurance companies require diagnostic findings from the first visit, abrupt de-diagnosing for the sake of simplifying the record from that first visit could be detrimental. Patients can become attached to and find meaning in their diagnostic labels. This was exemplified with the removal of Asperger’s syndrome from the DSM-5.⁹ Acute symptomatology may be an opportune time to revisit the core pathology of a patient, or a poor time for a patient to have this discussion.

Compile a list of all the patient’s diagnoses. Our initial visits are often illuminated when patients enumerate the vast number of diagnoses they have been given by different providers. Patients will often list half a dozen diagnoses. The patterns often follow life courses with ADHD, conduct disorder, and learning disability in childhood; with anxiety, depression, and/or bipolar disorder in early adulthood; to complicated grief, depression with pseudodementia, and neurocognitive disorders in older adults. Yet patients rarely appreciate the temporary or episodic nature of mental disorders and instead accumulate diagnoses at each change of provider.

Initiate discussion with the patient. It is meaningful to see if patients resonate with the question, “Do you ever feel like every psychiatrist you have seen has given you a different diagnosis?” In our experience, patients’ reactions to this question usually exemplify the problematic nature of the vast array of diagnoses our patients are given. The majority of them are unable to confidently explain the meaning of those diagnoses, the context in which they were given, or their significance. This simple exercise has a powerful effect on raising awareness to patients of the problematic nature of polydiagnosing.

Introduce de-diagnosing. The engagement of patients in the diagnostic process has a significant effect. Reviewing not only diagnostic criteria but also nosology and debates in our understanding of diagnoses can provide patients with further engagement in their care. A simple review of the debate of the bereavement exclusion may permit a patient to not only understand the complexity, but also the changing nature of diagnoses. Suddenly, they are no longer bystanders, but informed participants in their care.

Identify diagnoses most appropriate for removal. Contradictory diagnoses are common in the clinical settings we work in. We routinely see patients carrying multiple mood diagnoses, despite our diagnostic systems not permitting one to have both unipolar and bipolar depression. Superfluous diagnoses are also frequent, with patients receiving depressive, or anxious labels when in an acute state of psychosis or mania. This is exemplified by patients suffering from thought blocking and receiving cognitive or attention-related diagnoses. Concurrent yet different diagnoses are also common in patients with a different list of diagnoses by their primary care provider, their therapist, and their psychiatrist. This is particularly problematic as it forces the patient to alternate their thinking or choose between their providers.

Create a new narrative for the patient. Once diagnoses are explained, clarified, and understood, patients with the help of their providers can reexamine their life story under a new and simplified construct. This process often leads to a less confusing sense of self, an increased dedication to the treatment process, whether behavioral, social, psychological, or pharmacologic.

Consider deprescribing. With a more straightforward and more grounded list of diagnoses (or simply one diagnosis), we find the process of deprescribing to be simpler and more engaging for patients. For example, patients can clearly understand the lack of necessity of an antipsychotic prescription for a resolved substance-induced psychosis. Patients are more engaged in their care, leading to improved medication compliance and less attachment to discontinued medications.

Monitor and adapt. One should of course reevaluate diagnoses as the course of illness provides us with additional information. However, we suggest waiting for a manic episode to emerge prior to diagnosing bipolar rather than suggesting the diagnosis because a patient was wearing red shoes, spoke multiple languages, had multiple degrees and was creative.¹⁰ The contextual basis and progression of the symptoms should lead to continual reassessment of diagnoses.

Physicians are aware of the balance between Occam’s razor, which promotes the simplest single explanation for a problem, versus Hickam’s dictum that reminds us that patients can have as many diseases as they please. However, similarly to polypharmacy, “polydiagnosing” has negative effects. While the field of psychiatry’s advancing knowledge may encourage providers to diagnose their patients with the growing number of diagnoses, patients still need and benefit from a coherent and clear medical narrative. Psychiatry would be wise to recognize this concerning trend, in its attempt at rectifying polypharmacy.

Dr. Badre is a clinical and forensic psychiatrist in San Diego. He holds teaching positions at the University of California, San Diego, and the University of San Diego. He teaches medical education, psychopharmacology, ethics in psychiatry, and correctional care. Dr. Badre can be reached at his website, BadreMD.com. He has no conflicts of interest. Dr. Lehman is a professor of psychiatry at the University of California, San Diego. He is codirector of all acute and intensive psychiatric treatment at the Veterans Affairs Medical Center in San Diego, where he practices clinical psychiatry. He has no conflicts of interest.

References

1. Gupta S & Cahill JD. A prescription for “deprescribing” in psychiatry. Psychiatr Serv. 2016 Aug 1;67(8):904-7. doi: 10.1176/appi.ps.201500359.

2. Schuckit MA. Comorbidity between substance use disorders and psychiatric conditions. Addiction. 2006 Sep;101 Suppl 1:76-88. doi: 10.1111/j.1360-0443.2006.01592.x.

3. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR). American Psychiatric Association, 2022. https://psychiatry.org/psychiatrists/practice/dsm.

4. Kendler KS. An historical framework for psychiatric nosology. Psychol Med. 2009 Dec;39(12):1935-41. doi: 10.1017/S0033291709005753.

5. Regier DA et al. DSM-5 field trials in the United States and Canada. Am J Psychiatry. 2013 Jan;170(1):59-70. doi: 10.1176/appi.ajp.2012.12070999.

6. Bhattacharya R et al. When good news is bad news: psychological impact of false-positive diagnosis of HIV. AIDS Care. 2008 May;20(5):560-4. doi: 10.1080/09540120701867206.

7. Reeve E et al. Review of deprescribing processes and development of an evidence‐based, patient‐centred deprescribing process. Br J Clin Pharmacol. 2014 Oct;78(4):738-47. doi: 10.1111/bcp.12386.

8. Gupta S and Cahill JD. A prescription for “deprescribing” in psychiatry.

9. Solomon M. “On the appearance and disappearance of Asperger’s syndrome” in Kendler and Parnas (eds.) Philosophical Issues in Psychiatry IV: Classification of Psychiatric Illness. Oxford University Press, 2017. doi: 10.1093/med/9780198796022.003.0023.

10. Akiskal HS. Searching for behavioral indicators of bipolar II in patients presenting with major depressive episodes: The “red sign,” the “rule of three,” and other biographic signs of temperamental extravagance, activation, and hypomania. J Affect Disord. 2005 Feb;84(2-3):279-90. doi: 10.1016/j.jad.2004.06.002.

For many years, COPD has remained one of the top four leading causes of death in the United States according to CDC data. Around the world, it is responsible for about 3 million deaths annually. It is estimated that 16 million Americans are now diagnosed with COPD. However, it is commonly agreed by experts that it is widely underdiagnosed and there may be millions more suffering from this disease.

The direct costs of COPD are around $49 billion a year in direct costs, with billions more in indirect costs. Around the globe, COPD is one of the top three causes of death, with 90% of deaths happening in low- and middle-income countries. The burden of COPD is expected to grow over time because of the aging population and continued exposure to COPD risk factors.

The Global Initiative for Chronic Obstructive Lung Disease report (or GOLD) is revised every year, translated into many languages, and used by health care workers globally. It was started in 1998, and its aim was to produce guidelines based on the best scientific evidence available that was nonbiased to be used for assessment, diagnosis, and treatment of patients with COPD. The first report was issued in 2001. The method of producing the GOLD report was to do a search of PubMed for evidence-based, peer-reviewed studies. Those not captured by this method could be submitted for review. The science committee then meets twice a year and reviews each publication, eventually agreeing on a set of guidelines/updates.
 

2022 GOLD Report

For the 2022 GOLD report, 160 new references were added. Overall, the GOLD report is five chapters (more than 150 pages) giving in-depth guidance for the diagnosis, prevention, management, and treatment of patients with stable COPD, COPD exacerbations, and hospitalized patients.

The report suggests that COPD is being underdiagnosed. It’s important for primary care doctors to understand the new guidelines, because they are the clinicians who are most likely to be diagnosing and treating patients with COPD.

Family physicians and internists will be seeing more and more cases as the population ages, and we need to do a better job of recognizing patients who have COPD. If possible, we should try to have spirometry available in our practices. Like any other disease, we know prevention works best so primary care physicians also need to be looking for risk factors, such as smoking history, and help patients try to reduce them if possible. Below is more explanation of the latest guidelines.

For most of us, when we learned about COPD as a disease, the terms “chronic bronchitis” and “emphysema” were emphasized. These words are no longer used as synonymous for COPD.

The disease is now described as involving chronic limitation in airflow that results from a combination of small airway disease and parenchymal destruction (emphysema). The rates of each vary from person to person and progress at different rates. Key factors that contribute to COPD disease burden include chronic inflammation, narrowing of small airways, loss of alveolar attachments, loss of elastic recoil, and mucociliary dysfunction, according to the 2022 GOLD report.

Respiratory symptoms may precede the onset of airflow limitation. COPD should be considered in any patient with dyspnea, chronic cough or sputum production, a history of recurrent lower respiratory tract infections, and risk factors for the disease.

The biggest risk factor for COPD is smoking. Other risk factors include occupational exposure, e-cigarette use, pollution, genetic factors, and comorbid conditions. Symptoms of the disease can include chest tightness, wheezing, and fatigue.

To make a diagnosis of COPD, spirometry is required, the latest GOLD report says. A postbronchodilator FEV₁/FVC less than 0.70 confirms persistent airflow limitation and hence COPD. This value is used in clinical trials and forms the basis of what most treatment guidelines are derived from. It would be beneficial for any physician treating COPD patients to have easy access to spirometry. It provides the most reproducible and objective measurement of airflow limitation. Also, it was found that assessing the degree of reversibility of airflow limitation to decide therapeutic decisions is no longer recommended and thus, asking the patient to stop inhaled medications beforehand is unnecessary. To access the impact COPD has on a patient’s life beyond dyspnea, the guidelines recommend doing a disease-specific health questionnaire, such as the COPD Assessment Test (CAT).

Along with patient symptoms and history of exacerbations, spirometry is crucial for the diagnosis, prognosis, and therapeutic decisions in COPD patients, according to the GOLD guidance. The best predictor of frequent exacerbations, however, is a history of previous exacerbations. In cases where there is a discrepancy between airflow limitation and symptoms, additional testing should be considered. Alpha-1 antitrypsin deficiency (AATD) screening should be considered in younger patients (under 45 years) with perilobular emphysema, and those in areas of high AATD prevalence. Chest x-rays are not recommended in diagnosing COPD but can be helpful if other comorbidities are present. CT scan is not routinely recommended but should be used only for the detection of bronchiectasis, if the patient meets the criteria for lung cancer screening, if surgery is necessary, or if other diseases may need to be evaluated.

Pulse oximetry can be helpful in accessing degree of severity, respiratory failure, and right heart failure. Walking tests can be helpful for evaluating disability and mortality risk. Other tests that have been used but are not routinely recommended include plethysmography and diffusing capacity of the lungs for carbon monoxide.

Composite scores can identify patients who are at increased risk of mortality. One such score is the BODE (Body mass, Obstruction, Dyspnea, and Exercise) method. Biomarkers are being investigated, but data are still not available to recommend their routine use.
 

Dr. Girgis practices family medicine in South River, N.J., and is a clinical assistant professor of family medicine at Robert Wood Johnson Medical School, New Brunswick, N.J. You can contact her at fpnews@mdedge.com.

For many years, COPD has remained one of the top four leading causes of death in the United States according to CDC data. Around the world, it is responsible for about 3 million deaths annually. It is estimated that 16 million Americans are now diagnosed with COPD. However, it is commonly agreed by experts that it is widely underdiagnosed and there may be millions more suffering from this disease.

The direct costs of COPD are around $49 billion a year in direct costs, with billions more in indirect costs. Around the globe, COPD is one of the top three causes of death, with 90% of deaths happening in low- and middle-income countries. The burden of COPD is expected to grow over time because of the aging population and continued exposure to COPD risk factors.

The Global Initiative for Chronic Obstructive Lung Disease report (or GOLD) is revised every year, translated into many languages, and used by health care workers globally. It was started in 1998, and its aim was to produce guidelines based on the best scientific evidence available that was nonbiased to be used for assessment, diagnosis, and treatment of patients with COPD. The first report was issued in 2001. The method of producing the GOLD report was to do a search of PubMed for evidence-based, peer-reviewed studies. Those not captured by this method could be submitted for review. The science committee then meets twice a year and reviews each publication, eventually agreeing on a set of guidelines/updates.
 

2022 GOLD Report

For the 2022 GOLD report, 160 new references were added. Overall, the GOLD report is five chapters (more than 150 pages) giving in-depth guidance for the diagnosis, prevention, management, and treatment of patients with stable COPD, COPD exacerbations, and hospitalized patients.

The report suggests that COPD is being underdiagnosed. It’s important for primary care doctors to understand the new guidelines, because they are the clinicians who are most likely to be diagnosing and treating patients with COPD.

Family physicians and internists will be seeing more and more cases as the population ages, and we need to do a better job of recognizing patients who have COPD. If possible, we should try to have spirometry available in our practices. Like any other disease, we know prevention works best so primary care physicians also need to be looking for risk factors, such as smoking history, and help patients try to reduce them if possible. Below is more explanation of the latest guidelines.

For most of us, when we learned about COPD as a disease, the terms “chronic bronchitis” and “emphysema” were emphasized. These words are no longer used as synonymous for COPD.

The disease is now described as involving chronic limitation in airflow that results from a combination of small airway disease and parenchymal destruction (emphysema). The rates of each vary from person to person and progress at different rates. Key factors that contribute to COPD disease burden include chronic inflammation, narrowing of small airways, loss of alveolar attachments, loss of elastic recoil, and mucociliary dysfunction, according to the 2022 GOLD report.

Respiratory symptoms may precede the onset of airflow limitation. COPD should be considered in any patient with dyspnea, chronic cough or sputum production, a history of recurrent lower respiratory tract infections, and risk factors for the disease.

The biggest risk factor for COPD is smoking. Other risk factors include occupational exposure, e-cigarette use, pollution, genetic factors, and comorbid conditions. Symptoms of the disease can include chest tightness, wheezing, and fatigue.

To make a diagnosis of COPD, spirometry is required, the latest GOLD report says. A postbronchodilator FEV₁/FVC less than 0.70 confirms persistent airflow limitation and hence COPD. This value is used in clinical trials and forms the basis of what most treatment guidelines are derived from. It would be beneficial for any physician treating COPD patients to have easy access to spirometry. It provides the most reproducible and objective measurement of airflow limitation. Also, it was found that assessing the degree of reversibility of airflow limitation to decide therapeutic decisions is no longer recommended and thus, asking the patient to stop inhaled medications beforehand is unnecessary. To access the impact COPD has on a patient’s life beyond dyspnea, the guidelines recommend doing a disease-specific health questionnaire, such as the COPD Assessment Test (CAT).

Along with patient symptoms and history of exacerbations, spirometry is crucial for the diagnosis, prognosis, and therapeutic decisions in COPD patients, according to the GOLD guidance. The best predictor of frequent exacerbations, however, is a history of previous exacerbations. In cases where there is a discrepancy between airflow limitation and symptoms, additional testing should be considered. Alpha-1 antitrypsin deficiency (AATD) screening should be considered in younger patients (under 45 years) with perilobular emphysema, and those in areas of high AATD prevalence. Chest x-rays are not recommended in diagnosing COPD but can be helpful if other comorbidities are present. CT scan is not routinely recommended but should be used only for the detection of bronchiectasis, if the patient meets the criteria for lung cancer screening, if surgery is necessary, or if other diseases may need to be evaluated.

Pulse oximetry can be helpful in accessing degree of severity, respiratory failure, and right heart failure. Walking tests can be helpful for evaluating disability and mortality risk. Other tests that have been used but are not routinely recommended include plethysmography and diffusing capacity of the lungs for carbon monoxide.

Composite scores can identify patients who are at increased risk of mortality. One such score is the BODE (Body mass, Obstruction, Dyspnea, and Exercise) method. Biomarkers are being investigated, but data are still not available to recommend their routine use.
 

Dr. Girgis practices family medicine in South River, N.J., and is a clinical assistant professor of family medicine at Robert Wood Johnson Medical School, New Brunswick, N.J. You can contact her at fpnews@mdedge.com.

For many years, COPD has remained one of the top four leading causes of death in the United States according to CDC data. Around the world, it is responsible for about 3 million deaths annually. It is estimated that 16 million Americans are now diagnosed with COPD. However, it is commonly agreed by experts that it is widely underdiagnosed and there may be millions more suffering from this disease.

The direct costs of COPD are around $49 billion a year in direct costs, with billions more in indirect costs. Around the globe, COPD is one of the top three causes of death, with 90% of deaths happening in low- and middle-income countries. The burden of COPD is expected to grow over time because of the aging population and continued exposure to COPD risk factors.

The Global Initiative for Chronic Obstructive Lung Disease report (or GOLD) is revised every year, translated into many languages, and used by health care workers globally. It was started in 1998, and its aim was to produce guidelines based on the best scientific evidence available that was nonbiased to be used for assessment, diagnosis, and treatment of patients with COPD. The first report was issued in 2001. The method of producing the GOLD report was to do a search of PubMed for evidence-based, peer-reviewed studies. Those not captured by this method could be submitted for review. The science committee then meets twice a year and reviews each publication, eventually agreeing on a set of guidelines/updates.
 

2022 GOLD Report

For the 2022 GOLD report, 160 new references were added. Overall, the GOLD report is five chapters (more than 150 pages) giving in-depth guidance for the diagnosis, prevention, management, and treatment of patients with stable COPD, COPD exacerbations, and hospitalized patients.

The report suggests that COPD is being underdiagnosed. It’s important for primary care doctors to understand the new guidelines, because they are the clinicians who are most likely to be diagnosing and treating patients with COPD.

Family physicians and internists will be seeing more and more cases as the population ages, and we need to do a better job of recognizing patients who have COPD. If possible, we should try to have spirometry available in our practices. Like any other disease, we know prevention works best so primary care physicians also need to be looking for risk factors, such as smoking history, and help patients try to reduce them if possible. Below is more explanation of the latest guidelines.

For most of us, when we learned about COPD as a disease, the terms “chronic bronchitis” and “emphysema” were emphasized. These words are no longer used as synonymous for COPD.

The disease is now described as involving chronic limitation in airflow that results from a combination of small airway disease and parenchymal destruction (emphysema). The rates of each vary from person to person and progress at different rates. Key factors that contribute to COPD disease burden include chronic inflammation, narrowing of small airways, loss of alveolar attachments, loss of elastic recoil, and mucociliary dysfunction, according to the 2022 GOLD report.

Respiratory symptoms may precede the onset of airflow limitation. COPD should be considered in any patient with dyspnea, chronic cough or sputum production, a history of recurrent lower respiratory tract infections, and risk factors for the disease.

The biggest risk factor for COPD is smoking. Other risk factors include occupational exposure, e-cigarette use, pollution, genetic factors, and comorbid conditions. Symptoms of the disease can include chest tightness, wheezing, and fatigue.

To make a diagnosis of COPD, spirometry is required, the latest GOLD report says. A postbronchodilator FEV₁/FVC less than 0.70 confirms persistent airflow limitation and hence COPD. This value is used in clinical trials and forms the basis of what most treatment guidelines are derived from. It would be beneficial for any physician treating COPD patients to have easy access to spirometry. It provides the most reproducible and objective measurement of airflow limitation. Also, it was found that assessing the degree of reversibility of airflow limitation to decide therapeutic decisions is no longer recommended and thus, asking the patient to stop inhaled medications beforehand is unnecessary. To access the impact COPD has on a patient’s life beyond dyspnea, the guidelines recommend doing a disease-specific health questionnaire, such as the COPD Assessment Test (CAT).

