Affiliations
Department of Pediatrics, Children's Mercy Hospitals and Clinics, University of Missouri–Kansas City School of Medicine
Given name(s)
Ashley
Family name
Daly
Degrees
MD

In‐Hospital Asthma Resource Utilization

Article Type
Article
Changed
Sun, 05/21/2017 - 13:26
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Childhood obesity and in‐hospital asthma resource utilization
Author(s)
Jessica Bettenhausen, MD
Henry Puls, MD
Mary Ann Queen, MD
Christina Peacock, MD
Stephanie Burrus, DO
Christopher Miller, MD
Ashley Daly, MD
Jeffrey D. Colvin, MD, JD

Pediatric hospitalizations for obesity‐related conditions have doubled in the last decade, mirroring the trend of higher levels of childhood obesity in the United States.[1, 2, 3] Recent studies have demonstrated worsened pediatric in‐hospital outcomes, including mortality and increased resource utilization, for children with obesity across a range of diagnoses.[4, 5, 6, 7, 8, 9, 10] Although the mechanisms driving the association between obesity and in‐hospital outcomes are not fully known, for asthma it is believed that adipocytes expressing inflammatory markers create a low level of systemic inflammation, thereby increasing the severity of allergic‐type illnesses and decreasing the response to anti‐inflammatory medications, such as steroids.[11, 12, 13, 14, 15, 16, 17, 18] The relationship of obesity and in‐hospital asthma outcomes is of particular interest because status asthmaticus is the most common reason for admission in children aged 3 to 12 years, accounting for approximately 150,000 admissions (7.4% of all hospitalizations for children and adolescents) and $835 million in hospital costs annually.[19]

Few prior studies have examined the association of obesity and asthma outcomes in the in‐hospital setting. The studies examining this association have found patients with obesity to have a longer hospital length of stay (LOS) and increased hospital costs.[8, 9, 20] Obesity has also been associated with increased respiratory treatments and supplemental oxygen requirements.[20] Associations between obesity and admission rates from the emergency department (ED) for pediatric asthma have been inconsistent.[21, 22] Most of these prior studies had several limitations in identifying patients with obesity, including using weight‐for‐age percentiles or International Classification of Diseases, Ninth Revision (ICD‐9) codes, rather than body mass index (BMI) percentile for age, the currently recommended method.[23, 24, 25] Methods other than BMI have the potential to either underestimate obesity (ie, ICD‐9 codes)[26] or to confound weight with adiposity (ie, weight‐for‐age percentiles),[27] thereby skewing the primary exposure of interest.

In the present study, we sought to examine associations between obesity and in‐hospital outcomes for pediatric status asthmaticus using the currently endorsed method for identifying obesity in children, BMI percentile for age.[23, 24, 25] The outcomes of interest included a broad range of in‐hospital measures, including resource utilization (medication and radiology use), readmission rates, billed charges, and LOS. We hypothesize that obesity, due to its proinflammatory state, would result in increased LOS, increased resource utilization, and an increased readmission rate for children admitted with status asthmaticus.

METHODS

Data Sources

Data for this retrospective cross‐sectional study were obtained from 2 sources. First, we queried the Pediatric Health Information System (PHIS) administrative database, which draws information from multiple children's hospitals to identify patients at our 2 institutions of interest who met study criteria. The PHIS database also was used to collect patient demographic data. PHIS is an administrative database operated by Children's Hospital Association (Overland Park, KS) containing clinical and billing data from 43 tertiary care, freestanding children's hospitals, including data on 41 ICD‐9 diagnoses, billed charges, and LOS. Based on the primary diagnosis, PHIS assigns each discharge to an All Patient Refined‐Diagnosis Related Group (APR‐DRG v.24) (3M Health information Systems, St. Paul, MN). APR‐DRGs allow similar diagnoses to be grouped together.[28, 29] PHIS also uses ICD‐9 codes to identify patients with a complex chronic condition (CCC).[30, 31] CCCs are those conditions that can be reasonably expected to last at least 12 months (unless death intervenes) and to involve either several different organ systems or one system severely enough to require specialty pediatric care and probably some period of hospitalization in a tertiary care center.[30, 31] PHIS data quality is ensured through a collaborative effort of the participating hospitals, the Children's Hospital Association, and Truven Healthcare.

