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We have written routinely about the positive impact of implementing an electronic health record, citing potential improvements in areas such as charge capture, data sharing, and population management. In an attempt to be balanced, we’ve also discussed the financial implications and the risks of decreased productivity and provider frustration, among others. One area that we have not focused on – but which has been attracting increasingly more attention – is that of the advantages and limitations of Clinical Decision Support Systems (CDSSs).
CDSSs are tools that add evidence-based clinical intelligence to patient care, providing assistance to the provider as he or she treats patients and makes decisions about their management. A simple example of this would be an alert, reminding a physician to provide an immunization to age-appropriate patients while seeing them in the office. Some EHRs ship with this capability built-in and ready for deployment "right out of the box," while others completely lack real-decision support. Most commonly, however, an EHR will have the capability to provide support but rely heavily on end-user customization prior to implementation. The question that many are beginning to ask is how using a clinical decision support system will ultimately affect patient outcomes.
The promise and liability of clinical intelligence
There is no question that the medical community has accepted the concept of guideline-based workflows and the importance of evidence-based medicine at the point of care. More recently, though, several studies have begun to look at how CDSS tools that are packaged into EHRs have affected care delivery. Surprisingly, the results are inconsistent; while many studies have demonstrated the benefits of decision support, others have not shown impressive changes in patient outcomes.
Findings from a review of 100 studies comparing the outcomes in care provided with and without a CDSS showed that 64% of the studies demonstrated improvements in practitioner performance when using a Clinical Decision Support System. While the specific systems varied in type and purpose, improvements in performance were "associated with CDSSs that automatically prompted users," compared with those "requiring users to activate the system," (JAMA 2005;293:1223-38).
Similar results were found in a multidisciplinary randomized trial pin which investigators analyzed data from 21 centers and demonstrated that "computerized decision support increased concordance with guideline-recommended therapeutic decisions" for numerous treatment options and "reduced cases of both overtreatment and undertreatment" (BMJ 2009;338:b1440 [doi:10.1136/bmj.b1440]).
But not all of the studies have been so optimistic. Findings from a more recent study showed that there is little benefit to having a CDSS in place. Using survey data collected from over 250,000 ambulatory patient visits (sourced from the National Ambulatory Medical Care Survey), they discovered that only 1 of 20 quality indicators proved better in the group of patients treated using EHRs with a CDSS in place, compared with those treated without decision support. The investigators offered little explanation for these unexpected results, but they did cite some limitations in their methods and theorized that the value of current support systems may be minimal in the absence of standardization and better quality control (Arch. Intern. Med. 2011;171:897-903).
Searching for help
To meet certification for meaningful use, electronic records are required to have some minimal CDSS functionality available from Day 1. But in our experience with most products, the depth and breadth of this built-in support is sorely lacking. For some practitioners who simply view the EMR as a more complicated way of documenting progress notes and telephone calls, this might not seem like a big deal. After all, the world of paper offered no clinical intelligence to speak of. But for others hoping to realize the true promises of health information technology, high-quality decision support may be essential.
It is again important to point out that the usefulness of clinical decision support systems is typically limited by the EHR itself, so it’s critical to start investigating CDSS capability when first selecting an EHR. We would encourage everyone to request to see a demonstration of what – if any – decision support is present in the EHRs they are considering, and ask a lot of questions about how the information is accessed and kept current. Does the product have a standard toolset based on outdated practice suggestions or is it updated as new guidelines are published and research is released? Is the information customizable to meet the needs of the implementation, or is it a "one-size-fits-all" solution? Finally, is the information passive or active? In other words, does the provider need to go searching for the support, or is the software smart enough to offer support when appropriate in the form of an "alert" or "pop-up"?
A tale of art and science
When chess champion Gary Kasparov defeated IBM’s Deep Blue Supercomputer back in 1996, people around the globe shared in a warm feeling of vindication. More than a simple win, Kasparov’s victory proved that humans still had the advantage over machines. In the same way, it is possible to find the data questioning the value of CDSSs oddly reassuring. But the irony of history reminds us not to get comfortable in our assertions; just 1 year later, after extensive enhancements, Deep Blue returned to defeat Kasparov in a devastating rematch. We suggest viewing this irony as instructive; if one accepts – as we do unequivocally – the value of evidence-based medicine, one must also accept that the right decision support delivered in a timely fashion will ultimately lead to better care and improved clinical outcomes.
Dr. Skolnik is associate director of the family medicine residency program at Abington (Pa.) Memorial Hospital and professor of family and community medicine at Temple University, Philadelphia. He is also editor in chief of Redi-Reference, a software company that creates medical handheld references. Dr. Notte practices family medicine and health care informatics for Abington Memorial Hospital. They are partners in EHR Practice Consultants, helping practices move to EHR systems. Contact them at info@ehrpc.com.