Along with patient symptoms and history of exacerbations, spirometry is crucial for the diagnosis, prognosis, and therapeutic decisions in COPD patients, according to the GOLD guidance. The best predictor of frequent exacerbations, however, is a history of previous exacerbations. In cases where there is a discrepancy between airflow limitation and symptoms, additional testing should be considered. Alpha-1 antitrypsin deficiency (AATD) screening should be considered in younger patients (under 45 years) with perilobular emphysema, and those in areas of high AATD prevalence. Chest x-rays are not recommended in diagnosing COPD but can be helpful if other comorbidities are present. CT scan is not routinely recommended but should be used only for the detection of bronchiectasis, if the patient meets the criteria for lung cancer screening, if surgery is necessary, or if other diseases may need to be evaluated.

Pulse oximetry can be helpful in accessing degree of severity, respiratory failure, and right heart failure. Walking tests can be helpful for evaluating disability and mortality risk. Other tests that have been used but are not routinely recommended include plethysmography and diffusing capacity of the lungs for carbon monoxide.

Composite scores can identify patients who are at increased risk of mortality. One such score is the BODE (Body mass, Obstruction, Dyspnea, and Exercise) method. Biomarkers are being investigated, but data are still not available to recommend their routine use.
 

Dr. Girgis practices family medicine in South River, N.J., and is a clinical assistant professor of family medicine at Robert Wood Johnson Medical School, New Brunswick, N.J. You can contact her at fpnews@mdedge.com.

As a physician who has had a career-long obsession with the underappreciated value of sleep, a recent study published in the journal Child Development caught my eye. The findings presented by a group of Australian-based psychologists and educators suggest a positive association between napping and learning by preschool children. While the study itself relied on a very small sample and may not prove to be repeatable, the authors included in their introduction an excellent discussion of a large collection of recent studies supporting the educational benefit of sleep in general and napping in particular.

Although sleep seems to finally be receiving some of the attention it deserves, I am still concerned that as a profession we are failing to give it the appropriate weight at our health maintenance visits. This is particularly true of napping. Understandably, napping doesn’t feel urgent to parents in those turbulent first 4 or 5 months of night wakings and erratic settling. However, as a child approaches the 6-month milestone, napping is a topic ripe for well-considered anticipatory guidance.

When the recurrent cycles of awake-eat-sleep begin to develop into a somewhat predictable pattern and solid food is introduced, it’s time to suggest to parents a strategy that will encourage a napping pattern that will hopefully habituate into toddlerhood and beyond.

It can begin simply as a matter of defining the feeding in the middle of the day as lunch and then programming the period immediately following that meal as a siesta – a segment of the day completely reserved for rest. Many warm-weather countries have been using this strategy for centuries. Try to go to the pharmacy to pick up a prescription at 2 o’clock in the afternoon in rural Spain. It just ain’t gonna happen.

Most adults and children I know seem to be sleepy during this midday postprandial period. It makes more than a little sense to harness this natural drowsiness into creating a napping habit. However, the challenge for many young families is controlling their schedule to create a period of time when nothing else is going on in the child’s environment, leaving sleep as the only option. For some parents this requires the discipline to pause their own lives long enough so that the children realize that they aren’t missing out on something fun. This means no TV, no phone conversations, no visitors. Obviously, it also means not scheduling any appointments during this siesta period. Skilled day care providers have been doing this for years. But the message hasn’t seeped into the general population and sadly I occasionally see mothers with toddlers in the grocery store at 1 in the afternoon.

Once the nap/siesta is firmly welded to lunch, this gives the parent the ability to make minor adjustments that reflect the child’s stamina. If the child seems to be tiring/getting grumpy, serve up lunch a bit early and the restorative nap follows. As the child gets older and his or her stamina improves he or she may not be sleepy but the siesta remains as a quiet time. Some days it may be a nap, some days just a rest for an hour. By counseling parents to define the period after lunch as a siesta you will be helping them avoid that dreaded transition period called “giving up the nap.”

You may already be including this strategy in your anticipatory guidance. It may help to add to your advice the accumulating evidence that napping may play an important role in the child’s development and education.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

As a physician who has had a career-long obsession with the underappreciated value of sleep, a recent study published in the journal Child Development caught my eye. The findings presented by a group of Australian-based psychologists and educators suggest a positive association between napping and learning by preschool children. While the study itself relied on a very small sample and may not prove to be repeatable, the authors included in their introduction an excellent discussion of a large collection of recent studies supporting the educational benefit of sleep in general and napping in particular.

Although sleep seems to finally be receiving some of the attention it deserves, I am still concerned that as a profession we are failing to give it the appropriate weight at our health maintenance visits. This is particularly true of napping. Understandably, napping doesn’t feel urgent to parents in those turbulent first 4 or 5 months of night wakings and erratic settling. However, as a child approaches the 6-month milestone, napping is a topic ripe for well-considered anticipatory guidance.

When the recurrent cycles of awake-eat-sleep begin to develop into a somewhat predictable pattern and solid food is introduced, it’s time to suggest to parents a strategy that will encourage a napping pattern that will hopefully habituate into toddlerhood and beyond.

It can begin simply as a matter of defining the feeding in the middle of the day as lunch and then programming the period immediately following that meal as a siesta – a segment of the day completely reserved for rest. Many warm-weather countries have been using this strategy for centuries. Try to go to the pharmacy to pick up a prescription at 2 o’clock in the afternoon in rural Spain. It just ain’t gonna happen.

Most adults and children I know seem to be sleepy during this midday postprandial period. It makes more than a little sense to harness this natural drowsiness into creating a napping habit. However, the challenge for many young families is controlling their schedule to create a period of time when nothing else is going on in the child’s environment, leaving sleep as the only option. For some parents this requires the discipline to pause their own lives long enough so that the children realize that they aren’t missing out on something fun. This means no TV, no phone conversations, no visitors. Obviously, it also means not scheduling any appointments during this siesta period. Skilled day care providers have been doing this for years. But the message hasn’t seeped into the general population and sadly I occasionally see mothers with toddlers in the grocery store at 1 in the afternoon.

Once the nap/siesta is firmly welded to lunch, this gives the parent the ability to make minor adjustments that reflect the child’s stamina. If the child seems to be tiring/getting grumpy, serve up lunch a bit early and the restorative nap follows. As the child gets older and his or her stamina improves he or she may not be sleepy but the siesta remains as a quiet time. Some days it may be a nap, some days just a rest for an hour. By counseling parents to define the period after lunch as a siesta you will be helping them avoid that dreaded transition period called “giving up the nap.”

You may already be including this strategy in your anticipatory guidance. It may help to add to your advice the accumulating evidence that napping may play an important role in the child’s development and education.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

As a physician who has had a career-long obsession with the underappreciated value of sleep, a recent study published in the journal Child Development caught my eye. The findings presented by a group of Australian-based psychologists and educators suggest a positive association between napping and learning by preschool children. While the study itself relied on a very small sample and may not prove to be repeatable, the authors included in their introduction an excellent discussion of a large collection of recent studies supporting the educational benefit of sleep in general and napping in particular.

Although sleep seems to finally be receiving some of the attention it deserves, I am still concerned that as a profession we are failing to give it the appropriate weight at our health maintenance visits. This is particularly true of napping. Understandably, napping doesn’t feel urgent to parents in those turbulent first 4 or 5 months of night wakings and erratic settling. However, as a child approaches the 6-month milestone, napping is a topic ripe for well-considered anticipatory guidance.

When the recurrent cycles of awake-eat-sleep begin to develop into a somewhat predictable pattern and solid food is introduced, it’s time to suggest to parents a strategy that will encourage a napping pattern that will hopefully habituate into toddlerhood and beyond.

It can begin simply as a matter of defining the feeding in the middle of the day as lunch and then programming the period immediately following that meal as a siesta – a segment of the day completely reserved for rest. Many warm-weather countries have been using this strategy for centuries. Try to go to the pharmacy to pick up a prescription at 2 o’clock in the afternoon in rural Spain. It just ain’t gonna happen.

Most adults and children I know seem to be sleepy during this midday postprandial period. It makes more than a little sense to harness this natural drowsiness into creating a napping habit. However, the challenge for many young families is controlling their schedule to create a period of time when nothing else is going on in the child’s environment, leaving sleep as the only option. For some parents this requires the discipline to pause their own lives long enough so that the children realize that they aren’t missing out on something fun. This means no TV, no phone conversations, no visitors. Obviously, it also means not scheduling any appointments during this siesta period. Skilled day care providers have been doing this for years. But the message hasn’t seeped into the general population and sadly I occasionally see mothers with toddlers in the grocery store at 1 in the afternoon.

Once the nap/siesta is firmly welded to lunch, this gives the parent the ability to make minor adjustments that reflect the child’s stamina. If the child seems to be tiring/getting grumpy, serve up lunch a bit early and the restorative nap follows. As the child gets older and his or her stamina improves he or she may not be sleepy but the siesta remains as a quiet time. Some days it may be a nap, some days just a rest for an hour. By counseling parents to define the period after lunch as a siesta you will be helping them avoid that dreaded transition period called “giving up the nap.”

You may already be including this strategy in your anticipatory guidance. It may help to add to your advice the accumulating evidence that napping may play an important role in the child’s development and education.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

Now hot off the press from the “always-guessed-it-was-true-but-now-you-know-it” department comes a multinational study that looked at childhood cardiovascular risk factors and longevity.

Using data collected from individuals in Finland, Australia, and the United States the International Childhood Cardiovascular Cohorts Consortium Outcomes Study investigators sought links between subjects’ body mass index, systolic blood pressure, total cholesterol, blood triglyceride level, and smoking in childhood with cardiovascular disease and outcomes as they aged into adulthood.

The children were initially enrolled in the 1970s and 1980s. The adult evaluations were done in 2015-2019 when the subjects’ average age was 46. Of the 40,000 individuals who originally entered the study, 800 were found to have cardiovascular events of which over 300 had resulted in death. I found these numbers a bit surprising given the relatively young age at which the follow-up data were collected.

What was less surprising is that people with higher than normal values for all five risk factors as children had nearly three times the risk of cardiovascular disease as adults. Researchers found that smoking at a young age was biggest risk factor with body mass index, systolic blood pressure, blood triglycerides, and cholesterol following in descending order. They also found that adults who were obese as children had triple the risk of cardiovascular disease as adults. High blood pressure in childhood doubled the risk.

It will be interesting to see if and how these trends change as the study population ages. It could be that the effect of these childhood risk factors is blunted as the those segments at the highest risk die off and/or risk- associated behaviors adopted in adulthood become more prominent. But, it feels more likely that the childhood risk factors will remain as major contributors.

Is this just another ho-hum-told-you-so study or does it have some special relevance for us as pediatricians? At a minimum these findings should inspire us to stick with our calling to commit ourselves to the health of children. A healthy adult population is clearly our legacy.

Of course the two individual risk factors in childhood that appear to be the most potent in adulthood, obesity and smoking, are also the most frustrating for pediatricians to address. However, the study suggests that we should rejoice in those few successes when we achieve them. Childhood obesity has been a tough nut to crack. On the other hand, the societal change that has made great strides in adult smoking over the last half century should encourage us that our work with the pediatric population will eventually bring rewards.

Smoking and obesity can include components of both patient and parental behavior. Monitoring cholesterol, triglycerides, and blood pressure hinges on our behavior as providers. Although there have been recent recommendations that we be more attentive, we don’t have a strong history when it comes to detecting and addressing high blood pressure in children. This study should serve as an another reminder to take blood pressure more seriously.

I was surprised and somewhat disappointed that I first learned about the results of this study in an email newsletter from the medical school I attended. I would have hoped that a paper like this from a well known peer-reviewed journal with a clear message about the relationship of childhood health and longevity should have been picked up quickly by the lay press. Again, this leaves it to us to promote the message that the health of children is important in and of itself but plays a critical role in the health of adults.
 

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

Now hot off the press from the “always-guessed-it-was-true-but-now-you-know-it” department comes a multinational study that looked at childhood cardiovascular risk factors and longevity.

Using data collected from individuals in Finland, Australia, and the United States the International Childhood Cardiovascular Cohorts Consortium Outcomes Study investigators sought links between subjects’ body mass index, systolic blood pressure, total cholesterol, blood triglyceride level, and smoking in childhood with cardiovascular disease and outcomes as they aged into adulthood.

The children were initially enrolled in the 1970s and 1980s. The adult evaluations were done in 2015-2019 when the subjects’ average age was 46. Of the 40,000 individuals who originally entered the study, 800 were found to have cardiovascular events of which over 300 had resulted in death. I found these numbers a bit surprising given the relatively young age at which the follow-up data were collected.

What was less surprising is that people with higher than normal values for all five risk factors as children had nearly three times the risk of cardiovascular disease as adults. Researchers found that smoking at a young age was biggest risk factor with body mass index, systolic blood pressure, blood triglycerides, and cholesterol following in descending order. They also found that adults who were obese as children had triple the risk of cardiovascular disease as adults. High blood pressure in childhood doubled the risk.

It will be interesting to see if and how these trends change as the study population ages. It could be that the effect of these childhood risk factors is blunted as the those segments at the highest risk die off and/or risk- associated behaviors adopted in adulthood become more prominent. But, it feels more likely that the childhood risk factors will remain as major contributors.

Is this just another ho-hum-told-you-so study or does it have some special relevance for us as pediatricians? At a minimum these findings should inspire us to stick with our calling to commit ourselves to the health of children. A healthy adult population is clearly our legacy.

Of course the two individual risk factors in childhood that appear to be the most potent in adulthood, obesity and smoking, are also the most frustrating for pediatricians to address. However, the study suggests that we should rejoice in those few successes when we achieve them. Childhood obesity has been a tough nut to crack. On the other hand, the societal change that has made great strides in adult smoking over the last half century should encourage us that our work with the pediatric population will eventually bring rewards.

Smoking and obesity can include components of both patient and parental behavior. Monitoring cholesterol, triglycerides, and blood pressure hinges on our behavior as providers. Although there have been recent recommendations that we be more attentive, we don’t have a strong history when it comes to detecting and addressing high blood pressure in children. This study should serve as an another reminder to take blood pressure more seriously.

I was surprised and somewhat disappointed that I first learned about the results of this study in an email newsletter from the medical school I attended. I would have hoped that a paper like this from a well known peer-reviewed journal with a clear message about the relationship of childhood health and longevity should have been picked up quickly by the lay press. Again, this leaves it to us to promote the message that the health of children is important in and of itself but plays a critical role in the health of adults.
 

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

Now hot off the press from the “always-guessed-it-was-true-but-now-you-know-it” department comes a multinational study that looked at childhood cardiovascular risk factors and longevity.

Using data collected from individuals in Finland, Australia, and the United States the International Childhood Cardiovascular Cohorts Consortium Outcomes Study investigators sought links between subjects’ body mass index, systolic blood pressure, total cholesterol, blood triglyceride level, and smoking in childhood with cardiovascular disease and outcomes as they aged into adulthood.

The children were initially enrolled in the 1970s and 1980s. The adult evaluations were done in 2015-2019 when the subjects’ average age was 46. Of the 40,000 individuals who originally entered the study, 800 were found to have cardiovascular events of which over 300 had resulted in death. I found these numbers a bit surprising given the relatively young age at which the follow-up data were collected.

What was less surprising is that people with higher than normal values for all five risk factors as children had nearly three times the risk of cardiovascular disease as adults. Researchers found that smoking at a young age was biggest risk factor with body mass index, systolic blood pressure, blood triglycerides, and cholesterol following in descending order. They also found that adults who were obese as children had triple the risk of cardiovascular disease as adults. High blood pressure in childhood doubled the risk.

It will be interesting to see if and how these trends change as the study population ages. It could be that the effect of these childhood risk factors is blunted as the those segments at the highest risk die off and/or risk- associated behaviors adopted in adulthood become more prominent. But, it feels more likely that the childhood risk factors will remain as major contributors.

Is this just another ho-hum-told-you-so study or does it have some special relevance for us as pediatricians? At a minimum these findings should inspire us to stick with our calling to commit ourselves to the health of children. A healthy adult population is clearly our legacy.

Of course the two individual risk factors in childhood that appear to be the most potent in adulthood, obesity and smoking, are also the most frustrating for pediatricians to address. However, the study suggests that we should rejoice in those few successes when we achieve them. Childhood obesity has been a tough nut to crack. On the other hand, the societal change that has made great strides in adult smoking over the last half century should encourage us that our work with the pediatric population will eventually bring rewards.

Smoking and obesity can include components of both patient and parental behavior. Monitoring cholesterol, triglycerides, and blood pressure hinges on our behavior as providers. Although there have been recent recommendations that we be more attentive, we don’t have a strong history when it comes to detecting and addressing high blood pressure in children. This study should serve as an another reminder to take blood pressure more seriously.

I was surprised and somewhat disappointed that I first learned about the results of this study in an email newsletter from the medical school I attended. I would have hoped that a paper like this from a well known peer-reviewed journal with a clear message about the relationship of childhood health and longevity should have been picked up quickly by the lay press. Again, this leaves it to us to promote the message that the health of children is important in and of itself but plays a critical role in the health of adults.
 

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

Mental illness has been waiting in the wings for years; ignored, ridiculed, minimized, and stigmatized. Those who succumbed to it tried to lend testimonials, but to no avail. Those who were spared its effects remained in disbelief. So, it stayed on the sidelines, growing in intensity and breadth, yet stifled by the masses, until 2 years ago.

In March 2020, when COVID-19 became a pandemic, the importance of mental health finally became undeniable. As the pandemic’s effects progressed and wreaked havoc on our nation, our mental illness rates simultaneously surged. This surge paralleled that of the COVID-19 pandemic’s and in fact, contributed to a secondary crisis, allowing mental health to finally be addressed and gain center stage status.

But “mental health” is not easily defined, as it takes on many forms and is expressed in a variety of ways and via a myriad of symptoms. It does not discriminate by gender, race, age, socioeconomic status, educational level, profession, religion, or geography. At times, mental health status is consistent but at other times it can fluctuate in intensity, duration, and expression. It can be difficult to manage, yet there are various treatment modalities that can be implemented to lessen the impact of mental illness. Stressful events seem to potentiate its manifestation and yet, there are times it seems to appear spontaneously, much as an uninvited guest.

Mental health has a strong synergistic relationship with physical health, as they are very interdependent and allow us to function at our best only when they are both operating optimally. It should come as no surprise then, that the COVID-19 pandemic contributed to the exponential surge of mental illnesses. Capitalizing on its nondiscriminatory nature, mental illness impacted a large segment of the population – both those suffering from COVID-19 as well as those treating them.

As the nation starts to heal from the immediate and lingering physical and emotional consequences of the COVID-19 pandemic, President Biden has chosen to address and try to meet the needs of the health care heroes, the healers. The signing of H.R. 1667, the Dr. Lorna Breen Health Care Provider Protection Act into law on March 18, 2022, showed dedication to the health care community that has given tirelessly to our nation during the COVID-19 pandemic, and is itself recuperating from that effort.

Taking a top-down approach is essential to assuring the health of the nation. If our healers are not healthy, physically and mentally, they will not be able treat those whom they are dedicated to helping. Openly discussing and acknowledging the mental health problems of health care workers as a community makes it okay to not be okay. It normalizes the need for health care workers to prioritize their own mental health. It can also start to ease the fear of professional backlash or repercussions for practicing self-care.