Second, standardized chart reviews were then performed to collect clinical data not found in PHIS: BMI, LOS in hours, and medications administered, including total number of albuterol treatments administered during both the admission and the associated preceding ED visit.

Study Setting and Participants

All admissions examined in this study were at Children's Mercy Hospitals. Children's Mercy Hospitals includes 2 separate hospitals: 1 hospital is a 354‐bed academic, tertiary care freestanding children's hospital located in Kansas City, Missouri; a second, smaller, 50‐bed freestanding hospital is located in Overland Park, Kansas. Both hospitals have pediatric emergency departments. Inclusion criteria included patients aged 5 to 17 years discharged for status asthmaticus (APR‐DRG 141) at Children's Mercy Hospital from October 1, 2011 to September 30, 2012, with a recorded BMI during the admission or within 30 days of the admission. Patients between the ages of 2 and 5 years old were not included because of the incidence of viral‐induced wheezing in this age group and therefore possible miscoding of the asthma diagnosis. Exclusion criteria included a concurrent diagnosis of a CCC or bacterial pneumonia because these conditions could alter LOS, resource utilization, and readmission rates independent of the subject's status asthmaticus. In addition, to account for differences in the amount of treatment given in the pre‐inpatient setting, patients not initially treated through the hospital's ED were excluded. For patients with multiple admissions during the study period for the same diagnosis, only the index admission was examined. The institutional review board at Children's Mercy Hospital approved this study with waiver of informed consent.

Study Definitions

BMI percentile for age was used as both a continuous and categorical predictor variable. As a categorical variable it was divided into 4 categories: underweight (BMI <5%), normal weight (BMI 5%84%), overweight (BMI 85%94%), and obese (BMI 95%).[23] Race was categorized non‐Hispanic white, non‐Hispanic black, and other. Other included Asian, Pacific Islander, American Indian, and other. Ethnicity was categorized as Hispanic and non‐Hispanic. Insurance categories included private (commercial or TRICARE), public (Medicaid and Title V), and other (uninsured, self‐pay, and other). Adjusted billed charges were calculated for each hospitalization. Adjusted billed charges are the billed charges adjusted by the US Centers of Medicare and Medicaid Services' price/wage index for the study site's location.[32, 33]

To compare albuterol of different delivery methods, albuterol equivalents were calculated. Based upon prior research demonstrating equal efficacy between albuterol administered by nebulizer and metered‐dose inhaler (MDI),[34] every 2.5 mg of albuterol administered by nebulizer was treated as equivalent to 2 sprays of albuterol (90 g/spray) administered by MDI. Therefore, albuterol 2.5 mg nebulized and 2 sprays of albuterol (90 g/spray) were each defined as 1 albuterol equivalent. To compare continuous administration of nebulized albuterol with intermittent administration of albuterol, the total milligrams of continuously nebulized albuterol were examined. Per protocol at the study site, 10 mg per hour of continuous albuterol are administered for patients 5 years and younger and, for children 6 years and older, 15 mg per hour of continuous albuterol are administered. Based upon milligrams of albuterol nebulized, 5‐year‐old subjects receiving an hour of continuous albuterol would equal 4 albuterol equivalents (or 4 treatments of nebulized albuterol 2.5 mg/treatment or 4 treatments of albuterol 90 g/spray 2 sprays/treatment); for patients 6 years and older, an hour of continuous albuterol would equal 6 albuterol equivalents (or 6 treatments of nebulized albuterol 2.5 mg/treatment or 6 treatments of albuterol 90 g/spray 2 sprays/treatment). The variable total albuterol was then created to include albuterol equivalents delivered by metered dose inhaler and as both single and continuous nebulized treatments.