We have written routinely about the positive impact of implementing an electronic health record, citing potential improvements in areas such as charge capture, data sharing, and population management. In an attempt to be balanced, we’ve also discussed the financial implications and the risks of decreased productivity and provider frustration, among others. One area that we have not focused on – but which has been attracting increasingly more attention – is that of the advantages and limitations of Clinical Decision Support Systems (CDSSs).
CDSSs are tools that add evidence-based clinical intelligence to patient care, providing assistance to the provider as he or she treats patients and makes decisions about their management. A simple example of this would be an alert, reminding a physician to provide an immunization to age-appropriate patients while seeing them in the office. Some EHRs ship with this capability built-in and ready for deployment "right out of the box," while others completely lack real-decision support. Most commonly, however, an EHR will have the capability to provide support but rely heavily on end-user customization prior to implementation. The question that many are beginning to ask is how using a clinical decision support system will ultimately affect patient outcomes.
The promise and liability of clinical intelligence
There is no question that the medical community has accepted the concept of guideline-based workflows and the importance of evidence-based medicine at the point of care. More recently, though, several studies have begun to look at how CDSS tools that are packaged into EHRs have affected care delivery. Surprisingly, the results are inconsistent; while many studies have demonstrated the benefits of decision support, others have not shown impressive changes in patient outcomes.
Findings from a review of 100 studies comparing the outcomes in care provided with and without a CDSS showed that 64% of the studies demonstrated improvements in practitioner performance when using a Clinical Decision Support System. While the specific systems varied in type and purpose, improvements in performance were "associated with CDSSs that automatically prompted users," compared with those "requiring users to activate the system," (JAMA 2005;293:1223-38).
Similar results were found in a multidisciplinary randomized trial pin which investigators analyzed data from 21 centers and demonstrated that "computerized decision support increased concordance with guideline-recommended therapeutic decisions" for numerous treatment options and "reduced cases of both overtreatment and undertreatment" (BMJ 2009;338:b1440 [doi:10.1136/bmj.b1440]).
But not all of the studies have been so optimistic. Findings from a more recent study showed that there is little benefit to having a CDSS in place. Using survey data collected from over 250,000 ambulatory patient visits (sourced from the National Ambulatory Medical Care Survey), they discovered that only 1 of 20 quality indicators proved better in the group of patients treated using EHRs with a CDSS in place, compared with those treated without decision support. The investigators offered little explanation for these unexpected results, but they did cite some limitations in their methods and theorized that the value of current support systems may be minimal in the absence of standardization and better quality control (Arch. Intern. Med. 2011;171:897-903).
Searching for help
To meet certification for meaningful use, electronic records are required to have some minimal CDSS functionality available from Day 1. But in our experience with most products, the depth and breadth of this built-in support is sorely lacking. For some practitioners who simply view the EMR as a more complicated way of documenting progress notes and telephone calls, this might not seem like a big deal. After all, the world of paper offered no clinical intelligence to speak of. But for others hoping to realize the true promises of health information technology, high-quality decision support may be essential.
It is again important to point out that the usefulness of clinical decision support systems is typically limited by the EHR itself, so it’s critical to start investigating CDSS capability when first selecting an EHR. We would encourage everyone to request to see a demonstration of what – if any – decision support is present in the EHRs they are considering, and ask a lot of questions about how the information is accessed and kept current. Does the product have a standard toolset based on outdated practice suggestions or is it updated as new guidelines are published and research is released? Is the information customizable to meet the needs of the implementation, or is it a "one-size-fits-all" solution? Finally, is the information passive or active? In other words, does the provider need to go searching for the support, or is the software smart enough to offer support when appropriate in the form of an "alert" or "pop-up"?
A tale of art and science
When chess champion Gary Kasparov defeated IBM’s Deep Blue Supercomputer back in 1996, people around the globe shared in a warm feeling of vindication. More than a simple win, Kasparov’s victory proved that humans still had the advantage over machines. In the same way, it is possible to find the data questioning the value of CDSSs oddly reassuring. But the irony of history reminds us not to get comfortable in our assertions; just 1 year later, after extensive enhancements, Deep Blue returned to defeat Kasparov in a devastating rematch. We suggest viewing this irony as instructive; if one accepts – as we do unequivocally – the value of evidence-based medicine, one must also accept that the right decision support delivered in a timely fashion will ultimately lead to better care and improved clinical outcomes.
Dr. Skolnik is associate director of the family medicine residency program at Abington (Pa.) Memorial Hospital and professor of family and community medicine at Temple University, Philadelphia. He is also editor in chief of Redi-Reference, a software company that creates medical handheld references. Dr. Notte practices family medicine and health care informatics for Abington Memorial Hospital. They are partners in EHR Practice Consultants, helping practices move to EHR systems. Contact them at info@ehrpc.com.