I, for one, am very grateful for the prioritizing and promoting of the importance of mental health and wellness amongst health care workers. This helps to reduce the stigma of mental illness, helps us understand its impact, and allows us to formulate strategies and solutions to address its effects. The time has come.

Dr. Jarkon is a psychiatrist and director of the Center for Behavioral Health at the New York Institute of Technology College of Osteopathic Medicine in Old Westbury, N.Y.

Mental illness has been waiting in the wings for years; ignored, ridiculed, minimized, and stigmatized. Those who succumbed to it tried to lend testimonials, but to no avail. Those who were spared its effects remained in disbelief. So, it stayed on the sidelines, growing in intensity and breadth, yet stifled by the masses, until 2 years ago.

In March 2020, when COVID-19 became a pandemic, the importance of mental health finally became undeniable. As the pandemic’s effects progressed and wreaked havoc on our nation, our mental illness rates simultaneously surged. This surge paralleled that of the COVID-19 pandemic’s and in fact, contributed to a secondary crisis, allowing mental health to finally be addressed and gain center stage status.

But “mental health” is not easily defined, as it takes on many forms and is expressed in a variety of ways and via a myriad of symptoms. It does not discriminate by gender, race, age, socioeconomic status, educational level, profession, religion, or geography. At times, mental health status is consistent but at other times it can fluctuate in intensity, duration, and expression. It can be difficult to manage, yet there are various treatment modalities that can be implemented to lessen the impact of mental illness. Stressful events seem to potentiate its manifestation and yet, there are times it seems to appear spontaneously, much as an uninvited guest.

Mental health has a strong synergistic relationship with physical health, as they are very interdependent and allow us to function at our best only when they are both operating optimally. It should come as no surprise then, that the COVID-19 pandemic contributed to the exponential surge of mental illnesses. Capitalizing on its nondiscriminatory nature, mental illness impacted a large segment of the population – both those suffering from COVID-19 as well as those treating them.

As the nation starts to heal from the immediate and lingering physical and emotional consequences of the COVID-19 pandemic, President Biden has chosen to address and try to meet the needs of the health care heroes, the healers. The signing of H.R. 1667, the Dr. Lorna Breen Health Care Provider Protection Act into law on March 18, 2022, showed dedication to the health care community that has given tirelessly to our nation during the COVID-19 pandemic, and is itself recuperating from that effort.

Taking a top-down approach is essential to assuring the health of the nation. If our healers are not healthy, physically and mentally, they will not be able treat those whom they are dedicated to helping. Openly discussing and acknowledging the mental health problems of health care workers as a community makes it okay to not be okay. It normalizes the need for health care workers to prioritize their own mental health. It can also start to ease the fear of professional backlash or repercussions for practicing self-care.

I, for one, am very grateful for the prioritizing and promoting of the importance of mental health and wellness amongst health care workers. This helps to reduce the stigma of mental illness, helps us understand its impact, and allows us to formulate strategies and solutions to address its effects. The time has come.

Dr. Jarkon is a psychiatrist and director of the Center for Behavioral Health at the New York Institute of Technology College of Osteopathic Medicine in Old Westbury, N.Y.

Mental illness has been waiting in the wings for years; ignored, ridiculed, minimized, and stigmatized. Those who succumbed to it tried to lend testimonials, but to no avail. Those who were spared its effects remained in disbelief. So, it stayed on the sidelines, growing in intensity and breadth, yet stifled by the masses, until 2 years ago.

In March 2020, when COVID-19 became a pandemic, the importance of mental health finally became undeniable. As the pandemic’s effects progressed and wreaked havoc on our nation, our mental illness rates simultaneously surged. This surge paralleled that of the COVID-19 pandemic’s and in fact, contributed to a secondary crisis, allowing mental health to finally be addressed and gain center stage status.

But “mental health” is not easily defined, as it takes on many forms and is expressed in a variety of ways and via a myriad of symptoms. It does not discriminate by gender, race, age, socioeconomic status, educational level, profession, religion, or geography. At times, mental health status is consistent but at other times it can fluctuate in intensity, duration, and expression. It can be difficult to manage, yet there are various treatment modalities that can be implemented to lessen the impact of mental illness. Stressful events seem to potentiate its manifestation and yet, there are times it seems to appear spontaneously, much as an uninvited guest.

Mental health has a strong synergistic relationship with physical health, as they are very interdependent and allow us to function at our best only when they are both operating optimally. It should come as no surprise then, that the COVID-19 pandemic contributed to the exponential surge of mental illnesses. Capitalizing on its nondiscriminatory nature, mental illness impacted a large segment of the population – both those suffering from COVID-19 as well as those treating them.

As the nation starts to heal from the immediate and lingering physical and emotional consequences of the COVID-19 pandemic, President Biden has chosen to address and try to meet the needs of the health care heroes, the healers. The signing of H.R. 1667, the Dr. Lorna Breen Health Care Provider Protection Act into law on March 18, 2022, showed dedication to the health care community that has given tirelessly to our nation during the COVID-19 pandemic, and is itself recuperating from that effort.

Taking a top-down approach is essential to assuring the health of the nation. If our healers are not healthy, physically and mentally, they will not be able treat those whom they are dedicated to helping. Openly discussing and acknowledging the mental health problems of health care workers as a community makes it okay to not be okay. It normalizes the need for health care workers to prioritize their own mental health. It can also start to ease the fear of professional backlash or repercussions for practicing self-care.

I, for one, am very grateful for the prioritizing and promoting of the importance of mental health and wellness amongst health care workers. This helps to reduce the stigma of mental illness, helps us understand its impact, and allows us to formulate strategies and solutions to address its effects. The time has come.

Dr. Jarkon is a psychiatrist and director of the Center for Behavioral Health at the New York Institute of Technology College of Osteopathic Medicine in Old Westbury, N.Y.

I suspect that you have heard or read about the recent study in the Journal of Neuroscience that claims to have discovered evidence that as children become teenagers, their brains begin to tune out their mother’s voices. The story appeared in at least 10 Internet news sources including the American Academy of Pediatrics’ daily briefing.

Based on functional MRI studies by a group at Stanford (Calif.) University, the researchers found that while in general, teenagers became more attentive to all voices as they reached puberty, novel voices were favored over the maternal voices that had flooded their environment as younger children. Of course none of this comes as a surprise to anyone who has parented a teenager or spent any time trying to communicate with adolescents. Although we all must be a bit careful not to put too much stock in functional MRI studies, these findings do suggest a physiologic basis for the peer pressure that becomes one of the hallmarks of adolescence. I wouldn’t be surprised if some clever entrepreneur has already begun using MRI to search for just the right tonal qualities that will make the perfect Internet influencer.

But, will these MRI studies help parents who have already thrown up their arms and admitted defeat mumbling, “He’s stopped listening to me?” The more observant parents already realized long ago that their words were often the least effective tools in their tool kit when it comes to modifying behavior.

Just listen in any neighborhood playground or grocery store to how often you hear a parent trying to get a toddler or young child to correct a misbehavior using threats or promises that you and everyone else within earshot knows will never be followed by any consequence. How often do you see a parent modeling behaviors that they expect their children to avoid?

Some more “enlightened” parents will avoid threats and instead attempt to engage in a dialogue with their misbehaving child hoping that a rational discussion with a sleep-deprived toddler in full tantrum mode can convince the youngster to self-correct.

I’m sure you learned and may have even used the playground retort “sticks and stones may break my bones but words will never hurt me.” Of course more untrue words were never spoken. Words can hurt and they can scar. But words and threats can also be hollow and will fall on ears deafened by months and years during which there were no consequences. It is certainly nice to know that there is some physiologic correlation to what we all suspected. The good news is that teenagers are still listening to us, although they are increasingly more interested in what their peers and the rest of the world has to say.

What the study fails to point out is that while teenagers may still be listening to us their behavior is molded not so much by what we say but how we as parents and adults behave. Have we parented in a way in which our words are followed up with appropriate consequences? And, more importantly, have we modeled behavior that matches our words? We need to help parents realize that words can be important but parenting by example is the gold standard.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

I suspect that you have heard or read about the recent study in the Journal of Neuroscience that claims to have discovered evidence that as children become teenagers, their brains begin to tune out their mother’s voices. The story appeared in at least 10 Internet news sources including the American Academy of Pediatrics’ daily briefing.

Based on functional MRI studies by a group at Stanford (Calif.) University, the researchers found that while in general, teenagers became more attentive to all voices as they reached puberty, novel voices were favored over the maternal voices that had flooded their environment as younger children. Of course none of this comes as a surprise to anyone who has parented a teenager or spent any time trying to communicate with adolescents. Although we all must be a bit careful not to put too much stock in functional MRI studies, these findings do suggest a physiologic basis for the peer pressure that becomes one of the hallmarks of adolescence. I wouldn’t be surprised if some clever entrepreneur has already begun using MRI to search for just the right tonal qualities that will make the perfect Internet influencer.

But, will these MRI studies help parents who have already thrown up their arms and admitted defeat mumbling, “He’s stopped listening to me?” The more observant parents already realized long ago that their words were often the least effective tools in their tool kit when it comes to modifying behavior.

Just listen in any neighborhood playground or grocery store to how often you hear a parent trying to get a toddler or young child to correct a misbehavior using threats or promises that you and everyone else within earshot knows will never be followed by any consequence. How often do you see a parent modeling behaviors that they expect their children to avoid?

Some more “enlightened” parents will avoid threats and instead attempt to engage in a dialogue with their misbehaving child hoping that a rational discussion with a sleep-deprived toddler in full tantrum mode can convince the youngster to self-correct.

I’m sure you learned and may have even used the playground retort “sticks and stones may break my bones but words will never hurt me.” Of course more untrue words were never spoken. Words can hurt and they can scar. But words and threats can also be hollow and will fall on ears deafened by months and years during which there were no consequences. It is certainly nice to know that there is some physiologic correlation to what we all suspected. The good news is that teenagers are still listening to us, although they are increasingly more interested in what their peers and the rest of the world has to say.

What the study fails to point out is that while teenagers may still be listening to us their behavior is molded not so much by what we say but how we as parents and adults behave. Have we parented in a way in which our words are followed up with appropriate consequences? And, more importantly, have we modeled behavior that matches our words? We need to help parents realize that words can be important but parenting by example is the gold standard.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

I suspect that you have heard or read about the recent study in the Journal of Neuroscience that claims to have discovered evidence that as children become teenagers, their brains begin to tune out their mother’s voices. The story appeared in at least 10 Internet news sources including the American Academy of Pediatrics’ daily briefing.

Based on functional MRI studies by a group at Stanford (Calif.) University, the researchers found that while in general, teenagers became more attentive to all voices as they reached puberty, novel voices were favored over the maternal voices that had flooded their environment as younger children. Of course none of this comes as a surprise to anyone who has parented a teenager or spent any time trying to communicate with adolescents. Although we all must be a bit careful not to put too much stock in functional MRI studies, these findings do suggest a physiologic basis for the peer pressure that becomes one of the hallmarks of adolescence. I wouldn’t be surprised if some clever entrepreneur has already begun using MRI to search for just the right tonal qualities that will make the perfect Internet influencer.

But, will these MRI studies help parents who have already thrown up their arms and admitted defeat mumbling, “He’s stopped listening to me?” The more observant parents already realized long ago that their words were often the least effective tools in their tool kit when it comes to modifying behavior.

Just listen in any neighborhood playground or grocery store to how often you hear a parent trying to get a toddler or young child to correct a misbehavior using threats or promises that you and everyone else within earshot knows will never be followed by any consequence. How often do you see a parent modeling behaviors that they expect their children to avoid?

Some more “enlightened” parents will avoid threats and instead attempt to engage in a dialogue with their misbehaving child hoping that a rational discussion with a sleep-deprived toddler in full tantrum mode can convince the youngster to self-correct.

I’m sure you learned and may have even used the playground retort “sticks and stones may break my bones but words will never hurt me.” Of course more untrue words were never spoken. Words can hurt and they can scar. But words and threats can also be hollow and will fall on ears deafened by months and years during which there were no consequences. It is certainly nice to know that there is some physiologic correlation to what we all suspected. The good news is that teenagers are still listening to us, although they are increasingly more interested in what their peers and the rest of the world has to say.

What the study fails to point out is that while teenagers may still be listening to us their behavior is molded not so much by what we say but how we as parents and adults behave. Have we parented in a way in which our words are followed up with appropriate consequences? And, more importantly, have we modeled behavior that matches our words? We need to help parents realize that words can be important but parenting by example is the gold standard.

Dr. Wilkoff practiced primary care pediatrics in Brunswick, Maine, for nearly 40 years. He has authored several books on behavioral pediatrics, including “How to Say No to Your Toddler.” Other than a Littman stethoscope he accepted as a first-year medical student in 1966, Dr. Wilkoff reports having nothing to disclose. Email him at pdnews@mdedge.com.

Having witnessed the devastating impact of stigma on patients with mental illness throughout my psychiatric career, I am fed up and disgusted with this malevolent scourge.

I regard the stigma that engulfs neuropsychiatric disorders as a malignancy that mutilates patients’ souls and hastens their mortality.

Stigma is hate speech

How would you feel if you had a serious medical illness, a disabling brain disorder such as schizophrenia, depression, or anxiety, and people refer to you with pejorative and insulting terms such as crazy, deranged, lunatic, unhinged, nutty, insane, wacky, berserk, cuckoo, bonkers, flaky, screwball, or unglued? This is hate speech generated by stigma against people with mental illness. Individuals with heart disease, cancer, or diabetes never get called such disgraceful and stigmatizing terms that shame, stain, besmirch, and scar them, which happens daily to persons with psychiatric brain disorders.

The damage and harm of the discriminatory stigma on our patients is multifaceted. It is painful, detrimental, pernicious, and deleterious. It is corrosive to their spirits, crippling to their self-image, and subversive to their self-confidence. Hate speech is not simply words, but a menacing weapon that assaults the core humanity of medically ill psychiatric patients.

Although hate speech is punishable by law, there are rarely any legal actions against those who hurl hate speech at psychiatric patients every day. Society has institutionalized the stigma of mental illness and takes it in stride instead of recognizing it as an illegal, harmful act.

Long before the stresses of the COVID-19 pandemic, 43% of the population had been shown to experience a diagnosable psychiatric disorder over the course of their life.¹ Thus, tens of millions of people are burdened by stigma and the hate speech associated with it. This is directly related to massive ignorance about mental illness being the result of a neurobiological condition due to either genetic or intrauterine adverse events that disrupt brain development. Delusions and hallucinations are symptoms of a malfunctioning brain, depression is not a sign of personal weakness, anxiety is the most prevalent mental disorder in the world, and obsessive-compulsive disorder (OCD) is not odd behavior but the result of dysfunction of neural circuits. Correcting public misperceptions about psychiatric brain disorders can mitigate stigma, but it has yet to happen.

Stigma is a hate crime

Stigma can accelerate physical death and premature mortality. Many studies have confirmed that persons with schizophrenia do not receive basic primary care treatments for the life-shortening medical conditions that often afflict them, such as diabetes, dyslipidemia, and hypertension.² Stigma is responsible for a significant disparity of medical^3-5 and intensive care⁶ among individuals with mental illness compared to the general population. It’s no wonder most psychiatric disorders are associated with accelerated mortality.⁷ A recent study during the pandemic by Balasuriya et al⁸ reported that patients with depression had poor access to care. Stigma interferes with or delays necessary medical care, leading to clinical deterioration and unnecessary, preventable death. Stigma shortens life and is a hate crime.

Continue to: The extremely high suicide rates...

The extremely high suicide rates among individuals with serious mental illness, who live under the oppressiveness of stigma, is another example of how stigma is a hate crime that can cause patients with psychiatric disorders to give up and end their lives. Zaheer et al⁹ found that young patients with schizophrenia had an astronomical suicide rate compared to the general population (1 in 52 in individuals with schizophrenia, compared to 12 in 100,000 in the general population, roughly a 200-fold increase!). This is clearly a consequence of stigma and discrimination,¹⁰ which leads to demoralization, shame, loneliness, distress, and hopelessness. Stigma can be fatal, and that makes it a hate crime.

Stigma also limits vocational opportunities for individuals with mental illness. They are either not hired, or quickly fired. Even highly educated professionals such as physicians, nurses, lawyers, or teachers can lose their jobs if they divulge a history of a psychiatric disorder or alcohol or substance abuse, regardless of whether they are receiving treatment and are medically in remission. Even highly qualified politicians have been deemed “ineligible” for higher office if they disclose a history of psychiatric treatment. Stigma is loaded with outrageous discrimination that deprives our patients of “the pursuit of happiness,” a fundamental constitutional right.

Stigma surrounding the mental health professions

Stigma also engulfs mental health professionals, simply because they deal with psychiatric patients every day. In a classic article titled “The Enigma of Stigma,”¹¹ Dr. Paul Fink, past president of the American Psychiatric Association (1988-1989), described how psychiatrists are perceived as “different” from other physicians by the public and by the media. He said psychiatrists are tarred by the same brush as their patients as “undesirables” in society. And movies such as Psycho and One Flew Over the Cuckoo’s Nest reinforce the stigma against both psychiatric patients and the psychiatrists and nurses who treat them. The health care system that carves out “behavioral health” from the umbrella of “medical care” further accentuates the stigma by portraying the “separateness” of psychiatry, a genuine medical specialty, from its fellow medical disciplines. This becomes fodder for the antipsychiatry movement at every turn and can even lead to questioning the existence of mental illness, as Thomas Szasz¹² did by declaring that mental illness is a myth and describing psychiatry as “the science of lies.” No other medical specialty endures abuse and insults like psychiatry, and that’s a direct result of stigma.

Extinguishing stigma is a societal imperative

So what can be done to squelch stigma and defeat it once and for all, so that psychiatric patients can be treated with dignity and compassion, like people with cancer, heart attacks, diabetes, or brain tumors? The pandemic, terrible as it has been for the entire world, did have the silver lining of raising awareness about the ubiquity of psychiatric symptoms, such as anxiety and depression, across all ages, genders, educational and religious backgrounds, and socioeconomic classes. But there should also be a robust legal battle against the damaging effects of stigma. There are laws to sanction and penalize hate speech and hate crimes that must be implemented when stigma is documented. There are also parity laws, but they have no teeth and have not ameliorated the insurance discrepancies and economic burden of psychiatric disorders. A bold step would be to reclassify serious psychiatric brain disorders (schizophrenia, bipolar disorder, major depressive disorder, OCD, attention-deficit/hyperactivity disorder, generalized anxiety disorder/panic attacks, and borderline personality disorder) as neurologic disorders, which would automatically give patients with these disorders broad access to medical care, which happened when autism was reclassified as a neurologic disorder. Finally, a much more intensive public education must be disseminated about the neurobiological etiologies, brain structure, and function in psychiatric disorders, and the psychiatric symptoms associated with all neurologic disorders. Regrettably, empathy can be difficult to teach.

Stigma is hate speech and a hate crime. It must be permanently eliminated by effective laws and by erasing the widespread ignorance about the medical and neurologic roots of mental disorders, and by emphasizing the fact that they are as treatable as other general medical conditions.

Having witnessed the devastating impact of stigma on patients with mental illness throughout my psychiatric career, I am fed up and disgusted with this malevolent scourge.

I regard the stigma that engulfs neuropsychiatric disorders as a malignancy that mutilates patients’ souls and hastens their mortality.

Stigma is hate speech

How would you feel if you had a serious medical illness, a disabling brain disorder such as schizophrenia, depression, or anxiety, and people refer to you with pejorative and insulting terms such as crazy, deranged, lunatic, unhinged, nutty, insane, wacky, berserk, cuckoo, bonkers, flaky, screwball, or unglued? This is hate speech generated by stigma against people with mental illness. Individuals with heart disease, cancer, or diabetes never get called such disgraceful and stigmatizing terms that shame, stain, besmirch, and scar them, which happens daily to persons with psychiatric brain disorders.