Main Exposure

The main exposure of interest was BMI percentile for age.

Outcome Measures

The main outcome measure was inpatient LOS measured in hours. Secondary outcome measures included the total albuterol (in the inpatient setting as well as combined inpatient and ED settings) and the administration of intravenous IV fluids and intramuscular (IM) or IV systemic steroids. Other secondary measures included readmission for status asthmaticus during the study period, adjusted billed charges, and inpatient chest radiograph utilization.

Statistical Analyses

We summarized categorical variables with frequencies and percentages, and used [2] test across BMI categories. The non‐normal distribution of continuous dependent variables (LOS, number of albuterol treatments, billed charges) were summarized with medians and interquartile ranges (IQRs). Kruskal‐Wallis test was used to examine outcomes across BMI categories. For regression models, BMI percentile for age was divided into deciles and treated as a continuous predictor. Factors used in the regression models included age, gender, race, ethnicity, and insurance. Total albuterol received in the ED was also included in the model to adjust for differences in the amount of treatment received prior to admission. Incidence rate ratios were created using Poisson regression for continuous outcomes (LOS, billed charges, and number of albuterol equivalent treatments administered), and odds ratios were created using logistic regression for dichotomous outcomes. All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM, Armonk, NY), and P values <0.05 were considered statistically significant.

RESULTS

Patient Characteristics

Of 788 patients admitted for status asthmaticus during the study period, 518 (65.7%) met inclusion criteria; 42 (5.3%) did not meet inclusion criteria due to lack of a documented BMI (Table 1). Most patients were normal weight (59.7%). Approximately one‐third (36.7%) were either overweight or obese. The median age was 8 years, with patients with obesity being significantly older than underweight patients (9 vs 7.5 years, P<0.001). The majority of patients were black/African American (56.9%) and non‐Hispanic (88.6%). The percentage of patients who were obese was higher in patients of other race (29.3%) than whites (20.2%) or blacks (16.3%) (P<0.05). Patients of Hispanic ethnicity had a higher rate of obesity compared to non‐Hispanic patients (37.3% vs 17.4%, P<0.01). There were no differences in BMI categories for insurance.

Patient Characteristics by Body Mass Index Category
Patient CharacteristicsTotalCategory of Body Mass Index Percentile for Age
UnderweightNormalOverweightObeseP*

  • NOTE: Abbreviations: IQR, interquartile range. *Categorical variables were compared by 2 test, and continuous variables were compared by Kruskall‐Wallis test.

Total patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7) 
Age, y, median (IQR)8 (611)7.5 (5.89)8 (610)8 (610)9 (712)<0.001
Gender, n (%)      
Male30912 (3.9)184 (59.5)46 (14.9)67 (21.7)0.27
Female2096 (2.9)126 (60.3)42 (20.1)35 (16.7) 
Race, n (%)      
Non‐Hispanic white1248 (6.5)76 (61.3)15 (12.1)25 (20.2)0.021
Non‐Hispanic black2957 (2.4)182 (61.7)58 (19.7)48 (16.3) 
Other993 (3.0)52 (52.5)15 (15.2)29 (29.3) 
Ethnicity, n (%)      
Hispanic591 (1.7)25 (42.4)11 (18.6)22 (37.3)0.002
Non‐Hispanic45917 (3.7)285 (62.1)77 (16.8)80 (17.4) 
Insurance, n (%)      
Private16310 (6.1)97 (59.5)28 (17.2)28 (17.2)0.48
Public3137 (2.2)190 (60.7)51 (16.3)65 (20.8) 
Other421 (2.4)23 (54.8)9 (21.4)9 (21.4) 

LOS and Resource Utilization

The median LOS for all patients was approximately 1 day (Table 2). The median number of albuterol treatments in the inpatient setting was 14 (IQR, 824). When albuterol treatments given in the ED were included, the median number of treatments increased to 38 (IQR, 2848). Approximately one‐half of patients required supplemental oxygen, one‐third received IV fluids, and one‐fifth received either IV or IM steroids (with all but 1.6% of the remaining patients receiving oral steroids). Less than 5% of the study population received magnesium sulfate, epinephrine, required intensive care unit (ICU) admission, or were readmitted for status asthmaticus within 30 days. Approximately 15% of patients received a chest radiograph. The median adjusted billed charge was approximately $7,000. There were no differences in any of these outcomes by BMI category (P>0.05).