We have written routinely about the positive impact of implementing an electronic health record, citing potential improvements in areas such as charge capture, data sharing, and population management. In an attempt to be balanced, we’ve also discussed the financial implications and the risks of decreased productivity and provider frustration, among others. One area that we have not focused on – but which has been attracting increasingly more attention – is that of the advantages and limitations of Clinical Decision Support Systems (CDSSs).
CDSSs are tools that add evidence-based clinical intelligence to patient care, providing assistance to the provider as he or she treats patients and makes decisions about their management. A simple example of this would be an alert, reminding a physician to provide an immunization to age-appropriate patients while seeing them in the office. Some EHRs ship with this capability built-in and ready for deployment "right out of the box," while others completely lack real-decision support. Most commonly, however, an EHR will have the capability to provide support but rely heavily on end-user customization prior to implementation. The question that many are beginning to ask is how using a clinical decision support system will ultimately affect patient outcomes.
The promise and liability of clinical intelligence
There is no question that the medical community has accepted the concept of guideline-based workflows and the importance of evidence-based medicine at the point of care. More recently, though, several studies have begun to look at how CDSS tools that are packaged into EHRs have affected care delivery. Surprisingly, the results are inconsistent; while many studies have demonstrated the benefits of decision support, others have not shown impressive changes in patient outcomes.
Findings from a review of 100 studies comparing the outcomes in care provided with and without a CDSS showed that 64% of the studies demonstrated improvements in practitioner performance when using a Clinical Decision Support System. While the specific systems varied in type and purpose, improvements in performance were "associated with CDSSs that automatically prompted users," compared with those "requiring users to activate the system," (JAMA 2005;293:1223-38).
Similar results were found in a multidisciplinary randomized trial pin which investigators analyzed data from 21 centers and demonstrated that "computerized decision support increased concordance with guideline-recommended therapeutic decisions" for numerous treatment options and "reduced cases of both overtreatment and undertreatment" (BMJ 2009;338:b1440 [doi:10.1136/bmj.b1440]).
But not all of the studies have been so optimistic. Findings from a more recent study showed that there is little benefit to having a CDSS in place. Using survey data collected from over 250,000 ambulatory patient visits (sourced from the National Ambulatory Medical Care Survey), they discovered that only 1 of 20 quality indicators proved better in the group of patients treated using EHRs with a CDSS in place, compared with those treated without decision support. The investigators offered little explanation for these unexpected results, but they did cite some limitations in their methods and theorized that the value of current support systems may be minimal in the absence of standardization and better quality control (Arch. Intern. Med. 2011;171:897-903).
Searching for help
To meet certification for meaningful use, electronic records are required to have some minimal CDSS functionality available from Day 1. But in our experience with most products, the depth and breadth of this built-in support is sorely lacking. For some practitioners who simply view the EMR as a more complicated way of documenting progress notes and telephone calls, this might not seem like a big deal. After all, the world of paper offered no clinical intelligence to speak of. But for others hoping to realize the true promises of health information technology, high-quality decision support may be essential.
It is again important to point out that the usefulness of clinical decision support systems is typically limited by the EHR itself, so it’s critical to start investigating CDSS capability when first selecting an EHR. We would encourage everyone to request to see a demonstration of what – if any – decision support is present in the EHRs they are considering, and ask a lot of questions about how the information is accessed and kept current. Does the product have a standard toolset based on outdated practice suggestions or is it updated as new guidelines are published and research is released? Is the information customizable to meet the needs of the implementation, or is it a "one-size-fits-all" solution? Finally, is the information passive or active? In other words, does the provider need to go searching for the support, or is the software smart enough to offer support when appropriate in the form of an "alert" or "pop-up"?
A tale of art and science
When chess champion Gary Kasparov defeated IBM’s Deep Blue Supercomputer back in 1996, people around the globe shared in a warm feeling of vindication. More than a simple win, Kasparov’s victory proved that humans still had the advantage over machines. In the same way, it is possible to find the data questioning the value of CDSSs oddly reassuring. But the irony of history reminds us not to get comfortable in our assertions; just 1 year later, after extensive enhancements, Deep Blue returned to defeat Kasparov in a devastating rematch. We suggest viewing this irony as instructive; if one accepts – as we do unequivocally – the value of evidence-based medicine, one must also accept that the right decision support delivered in a timely fashion will ultimately lead to better care and improved clinical outcomes.
Dr. Skolnik is associate director of the family medicine residency program at Abington (Pa.) Memorial Hospital and professor of family and community medicine at Temple University, Philadelphia. He is also editor in chief of Redi-Reference, a software company that creates medical handheld references. Dr. Notte practices family medicine and health care informatics for Abington Memorial Hospital. They are partners in EHR Practice Consultants, helping practices move to EHR systems. Contact them at info@ehrpc.com.