The damage and harm of the discriminatory stigma on our patients is multifaceted. It is painful, detrimental, pernicious, and deleterious. It is corrosive to their spirits, crippling to their self-image, and subversive to their self-confidence. Hate speech is not simply words, but a menacing weapon that assaults the core humanity of medically ill psychiatric patients.

Although hate speech is punishable by law, there are rarely any legal actions against those who hurl hate speech at psychiatric patients every day. Society has institutionalized the stigma of mental illness and takes it in stride instead of recognizing it as an illegal, harmful act.

Long before the stresses of the COVID-19 pandemic, 43% of the population had been shown to experience a diagnosable psychiatric disorder over the course of their life.¹ Thus, tens of millions of people are burdened by stigma and the hate speech associated with it. This is directly related to massive ignorance about mental illness being the result of a neurobiological condition due to either genetic or intrauterine adverse events that disrupt brain development. Delusions and hallucinations are symptoms of a malfunctioning brain, depression is not a sign of personal weakness, anxiety is the most prevalent mental disorder in the world, and obsessive-compulsive disorder (OCD) is not odd behavior but the result of dysfunction of neural circuits. Correcting public misperceptions about psychiatric brain disorders can mitigate stigma, but it has yet to happen.

Stigma is a hate crime

Stigma can accelerate physical death and premature mortality. Many studies have confirmed that persons with schizophrenia do not receive basic primary care treatments for the life-shortening medical conditions that often afflict them, such as diabetes, dyslipidemia, and hypertension.² Stigma is responsible for a significant disparity of medical^3-5 and intensive care⁶ among individuals with mental illness compared to the general population. It’s no wonder most psychiatric disorders are associated with accelerated mortality.⁷ A recent study during the pandemic by Balasuriya et al⁸ reported that patients with depression had poor access to care. Stigma interferes with or delays necessary medical care, leading to clinical deterioration and unnecessary, preventable death. Stigma shortens life and is a hate crime.

Continue to: The extremely high suicide rates...

The extremely high suicide rates among individuals with serious mental illness, who live under the oppressiveness of stigma, is another example of how stigma is a hate crime that can cause patients with psychiatric disorders to give up and end their lives. Zaheer et al⁹ found that young patients with schizophrenia had an astronomical suicide rate compared to the general population (1 in 52 in individuals with schizophrenia, compared to 12 in 100,000 in the general population, roughly a 200-fold increase!). This is clearly a consequence of stigma and discrimination,¹⁰ which leads to demoralization, shame, loneliness, distress, and hopelessness. Stigma can be fatal, and that makes it a hate crime.

Stigma also limits vocational opportunities for individuals with mental illness. They are either not hired, or quickly fired. Even highly educated professionals such as physicians, nurses, lawyers, or teachers can lose their jobs if they divulge a history of a psychiatric disorder or alcohol or substance abuse, regardless of whether they are receiving treatment and are medically in remission. Even highly qualified politicians have been deemed “ineligible” for higher office if they disclose a history of psychiatric treatment. Stigma is loaded with outrageous discrimination that deprives our patients of “the pursuit of happiness,” a fundamental constitutional right.

Stigma surrounding the mental health professions

Stigma also engulfs mental health professionals, simply because they deal with psychiatric patients every day. In a classic article titled “The Enigma of Stigma,”¹¹ Dr. Paul Fink, past president of the American Psychiatric Association (1988-1989), described how psychiatrists are perceived as “different” from other physicians by the public and by the media. He said psychiatrists are tarred by the same brush as their patients as “undesirables” in society. And movies such as Psycho and One Flew Over the Cuckoo’s Nest reinforce the stigma against both psychiatric patients and the psychiatrists and nurses who treat them. The health care system that carves out “behavioral health” from the umbrella of “medical care” further accentuates the stigma by portraying the “separateness” of psychiatry, a genuine medical specialty, from its fellow medical disciplines. This becomes fodder for the antipsychiatry movement at every turn and can even lead to questioning the existence of mental illness, as Thomas Szasz¹² did by declaring that mental illness is a myth and describing psychiatry as “the science of lies.” No other medical specialty endures abuse and insults like psychiatry, and that’s a direct result of stigma.

Extinguishing stigma is a societal imperative

So what can be done to squelch stigma and defeat it once and for all, so that psychiatric patients can be treated with dignity and compassion, like people with cancer, heart attacks, diabetes, or brain tumors? The pandemic, terrible as it has been for the entire world, did have the silver lining of raising awareness about the ubiquity of psychiatric symptoms, such as anxiety and depression, across all ages, genders, educational and religious backgrounds, and socioeconomic classes. But there should also be a robust legal battle against the damaging effects of stigma. There are laws to sanction and penalize hate speech and hate crimes that must be implemented when stigma is documented. There are also parity laws, but they have no teeth and have not ameliorated the insurance discrepancies and economic burden of psychiatric disorders. A bold step would be to reclassify serious psychiatric brain disorders (schizophrenia, bipolar disorder, major depressive disorder, OCD, attention-deficit/hyperactivity disorder, generalized anxiety disorder/panic attacks, and borderline personality disorder) as neurologic disorders, which would automatically give patients with these disorders broad access to medical care, which happened when autism was reclassified as a neurologic disorder. Finally, a much more intensive public education must be disseminated about the neurobiological etiologies, brain structure, and function in psychiatric disorders, and the psychiatric symptoms associated with all neurologic disorders. Regrettably, empathy can be difficult to teach.

Stigma is hate speech and a hate crime. It must be permanently eliminated by effective laws and by erasing the widespread ignorance about the medical and neurologic roots of mental disorders, and by emphasizing the fact that they are as treatable as other general medical conditions.

Having witnessed the devastating impact of stigma on patients with mental illness throughout my psychiatric career, I am fed up and disgusted with this malevolent scourge.

I regard the stigma that engulfs neuropsychiatric disorders as a malignancy that mutilates patients’ souls and hastens their mortality.

Stigma is hate speech

How would you feel if you had a serious medical illness, a disabling brain disorder such as schizophrenia, depression, or anxiety, and people refer to you with pejorative and insulting terms such as crazy, deranged, lunatic, unhinged, nutty, insane, wacky, berserk, cuckoo, bonkers, flaky, screwball, or unglued? This is hate speech generated by stigma against people with mental illness. Individuals with heart disease, cancer, or diabetes never get called such disgraceful and stigmatizing terms that shame, stain, besmirch, and scar them, which happens daily to persons with psychiatric brain disorders.

The damage and harm of the discriminatory stigma on our patients is multifaceted. It is painful, detrimental, pernicious, and deleterious. It is corrosive to their spirits, crippling to their self-image, and subversive to their self-confidence. Hate speech is not simply words, but a menacing weapon that assaults the core humanity of medically ill psychiatric patients.

Although hate speech is punishable by law, there are rarely any legal actions against those who hurl hate speech at psychiatric patients every day. Society has institutionalized the stigma of mental illness and takes it in stride instead of recognizing it as an illegal, harmful act.

Long before the stresses of the COVID-19 pandemic, 43% of the population had been shown to experience a diagnosable psychiatric disorder over the course of their life.¹ Thus, tens of millions of people are burdened by stigma and the hate speech associated with it. This is directly related to massive ignorance about mental illness being the result of a neurobiological condition due to either genetic or intrauterine adverse events that disrupt brain development. Delusions and hallucinations are symptoms of a malfunctioning brain, depression is not a sign of personal weakness, anxiety is the most prevalent mental disorder in the world, and obsessive-compulsive disorder (OCD) is not odd behavior but the result of dysfunction of neural circuits. Correcting public misperceptions about psychiatric brain disorders can mitigate stigma, but it has yet to happen.

Stigma is a hate crime

Stigma can accelerate physical death and premature mortality. Many studies have confirmed that persons with schizophrenia do not receive basic primary care treatments for the life-shortening medical conditions that often afflict them, such as diabetes, dyslipidemia, and hypertension.² Stigma is responsible for a significant disparity of medical^3-5 and intensive care⁶ among individuals with mental illness compared to the general population. It’s no wonder most psychiatric disorders are associated with accelerated mortality.⁷ A recent study during the pandemic by Balasuriya et al⁸ reported that patients with depression had poor access to care. Stigma interferes with or delays necessary medical care, leading to clinical deterioration and unnecessary, preventable death. Stigma shortens life and is a hate crime.

Continue to: The extremely high suicide rates...

The extremely high suicide rates among individuals with serious mental illness, who live under the oppressiveness of stigma, is another example of how stigma is a hate crime that can cause patients with psychiatric disorders to give up and end their lives. Zaheer et al⁹ found that young patients with schizophrenia had an astronomical suicide rate compared to the general population (1 in 52 in individuals with schizophrenia, compared to 12 in 100,000 in the general population, roughly a 200-fold increase!). This is clearly a consequence of stigma and discrimination,¹⁰ which leads to demoralization, shame, loneliness, distress, and hopelessness. Stigma can be fatal, and that makes it a hate crime.

Stigma also limits vocational opportunities for individuals with mental illness. They are either not hired, or quickly fired. Even highly educated professionals such as physicians, nurses, lawyers, or teachers can lose their jobs if they divulge a history of a psychiatric disorder or alcohol or substance abuse, regardless of whether they are receiving treatment and are medically in remission. Even highly qualified politicians have been deemed “ineligible” for higher office if they disclose a history of psychiatric treatment. Stigma is loaded with outrageous discrimination that deprives our patients of “the pursuit of happiness,” a fundamental constitutional right.

Stigma surrounding the mental health professions

Stigma also engulfs mental health professionals, simply because they deal with psychiatric patients every day. In a classic article titled “The Enigma of Stigma,”¹¹ Dr. Paul Fink, past president of the American Psychiatric Association (1988-1989), described how psychiatrists are perceived as “different” from other physicians by the public and by the media. He said psychiatrists are tarred by the same brush as their patients as “undesirables” in society. And movies such as Psycho and One Flew Over the Cuckoo’s Nest reinforce the stigma against both psychiatric patients and the psychiatrists and nurses who treat them. The health care system that carves out “behavioral health” from the umbrella of “medical care” further accentuates the stigma by portraying the “separateness” of psychiatry, a genuine medical specialty, from its fellow medical disciplines. This becomes fodder for the antipsychiatry movement at every turn and can even lead to questioning the existence of mental illness, as Thomas Szasz¹² did by declaring that mental illness is a myth and describing psychiatry as “the science of lies.” No other medical specialty endures abuse and insults like psychiatry, and that’s a direct result of stigma.

Extinguishing stigma is a societal imperative

So what can be done to squelch stigma and defeat it once and for all, so that psychiatric patients can be treated with dignity and compassion, like people with cancer, heart attacks, diabetes, or brain tumors? The pandemic, terrible as it has been for the entire world, did have the silver lining of raising awareness about the ubiquity of psychiatric symptoms, such as anxiety and depression, across all ages, genders, educational and religious backgrounds, and socioeconomic classes. But there should also be a robust legal battle against the damaging effects of stigma. There are laws to sanction and penalize hate speech and hate crimes that must be implemented when stigma is documented. There are also parity laws, but they have no teeth and have not ameliorated the insurance discrepancies and economic burden of psychiatric disorders. A bold step would be to reclassify serious psychiatric brain disorders (schizophrenia, bipolar disorder, major depressive disorder, OCD, attention-deficit/hyperactivity disorder, generalized anxiety disorder/panic attacks, and borderline personality disorder) as neurologic disorders, which would automatically give patients with these disorders broad access to medical care, which happened when autism was reclassified as a neurologic disorder. Finally, a much more intensive public education must be disseminated about the neurobiological etiologies, brain structure, and function in psychiatric disorders, and the psychiatric symptoms associated with all neurologic disorders. Regrettably, empathy can be difficult to teach.

Stigma is hate speech and a hate crime. It must be permanently eliminated by effective laws and by erasing the widespread ignorance about the medical and neurologic roots of mental disorders, and by emphasizing the fact that they are as treatable as other general medical conditions.

Here we go again, and again, and again.

There just aren’t enough tears, and before the bodies of 19 small children are identified, the political noise starts up. Mass shootings are a part of the American landscape, but when they happen at schools, we all feel a distinct sense of violation and gaping grief. Those children are so innocent, so deserving of a right to live their lives, hold their place with their families, create their own legacies, and die of natural causes at a ripe old age. And those children could have been our children. There was nothing special about them; they were just sent to school that day like every child who is sent to school every day.

Here is how the politics goes: The Republicans will blame the Democrats and the Democrats will blame the Republicans. Is Rachel Maddow at fault, or is it Tucker Carlson? Social media accounts blamed both of them for the racially motivated mass murder in a Buffalo grocery store on May 14.

Mass murders were previously defined as a shooting where four or more victims are killed, excluding the shooter, in a public place that is not related to the commission of another crime. In 2012, the definition was changed to include events with three victims. This definition excludes gang violence and the murder of family members.

When it comes to explaining mass murder, the camps divide: They are the result of some combination of mental illness, easy access to firearms, and terrorism and hate. For psychiatry, there is a unique place in the argument – half of all mass shooters have exhibited signs or symptoms of psychiatric illness, and for those who want to deflect the issue away from issues related to the regulation of firearms, it becomes easy to blame “mental illness,” as though that explains it all. Either the gunman “snapped” in such a way that no one could have predicted, or the mental health system is at fault for not preventing it.

There are many ways to be emotionally disturbed; mental illness is only one of them, and there is no psychiatric diagnosis that includes the symptom of shooting strangers, or shooting children. The vast majority of people, including nearly all psychiatrists, will never know someone who perpetrates a mass shooting. 

Can mental illness give us any insight into these senseless killings? Sometimes, but rarely. Take John Hinckley Jr., who shot President Ronald Reagan as a means to impress actress Jodie Foster. Sometimes these killings are motivated by delusional beliefs. But the planning and preparation that goes into most mass shootings involves a degree of organization and forethought that we don’t typically see in those with severe psychotic disorders.

The other psychological explanation that satisfies some of a nonmedical population is that these killers “just snap.” This, too, is a term that is not included in our diagnostic vocabulary, but it remains a way for some to explain that which can’t be explained. If mental illness, however, is the cause of mass murders, then more stringent gun control is unnecessary. Every state already has a mechanism to prevent those with criminal and specified psychiatric histories from buying legal firearms, and it may be inevitable that these screens are not perfect. 

The next line of political thinking moves to the psychiatric “if only.” If only there were more state hospital beds and if only it were easier to compel people with psychiatric disorders to get treatment against their will, then we could eliminate these crimes. The Virginia tech shooter was mandated to get outpatient psychiatric treatment after a brief hospitalization, yet he never went and there was no mechanism in place to track him.

In cases where a person with a psychotic illness has a history of repeated violent episodes after stopping medications, it does make sense to mandate treatment, not because they are likely to shoot strangers, but because some people do become violent when they are ill and mental illness is believed to play a role in 10% of murders.

Mass murders remain rare, and while advocates for legislation that would make it easier to mandate involuntary care have cited violence prevention as a reason, it is hard to imagine that we would force people to get care because they “might” commit such a crime – unless there was convincing evidence that someone was at risk of committing such a heinous act.

For those who oppose stronger gun control laws, the “what if” may circulate around the need for even more firearms. What if teachers carried guns? What if schools were more heavily policed? What if the criminals were made to be afraid?

We are left with the fact that other countries do not see these numbers of mass shooting events, yet mental illness is ubiquitous. While the presence of psychiatric disorders does little to explain school shootings, we still have no understanding of what motivated the Sandy Hook killer, and it remains to be seen what we will come to understand about the gunman in Uvalde, Texas.

Mental illness is not unique to the United States; however, the number of available firearms is. In a country of 323 million people (including children and people who live in institutions where they have no access to firearms), there are estimated to be over 400 million guns in the United States, 98% of which are owned by civilians. 

Hate crimes and terrorism are another explanation for mass murders. In these instances, the gunman makes his motive obvious: There are social media announcements, or the site of the shooting is a synagogue, a mosque, or a location where the victims are of a specific race or religion. But hate may come out of a psychotic illness, and easy access to firearms allows for these crimes to continue. 

Firearms are now the No. 1 cause of mortality in children. Very few of these deaths are the result of mass murders. Many more are from accidental deaths, targeted crime, or suicide. Still, school shootings rip at our hearts. Neither the victims nor their grieving families have any role in the act, and suffering leaves its mark on families, communities, and all of us.
 

Are there answers?

In many states, physicians can now request emergency removal of firearms from the home of someone who is both mentally ill and threatening either suicide or homicide. During the era when high-capacity firearms were banned, from 1994 to 2004, mass murders decreased in our country. While most gunmen use legal firearms they have purchased, I would contend that “smart guns” – firearms that allow only the legal owner to operate them based on biometrics – would prevent some mass shootings and many accidents, crimes, and suicides. Universal background checks and tracking gun purchases in the way we monitor controlled medications, or even Sudafed, might allow authorities to predict who might be at risk of committing these heinous acts.

In his newly released book, Trigger Points: Inside the Mission to Stop Mass Murders in America, journalist Mark Follman argues for a proactive community approach using threat assessment methods and providing wraparound services to those who are deemed to be at risk for violent acts. Mr. Follman’s voice is one of the few out there saying that these events are not random and are, in fact, preventable.

In psychiatry, we struggle with school shootings such as the one we just saw in Uvalde. Our own hearts ache as we hold our children close and empathize with the loss of strangers who have been through the unthinkable. We help our patients as they process their emotions. And we wonder whether any of our patients might ever do anything so horrific. The feelings get complicated, the sadness and anger intermingle while the frustration builds, and we are left with our fears and the hope that if that very rare person were to walk through our office door, we would know what to do.

Dr. Miller is a coauthor of Committed: The Battle Over Involuntary Psychiatric Care (Johns Hopkins University Press, 2016). She has a private practice and is assistant professor of psychiatry and behavioral sciences at Johns Hopkins in Baltimore. A version of this article first appeared on Medscape.com.

Here we go again, and again, and again.

There just aren’t enough tears, and before the bodies of 19 small children are identified, the political noise starts up. Mass shootings are a part of the American landscape, but when they happen at schools, we all feel a distinct sense of violation and gaping grief. Those children are so innocent, so deserving of a right to live their lives, hold their place with their families, create their own legacies, and die of natural causes at a ripe old age. And those children could have been our children. There was nothing special about them; they were just sent to school that day like every child who is sent to school every day.

Here is how the politics goes: The Republicans will blame the Democrats and the Democrats will blame the Republicans. Is Rachel Maddow at fault, or is it Tucker Carlson? Social media accounts blamed both of them for the racially motivated mass murder in a Buffalo grocery store on May 14.

Mass murders were previously defined as a shooting where four or more victims are killed, excluding the shooter, in a public place that is not related to the commission of another crime. In 2012, the definition was changed to include events with three victims. This definition excludes gang violence and the murder of family members.

When it comes to explaining mass murder, the camps divide: They are the result of some combination of mental illness, easy access to firearms, and terrorism and hate. For psychiatry, there is a unique place in the argument – half of all mass shooters have exhibited signs or symptoms of psychiatric illness, and for those who want to deflect the issue away from issues related to the regulation of firearms, it becomes easy to blame “mental illness,” as though that explains it all. Either the gunman “snapped” in such a way that no one could have predicted, or the mental health system is at fault for not preventing it.

There are many ways to be emotionally disturbed; mental illness is only one of them, and there is no psychiatric diagnosis that includes the symptom of shooting strangers, or shooting children. The vast majority of people, including nearly all psychiatrists, will never know someone who perpetrates a mass shooting. 

Can mental illness give us any insight into these senseless killings? Sometimes, but rarely. Take John Hinckley Jr., who shot President Ronald Reagan as a means to impress actress Jodie Foster. Sometimes these killings are motivated by delusional beliefs. But the planning and preparation that goes into most mass shootings involves a degree of organization and forethought that we don’t typically see in those with severe psychotic disorders.

The other psychological explanation that satisfies some of a nonmedical population is that these killers “just snap.” This, too, is a term that is not included in our diagnostic vocabulary, but it remains a way for some to explain that which can’t be explained. If mental illness, however, is the cause of mass murders, then more stringent gun control is unnecessary. Every state already has a mechanism to prevent those with criminal and specified psychiatric histories from buying legal firearms, and it may be inevitable that these screens are not perfect. 

The next line of political thinking moves to the psychiatric “if only.” If only there were more state hospital beds and if only it were easier to compel people with psychiatric disorders to get treatment against their will, then we could eliminate these crimes. The Virginia tech shooter was mandated to get outpatient psychiatric treatment after a brief hospitalization, yet he never went and there was no mechanism in place to track him.

In cases where a person with a psychotic illness has a history of repeated violent episodes after stopping medications, it does make sense to mandate treatment, not because they are likely to shoot strangers, but because some people do become violent when they are ill and mental illness is believed to play a role in 10% of murders.

Mass murders remain rare, and while advocates for legislation that would make it easier to mandate involuntary care have cited violence prevention as a reason, it is hard to imagine that we would force people to get care because they “might” commit such a crime – unless there was convincing evidence that someone was at risk of committing such a heinous act.

For those who oppose stronger gun control laws, the “what if” may circulate around the need for even more firearms. What if teachers carried guns? What if schools were more heavily policed? What if the criminals were made to be afraid?

We are left with the fact that other countries do not see these numbers of mass shooting events, yet mental illness is ubiquitous. While the presence of psychiatric disorders does little to explain school shootings, we still have no understanding of what motivated the Sandy Hook killer, and it remains to be seen what we will come to understand about the gunman in Uvalde, Texas.

Mental illness is not unique to the United States; however, the number of available firearms is. In a country of 323 million people (including children and people who live in institutions where they have no access to firearms), there are estimated to be over 400 million guns in the United States, 98% of which are owned by civilians. 

Hate crimes and terrorism are another explanation for mass murders. In these instances, the gunman makes his motive obvious: There are social media announcements, or the site of the shooting is a synagogue, a mosque, or a location where the victims are of a specific race or religion. But hate may come out of a psychotic illness, and easy access to firearms allows for these crimes to continue. 

Firearms are now the No. 1 cause of mortality in children. Very few of these deaths are the result of mass murders. Many more are from accidental deaths, targeted crime, or suicide. Still, school shootings rip at our hearts. Neither the victims nor their grieving families have any role in the act, and suffering leaves its mark on families, communities, and all of us.
 

Are there answers?

In many states, physicians can now request emergency removal of firearms from the home of someone who is both mentally ill and threatening either suicide or homicide. During the era when high-capacity firearms were banned, from 1994 to 2004, mass murders decreased in our country. While most gunmen use legal firearms they have purchased, I would contend that “smart guns” – firearms that allow only the legal owner to operate them based on biometrics – would prevent some mass shootings and many accidents, crimes, and suicides. Universal background checks and tracking gun purchases in the way we monitor controlled medications, or even Sudafed, might allow authorities to predict who might be at risk of committing these heinous acts.

In his newly released book, Trigger Points: Inside the Mission to Stop Mass Murders in America, journalist Mark Follman argues for a proactive community approach using threat assessment methods and providing wraparound services to those who are deemed to be at risk for violent acts. Mr. Follman’s voice is one of the few out there saying that these events are not random and are, in fact, preventable.

In psychiatry, we struggle with school shootings such as the one we just saw in Uvalde. Our own hearts ache as we hold our children close and empathize with the loss of strangers who have been through the unthinkable. We help our patients as they process their emotions. And we wonder whether any of our patients might ever do anything so horrific. The feelings get complicated, the sadness and anger intermingle while the frustration builds, and we are left with our fears and the hope that if that very rare person were to walk through our office door, we would know what to do.

Dr. Miller is a coauthor of Committed: The Battle Over Involuntary Psychiatric Care (Johns Hopkins University Press, 2016). She has a private practice and is assistant professor of psychiatry and behavioral sciences at Johns Hopkins in Baltimore. A version of this article first appeared on Medscape.com.

Here we go again, and again, and again.

There just aren’t enough tears, and before the bodies of 19 small children are identified, the political noise starts up. Mass shootings are a part of the American landscape, but when they happen at schools, we all feel a distinct sense of violation and gaping grief. Those children are so innocent, so deserving of a right to live their lives, hold their place with their families, create their own legacies, and die of natural causes at a ripe old age. And those children could have been our children. There was nothing special about them; they were just sent to school that day like every child who is sent to school every day.

Here is how the politics goes: The Republicans will blame the Democrats and the Democrats will blame the Republicans. Is Rachel Maddow at fault, or is it Tucker Carlson? Social media accounts blamed both of them for the racially motivated mass murder in a Buffalo grocery store on May 14.

Mass murders were previously defined as a shooting where four or more victims are killed, excluding the shooter, in a public place that is not related to the commission of another crime. In 2012, the definition was changed to include events with three victims. This definition excludes gang violence and the murder of family members.

When it comes to explaining mass murder, the camps divide: They are the result of some combination of mental illness, easy access to firearms, and terrorism and hate. For psychiatry, there is a unique place in the argument – half of all mass shooters have exhibited signs or symptoms of psychiatric illness, and for those who want to deflect the issue away from issues related to the regulation of firearms, it becomes easy to blame “mental illness,” as though that explains it all. Either the gunman “snapped” in such a way that no one could have predicted, or the mental health system is at fault for not preventing it.

There are many ways to be emotionally disturbed; mental illness is only one of them, and there is no psychiatric diagnosis that includes the symptom of shooting strangers, or shooting children. The vast majority of people, including nearly all psychiatrists, will never know someone who perpetrates a mass shooting. 

Can mental illness give us any insight into these senseless killings? Sometimes, but rarely. Take John Hinckley Jr., who shot President Ronald Reagan as a means to impress actress Jodie Foster. Sometimes these killings are motivated by delusional beliefs. But the planning and preparation that goes into most mass shootings involves a degree of organization and forethought that we don’t typically see in those with severe psychotic disorders.

The other psychological explanation that satisfies some of a nonmedical population is that these killers “just snap.” This, too, is a term that is not included in our diagnostic vocabulary, but it remains a way for some to explain that which can’t be explained. If mental illness, however, is the cause of mass murders, then more stringent gun control is unnecessary. Every state already has a mechanism to prevent those with criminal and specified psychiatric histories from buying legal firearms, and it may be inevitable that these screens are not perfect. 

The next line of political thinking moves to the psychiatric “if only.” If only there were more state hospital beds and if only it were easier to compel people with psychiatric disorders to get treatment against their will, then we could eliminate these crimes. The Virginia tech shooter was mandated to get outpatient psychiatric treatment after a brief hospitalization, yet he never went and there was no mechanism in place to track him.

In cases where a person with a psychotic illness has a history of repeated violent episodes after stopping medications, it does make sense to mandate treatment, not because they are likely to shoot strangers, but because some people do become violent when they are ill and mental illness is believed to play a role in 10% of murders.

Mass murders remain rare, and while advocates for legislation that would make it easier to mandate involuntary care have cited violence prevention as a reason, it is hard to imagine that we would force people to get care because they “might” commit such a crime – unless there was convincing evidence that someone was at risk of committing such a heinous act.

For those who oppose stronger gun control laws, the “what if” may circulate around the need for even more firearms. What if teachers carried guns? What if schools were more heavily policed? What if the criminals were made to be afraid?

We are left with the fact that other countries do not see these numbers of mass shooting events, yet mental illness is ubiquitous. While the presence of psychiatric disorders does little to explain school shootings, we still have no understanding of what motivated the Sandy Hook killer, and it remains to be seen what we will come to understand about the gunman in Uvalde, Texas.

Mental illness is not unique to the United States; however, the number of available firearms is. In a country of 323 million people (including children and people who live in institutions where they have no access to firearms), there are estimated to be over 400 million guns in the United States, 98% of which are owned by civilians. 

Hate crimes and terrorism are another explanation for mass murders. In these instances, the gunman makes his motive obvious: There are social media announcements, or the site of the shooting is a synagogue, a mosque, or a location where the victims are of a specific race or religion. But hate may come out of a psychotic illness, and easy access to firearms allows for these crimes to continue. 

Firearms are now the No. 1 cause of mortality in children. Very few of these deaths are the result of mass murders. Many more are from accidental deaths, targeted crime, or suicide. Still, school shootings rip at our hearts. Neither the victims nor their grieving families have any role in the act, and suffering leaves its mark on families, communities, and all of us.
 

Are there answers?

In many states, physicians can now request emergency removal of firearms from the home of someone who is both mentally ill and threatening either suicide or homicide. During the era when high-capacity firearms were banned, from 1994 to 2004, mass murders decreased in our country. While most gunmen use legal firearms they have purchased, I would contend that “smart guns” – firearms that allow only the legal owner to operate them based on biometrics – would prevent some mass shootings and many accidents, crimes, and suicides. Universal background checks and tracking gun purchases in the way we monitor controlled medications, or even Sudafed, might allow authorities to predict who might be at risk of committing these heinous acts.

In his newly released book, Trigger Points: Inside the Mission to Stop Mass Murders in America, journalist Mark Follman argues for a proactive community approach using threat assessment methods and providing wraparound services to those who are deemed to be at risk for violent acts. Mr. Follman’s voice is one of the few out there saying that these events are not random and are, in fact, preventable.

In psychiatry, we struggle with school shootings such as the one we just saw in Uvalde. Our own hearts ache as we hold our children close and empathize with the loss of strangers who have been through the unthinkable. We help our patients as they process their emotions. And we wonder whether any of our patients might ever do anything so horrific. The feelings get complicated, the sadness and anger intermingle while the frustration builds, and we are left with our fears and the hope that if that very rare person were to walk through our office door, we would know what to do.

Dr. Miller is a coauthor of Committed: The Battle Over Involuntary Psychiatric Care (Johns Hopkins University Press, 2016). She has a private practice and is assistant professor of psychiatry and behavioral sciences at Johns Hopkins in Baltimore. A version of this article first appeared on Medscape.com.

From Medically Home Group, Boston, MA.

Brick-and-mortar hospitals in the United States have historically been considered the dominant setting for providing care to patients. The coordination and delivery of care has previously been bound to physical hospitals largely because multidisciplinary services were only accessible in an individual location. While the fundamental make-up of these services remains unchanged, these services are now available in alternate settings. Some of these services include access to a patient care team, supplies, diagnostics, pharmacy, and advanced therapeutic interventions. Presently, the physical environment is becoming increasingly irrelevant as the core of what makes the traditional hospital—the professional staff, collaborative work processes, and the dynamics of the space—have all been translated into a modern digitally integrated environment. The elements necessary to providing safe, effective care in a physical hospital setting are now available in a patient’s home.

Impetus for the Model

As hospitals reconsider how and where they deliver patient care because of limited resources, the hospital-at-home model has gained significant momentum and interest. This model transforms a home into a hospital. The inpatient acute care episode is entirely substituted with an intensive at-home hospital admission enabled by technology, multidisciplinary teams, and ancillary services. Furthermore, patients requiring post-acute support can be transitioned to their next phase of care seamlessly. Given the nationwide nursing shortage, aging population, challenges uncovered by the COVID-19 pandemic, rising hospital costs, nurse/provider burnout related to challenging work environments, and capacity constraints, a shift toward the combination of virtual and in-home care is imperative. The hospital-at-home model has been associated with superior patient outcomes, including reduced risks of delirium, improved functional status, improved patient and family member satisfaction, reduced mortality, reduced readmissions, and significantly lower costs.¹ COVID-19 alone has unmasked major facility-based deficiencies and limitations of our health care system. While the pandemic is not the impetus for the hospital-at-home model, the extended stress of this event has created a unique opportunity to reimagine and transform our health care delivery system so that it is less fragmented and more flexible.

Nursing in the Model

Nursing is central to the hospital-at-home model. Virtual nurses provide meticulous care plan oversight, assessment, and documentation across in-home service providers, to ensure holistic, safe, transparent, and continuous progression toward care plan milestones. The virtual nurse monitors patients using in-home technology that is set up at the time of admission. Connecting with patients to verify social and medical needs, the virtual nurse advocates for their patients and uses these technologies to care and deploy on-demand hands-on services to the patient. Service providers such as paramedics, infusion nurses, or home health nurses may be deployed to provide services in the patient’s home. By bringing in supplies, therapeutics, and interdisciplinary team members, the capabilities of a brick-and-mortar hospital are replicated in the home. All actions that occur wherever the patient is receiving care are overseen by professional nursing staff; in short, virtual nurses are the equivalent of bedside nurses in the brick-and-mortar health care facilities.

Potential Benefits

There are many benefits to the hospital-at-home model (Table). This health care model can be particularly helpful for patients who require frequent admission to acute care facilities, and is well suited for patients with a range of conditions, including those with COVID-19, pneumonia, cellulitis, or congestive heart failure. This care model helps eliminate some of the stressors for patients who have chronic illnesses or other conditions that require frequent hospital admissions. Patients can independently recover at home and can also be surrounded by their loved ones and pets while recovering. This care approach additionally eliminates the risk of hospital-acquired infections and injuries. The hospital-at-home model allows for increased mobility,² as patients are familiar with their surroundings, resulting in reduced onset of delirium. Additionally, patients with improved mobility performance are less likely to experience negative health outcomes.³ There is less chance of sleep disruption as the patient is sleeping in their own bed—no unfamiliar roommate, no call bells or health care personnel frequently coming into the room. The in-home technology set up for remote patient monitoring is designed with the user in mind. Ease of use empowers the patient to collaborate with their care team on their own terms and center the priorities of themselves and their families.

Positive Outcomes

The hospital-at-home model is associated with positive outcomes. The authors of a systematic review identified 10 randomized controlled trials of hospital-at-home programs (with a total of 1372 patients), but were able to obtain data for only 5 of these trials (with a total of 844 patients).⁴ They found a 38% reduction in 6-month mortality for patients who received hospital care at home, as well as significantly higher patient satisfaction across a range of medical conditions, including patients with cellulitis and community-acquired pneumonia, as well as elderly patients with multiple medical conditions. The authors concluded that hospital care at home was less expensive than admission to an acute care hospital.⁴ Similarly, a meta-analysis done by Caplan et al⁵ that included 61 randomized controlled trials concluded that hospital at home is associated with reductions in mortality, readmission rates, and cost, and increases in patient and caregiver satisfaction. Levine et al² found reduced costs and utilization with home hospitalization compared to in-hospital care, as well as improved patient mobility status.

The home is the ideal place to empower patients and caregivers to engage in self-management.² Receiving hospital care at home eliminates the need for dealing with transportation arrangements, traffic, road tolls, and time/scheduling constraints, or finding care for a dependent family member, some of the many stressors that may be experienced by patients who require frequent trips to the hospital. For patients who may not be clinically suitable candidates for hospital at home, such as those requiring critical care intervention and support, the brick-and-mortar hospital is still the appropriate site of care. The hospital-at-home model helps prevent bed shortages in brick-and-mortar hospital settings by allowing hospital care at home for patients who meet preset criteria. These patients can be hospitalized in alternative locations such as their own homes or the residence of a friend. This helps increase health system capacity as well as resiliency.

In addition to expanding safe and appropriate treatment spaces, the hospital-at-home model helps increase access to care for patients during nonstandard hours, including weekends, holidays, or when the waiting time in the emergency room is painfully long. Furthermore, providing care in the home gives the clinical team valuable insight into the patient’s daily life and routine. Performing medication reconciliation with the medicine cabinet in sight and dietary education in a patient’s kitchen are powerful touch points.² For example, a patient with congestive heart failure who must undergo diuresis is much more likely to meet their care goals when their home diet is aligned with the treatment goal. By being able to see exactly what is in a patient’s pantry and fridge, the care team can create a much more tailored approach to sodium intake and fluid management. Providers can create and execute true patient-centric care as they gain direct insight into the patient’s lifestyle, which is clearly valuable when creating care plans for complex chronic health issues.

Although there are clear benefits to hospital at home, how to best implement and scale this model presents a challenge. In addition to educating patients and families about this model of care, health care systems must expand their hospital-at-home programs and provide education about this model to clinical staff and trainees, and insurers must create reimbursement paradigms. Patients meeting eligibility criteria to enroll in hospital at home is the easiest hurdle, as hospital-at-home programs function best when they enroll and service as many patients as possible, including underserved populations.

Upfront Costs and Cost Savings

While there are upfront costs to set up technology and coordinate services, hospital at home also provides significant total cost savings when compared to coordination associated with brick-and-mortar admission. Hospital care accounts for about one-third of total medical expenditures and is a leading cause of debt.² Eliminating fixed hospital costs such as facility, overhead, and equipment costs through adoption of the hospital-at-home model can lead to a reduction in expenditures. It has been found that fewer laboratory and diagnostic tests are ordered for hospital-at-home patients when compared to similar patients in brick-and-mortar hospital settings, with comparable or better clinical patient outcomes.⁶ Furthermore, it is estimated that there are cost savings of 19% to 30% when compared to traditional inpatient care.⁶ Without legislative action, upon the end of the current COVID-19 public health emergency, the Centers for Medicare & Medicaid Service’s Acute Hospital Care at Home waiver will terminate. This could slow down scaling of the model.However, over the past 2 years there has been enough buy-in from major health systems and patients to continue the momentum of the model’s growth. When setting up a hospital-at-home program, it would be wise to consider a few factors: where in the hospital or health system entity structure the hospital-at-home program will reside, which existing resources can be leveraged within the hospital or health system, and what are the state or federal regulatory requirements for such a program. This type of program continues to fill gaps within the US health care system, meeting the needs of widely overlooked populations and increasing access to essential ancillary services.

Conclusion

It is time to consider our bias toward hospital-first options when managing the care needs of our patients. Health care providers have the option to advocate for holistic care, better experience, and better outcomes. Home-based options are safe, equitable, and patient-centric. Increased costs, consumerism, and technology have pushed us to think about alternative approaches to patient care delivery, and the pandemic created a unique opportunity to see just how far the health care system could stretch itself with capacity constraints, insufficient resources, and staff shortages. In light of new possibilities, it is time to reimagine and transform our health care delivery system so that it is unified, seamless, cohesive, and flexible.

Corresponding author: Payal Sharma, DNP, MSN, RN, FNP-BC, CBN; psharma@medicallyhome.com.

Disclosures: None reported.

From Medically Home Group, Boston, MA.

Brick-and-mortar hospitals in the United States have historically been considered the dominant setting for providing care to patients. The coordination and delivery of care has previously been bound to physical hospitals largely because multidisciplinary services were only accessible in an individual location. While the fundamental make-up of these services remains unchanged, these services are now available in alternate settings. Some of these services include access to a patient care team, supplies, diagnostics, pharmacy, and advanced therapeutic interventions. Presently, the physical environment is becoming increasingly irrelevant as the core of what makes the traditional hospital—the professional staff, collaborative work processes, and the dynamics of the space—have all been translated into a modern digitally integrated environment. The elements necessary to providing safe, effective care in a physical hospital setting are now available in a patient’s home.

Impetus for the Model

As hospitals reconsider how and where they deliver patient care because of limited resources, the hospital-at-home model has gained significant momentum and interest. This model transforms a home into a hospital. The inpatient acute care episode is entirely substituted with an intensive at-home hospital admission enabled by technology, multidisciplinary teams, and ancillary services. Furthermore, patients requiring post-acute support can be transitioned to their next phase of care seamlessly. Given the nationwide nursing shortage, aging population, challenges uncovered by the COVID-19 pandemic, rising hospital costs, nurse/provider burnout related to challenging work environments, and capacity constraints, a shift toward the combination of virtual and in-home care is imperative. The hospital-at-home model has been associated with superior patient outcomes, including reduced risks of delirium, improved functional status, improved patient and family member satisfaction, reduced mortality, reduced readmissions, and significantly lower costs.¹ COVID-19 alone has unmasked major facility-based deficiencies and limitations of our health care system. While the pandemic is not the impetus for the hospital-at-home model, the extended stress of this event has created a unique opportunity to reimagine and transform our health care delivery system so that it is less fragmented and more flexible.

Nursing in the Model

Nursing is central to the hospital-at-home model. Virtual nurses provide meticulous care plan oversight, assessment, and documentation across in-home service providers, to ensure holistic, safe, transparent, and continuous progression toward care plan milestones. The virtual nurse monitors patients using in-home technology that is set up at the time of admission. Connecting with patients to verify social and medical needs, the virtual nurse advocates for their patients and uses these technologies to care and deploy on-demand hands-on services to the patient. Service providers such as paramedics, infusion nurses, or home health nurses may be deployed to provide services in the patient’s home. By bringing in supplies, therapeutics, and interdisciplinary team members, the capabilities of a brick-and-mortar hospital are replicated in the home. All actions that occur wherever the patient is receiving care are overseen by professional nursing staff; in short, virtual nurses are the equivalent of bedside nurses in the brick-and-mortar health care facilities.

Potential Benefits

There are many benefits to the hospital-at-home model (Table). This health care model can be particularly helpful for patients who require frequent admission to acute care facilities, and is well suited for patients with a range of conditions, including those with COVID-19, pneumonia, cellulitis, or congestive heart failure. This care model helps eliminate some of the stressors for patients who have chronic illnesses or other conditions that require frequent hospital admissions. Patients can independently recover at home and can also be surrounded by their loved ones and pets while recovering. This care approach additionally eliminates the risk of hospital-acquired infections and injuries. The hospital-at-home model allows for increased mobility,² as patients are familiar with their surroundings, resulting in reduced onset of delirium. Additionally, patients with improved mobility performance are less likely to experience negative health outcomes.³ There is less chance of sleep disruption as the patient is sleeping in their own bed—no unfamiliar roommate, no call bells or health care personnel frequently coming into the room. The in-home technology set up for remote patient monitoring is designed with the user in mind. Ease of use empowers the patient to collaborate with their care team on their own terms and center the priorities of themselves and their families.

Positive Outcomes

The hospital-at-home model is associated with positive outcomes. The authors of a systematic review identified 10 randomized controlled trials of hospital-at-home programs (with a total of 1372 patients), but were able to obtain data for only 5 of these trials (with a total of 844 patients).⁴ They found a 38% reduction in 6-month mortality for patients who received hospital care at home, as well as significantly higher patient satisfaction across a range of medical conditions, including patients with cellulitis and community-acquired pneumonia, as well as elderly patients with multiple medical conditions. The authors concluded that hospital care at home was less expensive than admission to an acute care hospital.⁴ Similarly, a meta-analysis done by Caplan et al⁵ that included 61 randomized controlled trials concluded that hospital at home is associated with reductions in mortality, readmission rates, and cost, and increases in patient and caregiver satisfaction. Levine et al² found reduced costs and utilization with home hospitalization compared to in-hospital care, as well as improved patient mobility status.

The home is the ideal place to empower patients and caregivers to engage in self-management.² Receiving hospital care at home eliminates the need for dealing with transportation arrangements, traffic, road tolls, and time/scheduling constraints, or finding care for a dependent family member, some of the many stressors that may be experienced by patients who require frequent trips to the hospital. For patients who may not be clinically suitable candidates for hospital at home, such as those requiring critical care intervention and support, the brick-and-mortar hospital is still the appropriate site of care. The hospital-at-home model helps prevent bed shortages in brick-and-mortar hospital settings by allowing hospital care at home for patients who meet preset criteria. These patients can be hospitalized in alternative locations such as their own homes or the residence of a friend. This helps increase health system capacity as well as resiliency.

In addition to expanding safe and appropriate treatment spaces, the hospital-at-home model helps increase access to care for patients during nonstandard hours, including weekends, holidays, or when the waiting time in the emergency room is painfully long. Furthermore, providing care in the home gives the clinical team valuable insight into the patient’s daily life and routine. Performing medication reconciliation with the medicine cabinet in sight and dietary education in a patient’s kitchen are powerful touch points.² For example, a patient with congestive heart failure who must undergo diuresis is much more likely to meet their care goals when their home diet is aligned with the treatment goal. By being able to see exactly what is in a patient’s pantry and fridge, the care team can create a much more tailored approach to sodium intake and fluid management. Providers can create and execute true patient-centric care as they gain direct insight into the patient’s lifestyle, which is clearly valuable when creating care plans for complex chronic health issues.

Although there are clear benefits to hospital at home, how to best implement and scale this model presents a challenge. In addition to educating patients and families about this model of care, health care systems must expand their hospital-at-home programs and provide education about this model to clinical staff and trainees, and insurers must create reimbursement paradigms. Patients meeting eligibility criteria to enroll in hospital at home is the easiest hurdle, as hospital-at-home programs function best when they enroll and service as many patients as possible, including underserved populations.

Upfront Costs and Cost Savings

While there are upfront costs to set up technology and coordinate services, hospital at home also provides significant total cost savings when compared to coordination associated with brick-and-mortar admission. Hospital care accounts for about one-third of total medical expenditures and is a leading cause of debt.² Eliminating fixed hospital costs such as facility, overhead, and equipment costs through adoption of the hospital-at-home model can lead to a reduction in expenditures. It has been found that fewer laboratory and diagnostic tests are ordered for hospital-at-home patients when compared to similar patients in brick-and-mortar hospital settings, with comparable or better clinical patient outcomes.⁶ Furthermore, it is estimated that there are cost savings of 19% to 30% when compared to traditional inpatient care.⁶ Without legislative action, upon the end of the current COVID-19 public health emergency, the Centers for Medicare & Medicaid Service’s Acute Hospital Care at Home waiver will terminate. This could slow down scaling of the model.However, over the past 2 years there has been enough buy-in from major health systems and patients to continue the momentum of the model’s growth. When setting up a hospital-at-home program, it would be wise to consider a few factors: where in the hospital or health system entity structure the hospital-at-home program will reside, which existing resources can be leveraged within the hospital or health system, and what are the state or federal regulatory requirements for such a program. This type of program continues to fill gaps within the US health care system, meeting the needs of widely overlooked populations and increasing access to essential ancillary services.

Conclusion

It is time to consider our bias toward hospital-first options when managing the care needs of our patients. Health care providers have the option to advocate for holistic care, better experience, and better outcomes. Home-based options are safe, equitable, and patient-centric. Increased costs, consumerism, and technology have pushed us to think about alternative approaches to patient care delivery, and the pandemic created a unique opportunity to see just how far the health care system could stretch itself with capacity constraints, insufficient resources, and staff shortages. In light of new possibilities, it is time to reimagine and transform our health care delivery system so that it is unified, seamless, cohesive, and flexible.

Corresponding author: Payal Sharma, DNP, MSN, RN, FNP-BC, CBN; psharma@medicallyhome.com.

Disclosures: None reported.

From Medically Home Group, Boston, MA.

Brick-and-mortar hospitals in the United States have historically been considered the dominant setting for providing care to patients. The coordination and delivery of care has previously been bound to physical hospitals largely because multidisciplinary services were only accessible in an individual location. While the fundamental make-up of these services remains unchanged, these services are now available in alternate settings. Some of these services include access to a patient care team, supplies, diagnostics, pharmacy, and advanced therapeutic interventions. Presently, the physical environment is becoming increasingly irrelevant as the core of what makes the traditional hospital—the professional staff, collaborative work processes, and the dynamics of the space—have all been translated into a modern digitally integrated environment. The elements necessary to providing safe, effective care in a physical hospital setting are now available in a patient’s home.

Impetus for the Model

As hospitals reconsider how and where they deliver patient care because of limited resources, the hospital-at-home model has gained significant momentum and interest. This model transforms a home into a hospital. The inpatient acute care episode is entirely substituted with an intensive at-home hospital admission enabled by technology, multidisciplinary teams, and ancillary services. Furthermore, patients requiring post-acute support can be transitioned to their next phase of care seamlessly. Given the nationwide nursing shortage, aging population, challenges uncovered by the COVID-19 pandemic, rising hospital costs, nurse/provider burnout related to challenging work environments, and capacity constraints, a shift toward the combination of virtual and in-home care is imperative. The hospital-at-home model has been associated with superior patient outcomes, including reduced risks of delirium, improved functional status, improved patient and family member satisfaction, reduced mortality, reduced readmissions, and significantly lower costs.¹ COVID-19 alone has unmasked major facility-based deficiencies and limitations of our health care system. While the pandemic is not the impetus for the hospital-at-home model, the extended stress of this event has created a unique opportunity to reimagine and transform our health care delivery system so that it is less fragmented and more flexible.

Nursing in the Model

Nursing is central to the hospital-at-home model. Virtual nurses provide meticulous care plan oversight, assessment, and documentation across in-home service providers, to ensure holistic, safe, transparent, and continuous progression toward care plan milestones. The virtual nurse monitors patients using in-home technology that is set up at the time of admission. Connecting with patients to verify social and medical needs, the virtual nurse advocates for their patients and uses these technologies to care and deploy on-demand hands-on services to the patient. Service providers such as paramedics, infusion nurses, or home health nurses may be deployed to provide services in the patient’s home. By bringing in supplies, therapeutics, and interdisciplinary team members, the capabilities of a brick-and-mortar hospital are replicated in the home. All actions that occur wherever the patient is receiving care are overseen by professional nursing staff; in short, virtual nurses are the equivalent of bedside nurses in the brick-and-mortar health care facilities.

Potential Benefits

There are many benefits to the hospital-at-home model (Table). This health care model can be particularly helpful for patients who require frequent admission to acute care facilities, and is well suited for patients with a range of conditions, including those with COVID-19, pneumonia, cellulitis, or congestive heart failure. This care model helps eliminate some of the stressors for patients who have chronic illnesses or other conditions that require frequent hospital admissions. Patients can independently recover at home and can also be surrounded by their loved ones and pets while recovering. This care approach additionally eliminates the risk of hospital-acquired infections and injuries. The hospital-at-home model allows for increased mobility,² as patients are familiar with their surroundings, resulting in reduced onset of delirium. Additionally, patients with improved mobility performance are less likely to experience negative health outcomes.³ There is less chance of sleep disruption as the patient is sleeping in their own bed—no unfamiliar roommate, no call bells or health care personnel frequently coming into the room. The in-home technology set up for remote patient monitoring is designed with the user in mind. Ease of use empowers the patient to collaborate with their care team on their own terms and center the priorities of themselves and their families.

Positive Outcomes

The hospital-at-home model is associated with positive outcomes. The authors of a systematic review identified 10 randomized controlled trials of hospital-at-home programs (with a total of 1372 patients), but were able to obtain data for only 5 of these trials (with a total of 844 patients).⁴ They found a 38% reduction in 6-month mortality for patients who received hospital care at home, as well as significantly higher patient satisfaction across a range of medical conditions, including patients with cellulitis and community-acquired pneumonia, as well as elderly patients with multiple medical conditions. The authors concluded that hospital care at home was less expensive than admission to an acute care hospital.⁴ Similarly, a meta-analysis done by Caplan et al⁵ that included 61 randomized controlled trials concluded that hospital at home is associated with reductions in mortality, readmission rates, and cost, and increases in patient and caregiver satisfaction. Levine et al² found reduced costs and utilization with home hospitalization compared to in-hospital care, as well as improved patient mobility status.

The home is the ideal place to empower patients and caregivers to engage in self-management.² Receiving hospital care at home eliminates the need for dealing with transportation arrangements, traffic, road tolls, and time/scheduling constraints, or finding care for a dependent family member, some of the many stressors that may be experienced by patients who require frequent trips to the hospital. For patients who may not be clinically suitable candidates for hospital at home, such as those requiring critical care intervention and support, the brick-and-mortar hospital is still the appropriate site of care. The hospital-at-home model helps prevent bed shortages in brick-and-mortar hospital settings by allowing hospital care at home for patients who meet preset criteria. These patients can be hospitalized in alternative locations such as their own homes or the residence of a friend. This helps increase health system capacity as well as resiliency.

In addition to expanding safe and appropriate treatment spaces, the hospital-at-home model helps increase access to care for patients during nonstandard hours, including weekends, holidays, or when the waiting time in the emergency room is painfully long. Furthermore, providing care in the home gives the clinical team valuable insight into the patient’s daily life and routine. Performing medication reconciliation with the medicine cabinet in sight and dietary education in a patient’s kitchen are powerful touch points.² For example, a patient with congestive heart failure who must undergo diuresis is much more likely to meet their care goals when their home diet is aligned with the treatment goal. By being able to see exactly what is in a patient’s pantry and fridge, the care team can create a much more tailored approach to sodium intake and fluid management. Providers can create and execute true patient-centric care as they gain direct insight into the patient’s lifestyle, which is clearly valuable when creating care plans for complex chronic health issues.

Although there are clear benefits to hospital at home, how to best implement and scale this model presents a challenge. In addition to educating patients and families about this model of care, health care systems must expand their hospital-at-home programs and provide education about this model to clinical staff and trainees, and insurers must create reimbursement paradigms. Patients meeting eligibility criteria to enroll in hospital at home is the easiest hurdle, as hospital-at-home programs function best when they enroll and service as many patients as possible, including underserved populations.

Upfront Costs and Cost Savings

While there are upfront costs to set up technology and coordinate services, hospital at home also provides significant total cost savings when compared to coordination associated with brick-and-mortar admission. Hospital care accounts for about one-third of total medical expenditures and is a leading cause of debt.² Eliminating fixed hospital costs such as facility, overhead, and equipment costs through adoption of the hospital-at-home model can lead to a reduction in expenditures. It has been found that fewer laboratory and diagnostic tests are ordered for hospital-at-home patients when compared to similar patients in brick-and-mortar hospital settings, with comparable or better clinical patient outcomes.⁶ Furthermore, it is estimated that there are cost savings of 19% to 30% when compared to traditional inpatient care.⁶ Without legislative action, upon the end of the current COVID-19 public health emergency, the Centers for Medicare & Medicaid Service’s Acute Hospital Care at Home waiver will terminate. This could slow down scaling of the model.However, over the past 2 years there has been enough buy-in from major health systems and patients to continue the momentum of the model’s growth. When setting up a hospital-at-home program, it would be wise to consider a few factors: where in the hospital or health system entity structure the hospital-at-home program will reside, which existing resources can be leveraged within the hospital or health system, and what are the state or federal regulatory requirements for such a program. This type of program continues to fill gaps within the US health care system, meeting the needs of widely overlooked populations and increasing access to essential ancillary services.

Conclusion

It is time to consider our bias toward hospital-first options when managing the care needs of our patients. Health care providers have the option to advocate for holistic care, better experience, and better outcomes. Home-based options are safe, equitable, and patient-centric. Increased costs, consumerism, and technology have pushed us to think about alternative approaches to patient care delivery, and the pandemic created a unique opportunity to see just how far the health care system could stretch itself with capacity constraints, insufficient resources, and staff shortages. In light of new possibilities, it is time to reimagine and transform our health care delivery system so that it is unified, seamless, cohesive, and flexible.

Corresponding author: Payal Sharma, DNP, MSN, RN, FNP-BC, CBN; psharma@medicallyhome.com.

Disclosures: None reported.

From the Department of Cardiothoracic Surgery, Stanford University, Stanford, CA.

Abstract

Complex cardiac patients are often referred for surgery or palliative care based on the risk of perioperative mortality. This decision ignores factors such as quality of life or duration of life in either surgery or the palliative path. Here, we propose a model to numerically assess and compare the value of surgery vs palliation. This model includes quality and duration of life, as well as risk of perioperative mortality, and involves a patient’s preferences in the decision-making process.

For each pathway, surgery or palliative care, a value is calculated and compared to a normal life value (no disease symptoms and normal life expectancy). The formula is adjusted for the risk of operative mortality. The model produces a ratio of the value of surgery to the value of palliative care that signifies the superiority of one or another. This model calculation presents an objective estimated numerical value to compare the value of surgery and palliative care. It can be applied to every decision-making process before surgery. In general, if a procedure has the potential to significantly extend life in a patient who otherwise has a very short life expectancy with palliation only, performing high-risk surgery would be a reasonable option. A model that provides a numerical value for surgery vs palliative care and includes quality and duration of life in each pathway could be a useful tool for cardiac surgeons in decision making regarding high-risk surgery.

Keywords: high-risk surgery, palliative care, quality of life, life expectancy.

Patients with complex cardiovascular disease are occasionally considered inoperable due to the high risk of surgical mortality. When the risk of perioperative mortality (POM) is predicted to be too high, surgical intervention is denied, and patients are often referred to palliative care. The risk of POM in cardiac surgery is often calculated using large-scale databases, such as the Society of Thoracic Surgeons (STS) records. The STS risk models, which are regularly updated, are based on large data sets and incorporate precise statistical methods for risk adjustment.¹ In general, these calculators provide a percentage value that defines the magnitude of the risk of death, and then an arbitrary range is selected to categorize the procedure as low, medium, or high risk or inoperable status. The STS database does not set a cutoff point or range to define “operability.” Assigning inoperable status to a certain risk rate is problematic, with many ethical, legal, and moral implications, and for this reason, it has mostly remained undefined. In contrast, the low- and medium-risk ranges are easier to define. Another limitation encountered in the STS database is the lack of risk data for less common but very high-risk procedures, such as a triple valve replacement.

A common example where risk classification has been defined is in patients who are candidates for surgical vs transcatheter aortic valve replacement. Some groups have described a risk of <4% as low risk, 4% to 8% as intermediate risk, >8% as high risk, and >15% as inoperable²; for some other groups, a risk of POM >50% is considered extreme risk or inoperable.^3,4 This procedure-specific classification is a useful decision-making tool and helps the surgeon perform an initial risk assessment to allocate a specific patient to a group—operable or nonoperable—only by calculating the risk of surgical death. However, this allocation method does not provide any information on how and when death occurs in either group. These 2 parameters of how and when death occurs define the quality of life (QOL) and the duration of life (DOL), respectively, and together could be considered as the value of life in each pathway. A survivor of a high-risk surgery may benefit from good quality and extended life (a high value), or, on the other end of the spectrum, a high-risk patient who does not undergo surgery is spared the mortality risk of the surgery but dies sooner (low value) with symptoms due to the natural course of the untreated disease.

The central question is, if a surgery is high risk but has the potential of providing a good value (for those who survive it), what QOL and DOL values are acceptable to risk or to justify accepting and proceeding with a risky surgery? Or how high a POM risk is justified to proceed with surgery rather than the alternative palliative care with a certain quality and duration? It is obvious that a decision-making process that is based on POM cannot compare the value of surgery (Vs) and the value of palliation (Vp). Furthermore, it ignores patient preferences and their input, as these are excluded from this decision-making process.

To be able to include QOL and DOL in any decision making, one must precisely describe these parameters. Both QOL and DOL are used for estimation of disease burden by health care administrators, public health experts, insurance agencies, and others. Multiple models have been proposed and used to estimate the overall burden of the disease. Most of the models for this purpose are created for large-scale economic purposes and not for decision making in individual cases.

An important measure is the quality-adjusted life year (QALY). This is an important parameter since it includes both measures of quality and quantity of life.^5,6 QALY is a simplified measure to assess the value of health outcomes, and it has been used in economic calculations to assess mainly the cost-effectiveness of various interventions. We sought to evaluate the utility of a similar method in adding further insight into the surgical decision-making process. In this article, we propose a simple model to compare the value of surgery vs palliative care, similar to QALY. This model includes and adjusts for the quality and the quantity of life, in addition to the risk of POM, in the decision-making process for high-risk patients.

The Model

The 2 decision pathways, surgery and palliative care, are compared for their value. We define the value as the product of QOL and DOL in each pathway and use the severity of the symptoms as a surrogate for QOL. If duration and quality were depicted on the x and y axes of a graph (Figure 1), then the area under the curve would represent the collective value in each situation. Figure 2 shows the timeline and the different pathways with each decision. The value in each situation is calculated in relation to the full value, which is represented as the value of normal life (Vn), that is, life without disease and with normal life expectancy. The values of each decision pathway, the value of surgery (Vs) and the value of palliation (Vp), are then compared to define the benefit for each decision as follows:

If Vs/Vp > 1, the benefit is toward surgery;

If Vs/Vp < 1, the benefit is for palliative care.

Definitions

Both quality and duration of life are presented on a 1-10 scale, 1 being the lowest and 10 the highest value, to yield a product with a value of 100 in normal, disease-free life. Any lower value is presented as a percentage to represent the comparison to the full value. QOL is determined by degradation of full quality with the average level of symptoms. DOL is calculated as a lost time (period of time from death after a specific intervention [surgery or palliation] until death at normal life expectancy) in fraction of full life (death at life expectancy). The Vs is adjusted to exclude the nonsurvivors using the chance of survival (100 – POM risk).

For the DOL under any condition, a 10-year survival rate could be used as a surrogate in this formula. Compared to life expectancy value, using the 10-year survival rate simplifies the calculation since cardiac diseases are more prevalent in older age, close to or beyond the average life expectancy value.

Using the time intervals from the timeline in Figure 2:

dh = time interval from diagnosis to death at life expectancy

dg = time interval from diagnosis to death after successful surgery

df = time interval from diagnosis to death after palliative care

Duration for palliative care:

Duration for surgery:

Adjustment: This value is calculated for those who survive the surgery. To adjust for the POM, it is multiplied by the 100 − POM risk.

Since value is the base for comparison in this model, and it is the product of 2 equally important factors in the formula (severity and duration of symptoms), a factor of 10 was chosen to yield a value of 100, which represents 100% health or absence of symptoms for any duration.

After elimination of normal life expectancy, form the numerator and denominator:

To adjust for surgical outcomes in special circumstances where less than optimal or standard surgical results are expected (eg, in very rare surgeries, limited resource institutions, or suboptimal postoperative surgical care), an optional coefficient R can be added to the numerator (surgical value). This optional coefficient, with values such as 0.8, 0.9 (to degrade the value of surgery) or 1 (standard surgical outcome), adjusts for variability in interinstitutional surgical results or surgeon variability. No coefficient is added to the denominator since palliative care provides minimal differences between clinicians and hospitals. Thus, the final adjusted formula would be as follows:

Example

A 60-year-old patient with a 10% POM risk needs to be allocated to surgical or palliative care. With palliative care, if this patient lived 6 years with average symptoms grade 4, the Vp would be 20; that is, 20% of the normal life value (if he lived 18 years instead without the disease).

Using the formula for calculation of value in each pathway:

With adjustment of 90% survival chance in surgery, 53 × 90% = 48%. In this example, Vs/Vp = 48/20 = 2.4, showing a significant benefit for surgical care. Notably, the unknown value of normal life expectancy is not needed for the calculation of Vs/Vp, since it is the same in both pathways and it is eliminated by calculation in fraction.

Based on this formula, since the duration of surgical symptoms is short, no matter how severe these are, if the potential duration of life after surgery is high (represented by smaller area under the curve in Figure 1), the numerator becomes larger and the value of the surgery grows. For example, if a patient with a 15% risk of POM, which is generally considered inoperable, lives 5 years, as opposed to 2 years with palliative care with mild symptoms (eg 3/10), Vs/Vp would be 2.7, still showing a significant benefit for surgical care.

Discussion

Any surgical intervention is offered with 2 goals in mind, improving QOL and extending DOL. In a high-risk patient, surgery might be declined due to a high risk of POM, and the patient is offered palliative care, which other than providing symptom relief does not change the course of disease and eventually the patient will die due to the untreated disease. In this decision-making method, mostly completed by a care team only, a potential risk of death due to surgery which possibly could cure the patient is traded for immediate survival; however, the symptomatic course ensues until death. This mostly unilateral decision-making process by a care team, which incorporates minimal input from the patient or ignores patient preferences altogether, is based only on POM risk, and roughly includes a single parameter: years of potential life lost (YPLL). YPLL is a measure of premature mortality, and in the setting of surgical intervention, YPLL is the number of years a patient would lose unless a successful surgery were undertaken. Obviously, patients would live longer if a surgery that was intended to save them failed.

In this article, we proposed a simple method to quantify each decision to decide whether to operate or choose surgical care vs palliative care. Since quality and duration of life are both end factors clinicians and patients aspire to in each decision, they can be considered together as the value of each decision. We believe a numerical framework would provide an objective way to assist both the patient at high risk and the care team in the decision-making process.

The 2 parameters we consider are DOL and QOL. DOL, or survival, can be extracted from large-scale data using statistical methods that have been developed to predict survival under various conditions, such as Kaplan-Meier curves. These methods present the chance of survival in percentages in a defined time frame, such as a 5- or 10-year period.

While the DOL is a numerical parameter and quantifiable, the QOL is a more complex entity. This subjective parameter bears multiple definitions, aspects, and categories, and therefore multiple scales for quantification of QOL have been proposed. These scales have been used extensively for the purpose of health determination in health care policy and economic planning. Most scales acknowledge that QOL is multifactorial and includes interrelated aspects such as mental and socioeconomic factors. We have also noticed that QOL is better determined by the palliative care team than surgeons, so including these care providers in the decision-making process might reduce surgeon bias.

Since our purpose here is only to assist with the decision on medical intervention, we focus on physical QOL. Multiple scales are used to assess health-related QOL, such as the Assessment of Quality of Life (AQoL)-8D,⁷ EuroQol-5 Dimension (EQ-5D),⁸ 15D,⁹ and the 36-Item Short Form Survey (SF-36).¹⁰ These complex scales are built for systematic reviews, and they are not practical for a clinical user. To simplify and keep this practical, we define QOL by using the severity or grade of symptoms related to the disease the patient has on a scale of 0 to 10. The severity of symptoms can be easily determined using available scales. An applicable scale for this purpose is the Edmonton Symptom Assessment Scale (ESAS), which has been in use for years and has evolved as a useful tool in the medical field.¹¹

Once DOL and QOL are determined on a 1-10 scale, the multiplied value then provides a product that we consider a value. The highest value hoped for in each decision is the achievement of the best QOL and DOL, a value of 100. In Figure 1, a graphic presentation of value in each decision is best seen as the area under the curve. As shown, a successful surgery, even when accompanied by significant symptoms during initial recovery, has a chance (100 – risk of POM%) to gain a larger area under curve (value) by achieving a longer life with no or fewer symptoms. However, in palliative care, progressing disease and even palliated symptoms with a shorter life expectancy impose a large burden on the patient and a much lower value. Note that in this calculation, life expectancy, which is an important but unpredictable factor, is initially included; however, by ratio comparison, it is eliminated, simplifying the calculation further.

Using this formula in different settings reveals that high-risk surgery has a greater potential to reduce YPLL in the general population. Based on this formula, compared to a surgery with potential to significantly extend DOL, a definite shorter and symptomatic life course with palliative care makes it a significantly less favorable option. In fact, in the cardiovascular field, palliative care has minimal or no effect on natural history, as the mechanism of illness is mechanical, such as occlusion of coronary arteries or valve dysfunction, leading eventually to heart failure and death. In a study by Xu et al, although palliative care reduced readmission rates and improved symptoms on a variety of scales, there was no effect on mortality and QOL in patients with heart failure.¹²

No model in this field has proven to be ideal, and this model bears multiple limitations as well. We have used severity of symptoms as a surrogate for QOL based on the fact that cardiac patients with different pathologies who are untreated will have a common final pathway with development of heart failure symptoms that dictate their QOL. Also, grading QOL is a difficult task at times. Even a model such as QALY, which is one of the most used, is not a perfect model and is not free of problems.⁶ The difference in surgical results and life expectancy between sexes and ethnic groups might be a source of bias in this formula. Also, multiple factors directly and indirectly affect QOL and DOL and create inaccuracies; therefore, making an exact science from an inexact one naturally relies on multiple assumptions. Although it has previously been shown that most POM occurs in a short period of time after cardiac surgery,¹³ long-term complications that potentially degrade QOL are not included in this model. By applying this model, one must assume indefinite economic resources. Moreover, applying a single mathematical model in a biologic system and in the general population has intrinsic shortcomings, and it must overlook many other factors (eg, ethical, legal). For example, it will be hard to justify a failed surgery with 15% risk of POM undertaken to eliminate the severe long-lasting symptoms of a disease, while the outcome of a successful surgery with a 20% risk of POM that adds life and quality would be ignored in the current health care system. Thus, regardless of the significant potential, most surgeons would waive a surgery based solely on the percentage rate of POM, perhaps using other terms such as ”peri-nonoperative mortality.”

Conclusion

We have proposed a simple and practical formula for decision making regarding surgical vs palliative care in high-risk patients. By assigning a value that is composed of QOL and DOL in each pathway and including the risk of POM, a ratio of values provides a numerical estimation that can be used to show preference over a specific decision. An advantage of this formula, in addition to presenting an arithmetic value that is easier to understand, is that it can be used in shared decision making with patients. We emphasize that this model is only a preliminary concept at this time and has not been tested or validated for clinical use. Validation of such a model will require extensive work and testing within a large-scale population. We hope that this article will serve as a starting point for the development of other models, and that this formula will become more sophisticated with fewer limitations through larger multidisciplinary efforts in the future.

Corresponding author: Rabin Gerrah, MD, Good Samaritan Regional Medical Center, 3640 NW Samaritan Drive, Suite 100B, Corvallis, OR 97330; rgerrah@stanford.edu.

Disclosures: None reported.

From the Department of Cardiothoracic Surgery, Stanford University, Stanford, CA.

Abstract

Complex cardiac patients are often referred for surgery or palliative care based on the risk of perioperative mortality. This decision ignores factors such as quality of life or duration of life in either surgery or the palliative path. Here, we propose a model to numerically assess and compare the value of surgery vs palliation. This model includes quality and duration of life, as well as risk of perioperative mortality, and involves a patient’s preferences in the decision-making process.

For each pathway, surgery or palliative care, a value is calculated and compared to a normal life value (no disease symptoms and normal life expectancy). The formula is adjusted for the risk of operative mortality. The model produces a ratio of the value of surgery to the value of palliative care that signifies the superiority of one or another. This model calculation presents an objective estimated numerical value to compare the value of surgery and palliative care. It can be applied to every decision-making process before surgery. In general, if a procedure has the potential to significantly extend life in a patient who otherwise has a very short life expectancy with palliation only, performing high-risk surgery would be a reasonable option. A model that provides a numerical value for surgery vs palliative care and includes quality and duration of life in each pathway could be a useful tool for cardiac surgeons in decision making regarding high-risk surgery.

Keywords: high-risk surgery, palliative care, quality of life, life expectancy.

Patients with complex cardiovascular disease are occasionally considered inoperable due to the high risk of surgical mortality. When the risk of perioperative mortality (POM) is predicted to be too high, surgical intervention is denied, and patients are often referred to palliative care. The risk of POM in cardiac surgery is often calculated using large-scale databases, such as the Society of Thoracic Surgeons (STS) records. The STS risk models, which are regularly updated, are based on large data sets and incorporate precise statistical methods for risk adjustment.¹ In general, these calculators provide a percentage value that defines the magnitude of the risk of death, and then an arbitrary range is selected to categorize the procedure as low, medium, or high risk or inoperable status. The STS database does not set a cutoff point or range to define “operability.” Assigning inoperable status to a certain risk rate is problematic, with many ethical, legal, and moral implications, and for this reason, it has mostly remained undefined. In contrast, the low- and medium-risk ranges are easier to define. Another limitation encountered in the STS database is the lack of risk data for less common but very high-risk procedures, such as a triple valve replacement.

A common example where risk classification has been defined is in patients who are candidates for surgical vs transcatheter aortic valve replacement. Some groups have described a risk of <4% as low risk, 4% to 8% as intermediate risk, >8% as high risk, and >15% as inoperable²; for some other groups, a risk of POM >50% is considered extreme risk or inoperable.^3,4 This procedure-specific classification is a useful decision-making tool and helps the surgeon perform an initial risk assessment to allocate a specific patient to a group—operable or nonoperable—only by calculating the risk of surgical death. However, this allocation method does not provide any information on how and when death occurs in either group. These 2 parameters of how and when death occurs define the quality of life (QOL) and the duration of life (DOL), respectively, and together could be considered as the value of life in each pathway. A survivor of a high-risk surgery may benefit from good quality and extended life (a high value), or, on the other end of the spectrum, a high-risk patient who does not undergo surgery is spared the mortality risk of the surgery but dies sooner (low value) with symptoms due to the natural course of the untreated disease.

The central question is, if a surgery is high risk but has the potential of providing a good value (for those who survive it), what QOL and DOL values are acceptable to risk or to justify accepting and proceeding with a risky surgery? Or how high a POM risk is justified to proceed with surgery rather than the alternative palliative care with a certain quality and duration? It is obvious that a decision-making process that is based on POM cannot compare the value of surgery (Vs) and the value of palliation (Vp). Furthermore, it ignores patient preferences and their input, as these are excluded from this decision-making process.

To be able to include QOL and DOL in any decision making, one must precisely describe these parameters. Both QOL and DOL are used for estimation of disease burden by health care administrators, public health experts, insurance agencies, and others. Multiple models have been proposed and used to estimate the overall burden of the disease. Most of the models for this purpose are created for large-scale economic purposes and not for decision making in individual cases.

An important measure is the quality-adjusted life year (QALY). This is an important parameter since it includes both measures of quality and quantity of life.^5,6 QALY is a simplified measure to assess the value of health outcomes, and it has been used in economic calculations to assess mainly the cost-effectiveness of various interventions. We sought to evaluate the utility of a similar method in adding further insight into the surgical decision-making process. In this article, we propose a simple model to compare the value of surgery vs palliative care, similar to QALY. This model includes and adjusts for the quality and the quantity of life, in addition to the risk of POM, in the decision-making process for high-risk patients.

The Model

The 2 decision pathways, surgery and palliative care, are compared for their value. We define the value as the product of QOL and DOL in each pathway and use the severity of the symptoms as a surrogate for QOL. If duration and quality were depicted on the x and y axes of a graph (Figure 1), then the area under the curve would represent the collective value in each situation. Figure 2 shows the timeline and the different pathways with each decision. The value in each situation is calculated in relation to the full value, which is represented as the value of normal life (Vn), that is, life without disease and with normal life expectancy. The values of each decision pathway, the value of surgery (Vs) and the value of palliation (Vp), are then compared to define the benefit for each decision as follows:

If Vs/Vp > 1, the benefit is toward surgery;

If Vs/Vp < 1, the benefit is for palliative care.

Definitions

Both quality and duration of life are presented on a 1-10 scale, 1 being the lowest and 10 the highest value, to yield a product with a value of 100 in normal, disease-free life. Any lower value is presented as a percentage to represent the comparison to the full value. QOL is determined by degradation of full quality with the average level of symptoms. DOL is calculated as a lost time (period of time from death after a specific intervention [surgery or palliation] until death at normal life expectancy) in fraction of full life (death at life expectancy). The Vs is adjusted to exclude the nonsurvivors using the chance of survival (100 – POM risk).

For the DOL under any condition, a 10-year survival rate could be used as a surrogate in this formula. Compared to life expectancy value, using the 10-year survival rate simplifies the calculation since cardiac diseases are more prevalent in older age, close to or beyond the average life expectancy value.

Using the time intervals from the timeline in Figure 2:

dh = time interval from diagnosis to death at life expectancy

dg = time interval from diagnosis to death after successful surgery

df = time interval from diagnosis to death after palliative care

Duration for palliative care:

Duration for surgery:

Adjustment: This value is calculated for those who survive the surgery. To adjust for the POM, it is multiplied by the 100 − POM risk.

Since value is the base for comparison in this model, and it is the product of 2 equally important factors in the formula (severity and duration of symptoms), a factor of 10 was chosen to yield a value of 100, which represents 100% health or absence of symptoms for any duration.

After elimination of normal life expectancy, form the numerator and denominator:

To adjust for surgical outcomes in special circumstances where less than optimal or standard surgical results are expected (eg, in very rare surgeries, limited resource institutions, or suboptimal postoperative surgical care), an optional coefficient R can be added to the numerator (surgical value). This optional coefficient, with values such as 0.8, 0.9 (to degrade the value of surgery) or 1 (standard surgical outcome), adjusts for variability in interinstitutional surgical results or surgeon variability. No coefficient is added to the denominator since palliative care provides minimal differences between clinicians and hospitals. Thus, the final adjusted formula would be as follows:

Example

A 60-year-old patient with a 10% POM risk needs to be allocated to surgical or palliative care. With palliative care, if this patient lived 6 years with average symptoms grade 4, the Vp would be 20; that is, 20% of the normal life value (if he lived 18 years instead without the disease).

Using the formula for calculation of value in each pathway:

With adjustment of 90% survival chance in surgery, 53 × 90% = 48%. In this example, Vs/Vp = 48/20 = 2.4, showing a significant benefit for surgical care. Notably, the unknown value of normal life expectancy is not needed for the calculation of Vs/Vp, since it is the same in both pathways and it is eliminated by calculation in fraction.

Based on this formula, since the duration of surgical symptoms is short, no matter how severe these are, if the potential duration of life after surgery is high (represented by smaller area under the curve in Figure 1), the numerator becomes larger and the value of the surgery grows. For example, if a patient with a 15% risk of POM, which is generally considered inoperable, lives 5 years, as opposed to 2 years with palliative care with mild symptoms (eg 3/10), Vs/Vp would be 2.7, still showing a significant benefit for surgical care.

Discussion

Any surgical intervention is offered with 2 goals in mind, improving QOL and extending DOL. In a high-risk patient, surgery might be declined due to a high risk of POM, and the patient is offered palliative care, which other than providing symptom relief does not change the course of disease and eventually the patient will die due to the untreated disease. In this decision-making method, mostly completed by a care team only, a potential risk of death due to surgery which possibly could cure the patient is traded for immediate survival; however, the symptomatic course ensues until death. This mostly unilateral decision-making process by a care team, which incorporates minimal input from the patient or ignores patient preferences altogether, is based only on POM risk, and roughly includes a single parameter: years of potential life lost (YPLL). YPLL is a measure of premature mortality, and in the setting of surgical intervention, YPLL is the number of years a patient would lose unless a successful surgery were undertaken. Obviously, patients would live longer if a surgery that was intended to save them failed.

In this article, we proposed a simple method to quantify each decision to decide whether to operate or choose surgical care vs palliative care. Since quality and duration of life are both end factors clinicians and patients aspire to in each decision, they can be considered together as the value of each decision. We believe a numerical framework would provide an objective way to assist both the patient at high risk and the care team in the decision-making process.

The 2 parameters we consider are DOL and QOL. DOL, or survival, can be extracted from large-scale data using statistical methods that have been developed to predict survival under various conditions, such as Kaplan-Meier curves. These methods present the chance of survival in percentages in a defined time frame, such as a 5- or 10-year period.

While the DOL is a numerical parameter and quantifiable, the QOL is a more complex entity. This subjective parameter bears multiple definitions, aspects, and categories, and therefore multiple scales for quantification of QOL have been proposed. These scales have been used extensively for the purpose of health determination in health care policy and economic planning. Most scales acknowledge that QOL is multifactorial and includes interrelated aspects such as mental and socioeconomic factors. We have also noticed that QOL is better determined by the palliative care team than surgeons, so including these care providers in the decision-making process might reduce surgeon bias.

Since our purpose here is only to assist with the decision on medical intervention, we focus on physical QOL. Multiple scales are used to assess health-related QOL, such as the Assessment of Quality of Life (AQoL)-8D,⁷ EuroQol-5 Dimension (EQ-5D),⁸ 15D,⁹ and the 36-Item Short Form Survey (SF-36).¹⁰ These complex scales are built for systematic reviews, and they are not practical for a clinical user. To simplify and keep this practical, we define QOL by using the severity or grade of symptoms related to the disease the patient has on a scale of 0 to 10. The severity of symptoms can be easily determined using available scales. An applicable scale for this purpose is the Edmonton Symptom Assessment Scale (ESAS), which has been in use for years and has evolved as a useful tool in the medical field.¹¹

Once DOL and QOL are determined on a 1-10 scale, the multiplied value then provides a product that we consider a value. The highest value hoped for in each decision is the achievement of the best QOL and DOL, a value of 100. In Figure 1, a graphic presentation of value in each decision is best seen as the area under the curve. As shown, a successful surgery, even when accompanied by significant symptoms during initial recovery, has a chance (100 – risk of POM%) to gain a larger area under curve (value) by achieving a longer life with no or fewer symptoms. However, in palliative care, progressing disease and even palliated symptoms with a shorter life expectancy impose a large burden on the patient and a much lower value. Note that in this calculation, life expectancy, which is an important but unpredictable factor, is initially included; however, by ratio comparison, it is eliminated, simplifying the calculation further.

Using this formula in different settings reveals that high-risk surgery has a greater potential to reduce YPLL in the general population. Based on this formula, compared to a surgery with potential to significantly extend DOL, a definite shorter and symptomatic life course with palliative care makes it a significantly less favorable option. In fact, in the cardiovascular field, palliative care has minimal or no effect on natural history, as the mechanism of illness is mechanical, such as occlusion of coronary arteries or valve dysfunction, leading eventually to heart failure and death. In a study by Xu et al, although palliative care reduced readmission rates and improved symptoms on a variety of scales, there was no effect on mortality and QOL in patients with heart failure.¹²

No model in this field has proven to be ideal, and this model bears multiple limitations as well. We have used severity of symptoms as a surrogate for QOL based on the fact that cardiac patients with different pathologies who are untreated will have a common final pathway with development of heart failure symptoms that dictate their QOL. Also, grading QOL is a difficult task at times. Even a model such as QALY, which is one of the most used, is not a perfect model and is not free of problems.⁶ The difference in surgical results and life expectancy between sexes and ethnic groups might be a source of bias in this formula. Also, multiple factors directly and indirectly affect QOL and DOL and create inaccuracies; therefore, making an exact science from an inexact one naturally relies on multiple assumptions. Although it has previously been shown that most POM occurs in a short period of time after cardiac surgery,¹³ long-term complications that potentially degrade QOL are not included in this model. By applying this model, one must assume indefinite economic resources. Moreover, applying a single mathematical model in a biologic system and in the general population has intrinsic shortcomings, and it must overlook many other factors (eg, ethical, legal). For example, it will be hard to justify a failed surgery with 15% risk of POM undertaken to eliminate the severe long-lasting symptoms of a disease, while the outcome of a successful surgery with a 20% risk of POM that adds life and quality would be ignored in the current health care system. Thus, regardless of the significant potential, most surgeons would waive a surgery based solely on the percentage rate of POM, perhaps using other terms such as ”peri-nonoperative mortality.”

Conclusion

We have proposed a simple and practical formula for decision making regarding surgical vs palliative care in high-risk patients. By assigning a value that is composed of QOL and DOL in each pathway and including the risk of POM, a ratio of values provides a numerical estimation that can be used to show preference over a specific decision. An advantage of this formula, in addition to presenting an arithmetic value that is easier to understand, is that it can be used in shared decision making with patients. We emphasize that this model is only a preliminary concept at this time and has not been tested or validated for clinical use. Validation of such a model will require extensive work and testing within a large-scale population. We hope that this article will serve as a starting point for the development of other models, and that this formula will become more sophisticated with fewer limitations through larger multidisciplinary efforts in the future.

Corresponding author: Rabin Gerrah, MD, Good Samaritan Regional Medical Center, 3640 NW Samaritan Drive, Suite 100B, Corvallis, OR 97330; rgerrah@stanford.edu.

Disclosures: None reported.

From the Department of Cardiothoracic Surgery, Stanford University, Stanford, CA.

Abstract

Complex cardiac patients are often referred for surgery or palliative care based on the risk of perioperative mortality. This decision ignores factors such as quality of life or duration of life in either surgery or the palliative path. Here, we propose a model to numerically assess and compare the value of surgery vs palliation. This model includes quality and duration of life, as well as risk of perioperative mortality, and involves a patient’s preferences in the decision-making process.

For each pathway, surgery or palliative care, a value is calculated and compared to a normal life value (no disease symptoms and normal life expectancy). The formula is adjusted for the risk of operative mortality. The model produces a ratio of the value of surgery to the value of palliative care that signifies the superiority of one or another. This model calculation presents an objective estimated numerical value to compare the value of surgery and palliative care. It can be applied to every decision-making process before surgery. In general, if a procedure has the potential to significantly extend life in a patient who otherwise has a very short life expectancy with palliation only, performing high-risk surgery would be a reasonable option. A model that provides a numerical value for surgery vs palliative care and includes quality and duration of life in each pathway could be a useful tool for cardiac surgeons in decision making regarding high-risk surgery.

Keywords: high-risk surgery, palliative care, quality of life, life expectancy.

Patients with complex cardiovascular disease are occasionally considered inoperable due to the high risk of surgical mortality. When the risk of perioperative mortality (POM) is predicted to be too high, surgical intervention is denied, and patients are often referred to palliative care. The risk of POM in cardiac surgery is often calculated using large-scale databases, such as the Society of Thoracic Surgeons (STS) records. The STS risk models, which are regularly updated, are based on large data sets and incorporate precise statistical methods for risk adjustment.¹ In general, these calculators provide a percentage value that defines the magnitude of the risk of death, and then an arbitrary range is selected to categorize the procedure as low, medium, or high risk or inoperable status. The STS database does not set a cutoff point or range to define “operability.” Assigning inoperable status to a certain risk rate is problematic, with many ethical, legal, and moral implications, and for this reason, it has mostly remained undefined. In contrast, the low- and medium-risk ranges are easier to define. Another limitation encountered in the STS database is the lack of risk data for less common but very high-risk procedures, such as a triple valve replacement.

A common example where risk classification has been defined is in patients who are candidates for surgical vs transcatheter aortic valve replacement. Some groups have described a risk of <4% as low risk, 4% to 8% as intermediate risk, >8% as high risk, and >15% as inoperable²; for some other groups, a risk of POM >50% is considered extreme risk or inoperable.^3,4 This procedure-specific classification is a useful decision-making tool and helps the surgeon perform an initial risk assessment to allocate a specific patient to a group—operable or nonoperable—only by calculating the risk of surgical death. However, this allocation method does not provide any information on how and when death occurs in either group. These 2 parameters of how and when death occurs define the quality of life (QOL) and the duration of life (DOL), respectively, and together could be considered as the value of life in each pathway. A survivor of a high-risk surgery may benefit from good quality and extended life (a high value), or, on the other end of the spectrum, a high-risk patient who does not undergo surgery is spared the mortality risk of the surgery but dies sooner (low value) with symptoms due to the natural course of the untreated disease.

The central question is, if a surgery is high risk but has the potential of providing a good value (for those who survive it), what QOL and DOL values are acceptable to risk or to justify accepting and proceeding with a risky surgery? Or how high a POM risk is justified to proceed with surgery rather than the alternative palliative care with a certain quality and duration? It is obvious that a decision-making process that is based on POM cannot compare the value of surgery (Vs) and the value of palliation (Vp). Furthermore, it ignores patient preferences and their input, as these are excluded from this decision-making process.

To be able to include QOL and DOL in any decision making, one must precisely describe these parameters. Both QOL and DOL are used for estimation of disease burden by health care administrators, public health experts, insurance agencies, and others. Multiple models have been proposed and used to estimate the overall burden of the disease. Most of the models for this purpose are created for large-scale economic purposes and not for decision making in individual cases.

An important measure is the quality-adjusted life year (QALY). This is an important parameter since it includes both measures of quality and quantity of life.^5,6 QALY is a simplified measure to assess the value of health outcomes, and it has been used in economic calculations to assess mainly the cost-effectiveness of various interventions. We sought to evaluate the utility of a similar method in adding further insight into the surgical decision-making process. In this article, we propose a simple model to compare the value of surgery vs palliative care, similar to QALY. This model includes and adjusts for the quality and the quantity of life, in addition to the risk of POM, in the decision-making process for high-risk patients.

The Model

The 2 decision pathways, surgery and palliative care, are compared for their value. We define the value as the product of QOL and DOL in each pathway and use the severity of the symptoms as a surrogate for QOL. If duration and quality were depicted on the x and y axes of a graph (Figure 1), then the area under the curve would represent the collective value in each situation. Figure 2 shows the timeline and the different pathways with each decision. The value in each situation is calculated in relation to the full value, which is represented as the value of normal life (Vn), that is, life without disease and with normal life expectancy. The values of each decision pathway, the value of surgery (Vs) and the value of palliation (Vp), are then compared to define the benefit for each decision as follows:

If Vs/Vp > 1, the benefit is toward surgery;

If Vs/Vp < 1, the benefit is for palliative care.

Definitions

Both quality and duration of life are presented on a 1-10 scale, 1 being the lowest and 10 the highest value, to yield a product with a value of 100 in normal, disease-free life. Any lower value is presented as a percentage to represent the comparison to the full value. QOL is determined by degradation of full quality with the average level of symptoms. DOL is calculated as a lost time (period of time from death after a specific intervention [surgery or palliation] until death at normal life expectancy) in fraction of full life (death at life expectancy). The Vs is adjusted to exclude the nonsurvivors using the chance of survival (100 – POM risk).

For the DOL under any condition, a 10-year survival rate could be used as a surrogate in this formula. Compared to life expectancy value, using the 10-year survival rate simplifies the calculation since cardiac diseases are more prevalent in older age, close to or beyond the average life expectancy value.

Using the time intervals from the timeline in Figure 2:

dh = time interval from diagnosis to death at life expectancy

dg = time interval from diagnosis to death after successful surgery

df = time interval from diagnosis to death after palliative care

Duration for palliative care:

Duration for surgery:

Adjustment: This value is calculated for those who survive the surgery. To adjust for the POM, it is multiplied by the 100 − POM risk.

Since value is the base for comparison in this model, and it is the product of 2 equally important factors in the formula (severity and duration of symptoms), a factor of 10 was chosen to yield a value of 100, which represents 100% health or absence of symptoms for any duration.

After elimination of normal life expectancy, form the numerator and denominator:

To adjust for surgical outcomes in special circumstances where less than optimal or standard surgical results are expected (eg, in very rare surgeries, limited resource institutions, or suboptimal postoperative surgical care), an optional coefficient R can be added to the numerator (surgical value). This optional coefficient, with values such as 0.8, 0.9 (to degrade the value of surgery) or 1 (standard surgical outcome), adjusts for variability in interinstitutional surgical results or surgeon variability. No coefficient is added to the denominator since palliative care provides minimal differences between clinicians and hospitals. Thus, the final adjusted formula would be as follows:

Example

A 60-year-old patient with a 10% POM risk needs to be allocated to surgical or palliative care. With palliative care, if this patient lived 6 years with average symptoms grade 4, the Vp would be 20; that is, 20% of the normal life value (if he lived 18 years instead without the disease).

Using the formula for calculation of value in each pathway:

With adjustment of 90% survival chance in surgery, 53 × 90% = 48%. In this example, Vs/Vp = 48/20 = 2.4, showing a significant benefit for surgical care. Notably, the unknown value of normal life expectancy is not needed for the calculation of Vs/Vp, since it is the same in both pathways and it is eliminated by calculation in fraction.

Based on this formula, since the duration of surgical symptoms is short, no matter how severe these are, if the potential duration of life after surgery is high (represented by smaller area under the curve in Figure 1), the numerator becomes larger and the value of the surgery grows. For example, if a patient with a 15% risk of POM, which is generally considered inoperable, lives 5 years, as opposed to 2 years with palliative care with mild symptoms (eg 3/10), Vs/Vp would be 2.7, still showing a significant benefit for surgical care.

Discussion

Any surgical intervention is offered with 2 goals in mind, improving QOL and extending DOL. In a high-risk patient, surgery might be declined due to a high risk of POM, and the patient is offered palliative care, which other than providing symptom relief does not change the course of disease and eventually the patient will die due to the untreated disease. In this decision-making method, mostly completed by a care team only, a potential risk of death due to surgery which possibly could cure the patient is traded for immediate survival; however, the symptomatic course ensues until death. This mostly unilateral decision-making process by a care team, which incorporates minimal input from the patient or ignores patient preferences altogether, is based only on POM risk, and roughly includes a single parameter: years of potential life lost (YPLL). YPLL is a measure of premature mortality, and in the setting of surgical intervention, YPLL is the number of years a patient would lose unless a successful surgery were undertaken. Obviously, patients would live longer if a surgery that was intended to save them failed.

In this article, we proposed a simple method to quantify each decision to decide whether to operate or choose surgical care vs palliative care. Since quality and duration of life are both end factors clinicians and patients aspire to in each decision, they can be considered together as the value of each decision. We believe a numerical framework would provide an objective way to assist both the patient at high risk and the care team in the decision-making process.

The 2 parameters we consider are DOL and QOL. DOL, or survival, can be extracted from large-scale data using statistical methods that have been developed to predict survival under various conditions, such as Kaplan-Meier curves. These methods present the chance of survival in percentages in a defined time frame, such as a 5- or 10-year period.

While the DOL is a numerical parameter and quantifiable, the QOL is a more complex entity. This subjective parameter bears multiple definitions, aspects, and categories, and therefore multiple scales for quantification of QOL have been proposed. These scales have been used extensively for the purpose of health determination in health care policy and economic planning. Most scales acknowledge that QOL is multifactorial and includes interrelated aspects such as mental and socioeconomic factors. We have also noticed that QOL is better determined by the palliative care team than surgeons, so including these care providers in the decision-making process might reduce surgeon bias.

Since our purpose here is only to assist with the decision on medical intervention, we focus on physical QOL. Multiple scales are used to assess health-related QOL, such as the Assessment of Quality of Life (AQoL)-8D,⁷ EuroQol-5 Dimension (EQ-5D),⁸ 15D,⁹ and the 36-Item Short Form Survey (SF-36).¹⁰ These complex scales are built for systematic reviews, and they are not practical for a clinical user. To simplify and keep this practical, we define QOL by using the severity or grade of symptoms related to the disease the patient has on a scale of 0 to 10. The severity of symptoms can be easily determined using available scales. An applicable scale for this purpose is the Edmonton Symptom Assessment Scale (ESAS), which has been in use for years and has evolved as a useful tool in the medical field.¹¹

Once DOL and QOL are determined on a 1-10 scale, the multiplied value then provides a product that we consider a value. The highest value hoped for in each decision is the achievement of the best QOL and DOL, a value of 100. In Figure 1, a graphic presentation of value in each decision is best seen as the area under the curve. As shown, a successful surgery, even when accompanied by significant symptoms during initial recovery, has a chance (100 – risk of POM%) to gain a larger area under curve (value) by achieving a longer life with no or fewer symptoms. However, in palliative care, progressing disease and even palliated symptoms with a shorter life expectancy impose a large burden on the patient and a much lower value. Note that in this calculation, life expectancy, which is an important but unpredictable factor, is initially included; however, by ratio comparison, it is eliminated, simplifying the calculation further.

Using this formula in different settings reveals that high-risk surgery has a greater potential to reduce YPLL in the general population. Based on this formula, compared to a surgery with potential to significantly extend DOL, a definite shorter and symptomatic life course with palliative care makes it a significantly less favorable option. In fact, in the cardiovascular field, palliative care has minimal or no effect on natural history, as the mechanism of illness is mechanical, such as occlusion of coronary arteries or valve dysfunction, leading eventually to heart failure and death. In a study by Xu et al, although palliative care reduced readmission rates and improved symptoms on a variety of scales, there was no effect on mortality and QOL in patients with heart failure.¹²

No model in this field has proven to be ideal, and this model bears multiple limitations as well. We have used severity of symptoms as a surrogate for QOL based on the fact that cardiac patients with different pathologies who are untreated will have a common final pathway with development of heart failure symptoms that dictate their QOL. Also, grading QOL is a difficult task at times. Even a model such as QALY, which is one of the most used, is not a perfect model and is not free of problems.⁶ The difference in surgical results and life expectancy between sexes and ethnic groups might be a source of bias in this formula. Also, multiple factors directly and indirectly affect QOL and DOL and create inaccuracies; therefore, making an exact science from an inexact one naturally relies on multiple assumptions. Although it has previously been shown that most POM occurs in a short period of time after cardiac surgery,¹³ long-term complications that potentially degrade QOL are not included in this model. By applying this model, one must assume indefinite economic resources. Moreover, applying a single mathematical model in a biologic system and in the general population has intrinsic shortcomings, and it must overlook many other factors (eg, ethical, legal). For example, it will be hard to justify a failed surgery with 15% risk of POM undertaken to eliminate the severe long-lasting symptoms of a disease, while the outcome of a successful surgery with a 20% risk of POM that adds life and quality would be ignored in the current health care system. Thus, regardless of the significant potential, most surgeons would waive a surgery based solely on the percentage rate of POM, perhaps using other terms such as ”peri-nonoperative mortality.”

Conclusion

We have proposed a simple and practical formula for decision making regarding surgical vs palliative care in high-risk patients. By assigning a value that is composed of QOL and DOL in each pathway and including the risk of POM, a ratio of values provides a numerical estimation that can be used to show preference over a specific decision. An advantage of this formula, in addition to presenting an arithmetic value that is easier to understand, is that it can be used in shared decision making with patients. We emphasize that this model is only a preliminary concept at this time and has not been tested or validated for clinical use. Validation of such a model will require extensive work and testing within a large-scale population. We hope that this article will serve as a starting point for the development of other models, and that this formula will become more sophisticated with fewer limitations through larger multidisciplinary efforts in the future.

Corresponding author: Rabin Gerrah, MD, Good Samaritan Regional Medical Center, 3640 NW Samaritan Drive, Suite 100B, Corvallis, OR 97330; rgerrah@stanford.edu.

Disclosures: None reported.