Resource Utilization, Readmissions, Length of Stay, and Billed Charges for In‐Hospital Status Asthmaticus by Body Mass Index Category
 TotalBody Mass Index Category
UnderweightNormalOverweightObese

  • NOTE: Abbreviations: ICU, intensive care unit; IM, intramuscular; IQR, interquartile range; IV, intravenous. *All differences between body mass index categories were nonsignificant (P>0.05).

Total Patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7)
LOS, h, median (IQR)26 (1841)41 (19.560.5)26 (1841)26 (19.2540)31 (1942)
Inpatient albuterol equivalents, median (IQR)14(824)19 (9.528)14 (824)14 (8.522)16 (824)
Total albuterol equivalents, median (IQR)38 (2848)34 (2734)36 (2848)37 (2849.5)40 (3052)
Adjusted billed charges, $, median (IQR)6,999.5 (52929258)7,457 (56048536)6876 (52379390)7056 (54099061)7198 (53319306)
All readmits, n (%)44 (8.5)2 (11.1)29 (9.4)7 (8.0)6 (5.9)
Readmits within 30 days, n (%)11 (2.1)1 (5.6)7 (2.3)1 (1.1)2 (2.0)
ICU admissions, n (%)24 (4.6)0 (0)13 (4.2)7 (8.0)4 (3.9)
Chest radiograph, n (%)64 (12.4)5 (27.8)34 (11.0)12 (13.6)13 (12.7)
Oxygen, n (%)255 (49.2)11 (61.1)157 (50.6)42 (47.7)45 (44.1)
IV/IM steroid, n (%)93 (18.0)2 (11.1)53 (17.1)18 (20.5)20 (19.6)
Epinephrine, n (%)2 (0.4)0 (0)2 (0.6)0 (0)0 (0)
Magnesium, n (%)15 (2.9)0 (0)8 (2.6)3 (3.4)4 (3.9)
IV fluids, n (%)152 (29.3)4 (22.2)85 (27.4)31 (35.2)32 (31.4)

Multivariable Results

After adjusting for age, gender, race, ethnicity, and insurance, the decile of BMI percentile for age showed a small negative association with LOS. Specifically, for each decile increase for BMI percentile for age, LOS decreased by approximately 2%. BMI percentile for age was not associated with other measures of resource utilization including total albuterol use, adjusted billed charges, readmission, ICU care, receipt of supplemental oxygen or a chest radiograph, IV fluids, or other medications (IV/IM steroids, epinephrine, or magnesium sulfate).

DISCUSSION

Our study suggests that the decile of BMI percentile for age is inversely associated with LOS but did not have a clinically meaningful effect. Secondary measures, such as total albuterol needs and adjusted billed charges, did not show an association with BMI percentile for age. There were also no associations between BMI percentile for age and other resource utilization outcomes.

Our findings differ from previous studies examining in‐hospital status asthmaticus in children who are overweight or obese. In addition, the present study was able to adjust for therapies received prior to admission. Carroll et al. demonstrated an increased LOS of approximately 3 days for overweight or obese asthmatics admitted to the ICU with status asthmaticus as well as increased duration of supplemental oxygen, continuous albuterol, and intravenous steroids.[20] It is possible that differences in methodology (ie, weight‐for‐age percentile vs BMI percentile for age, inclusion of ED treatments), different thresholds for treatment of status asthmaticus outside the ICU, or differences in patient populations studied (ie, only ICU patients vs all in‐hospital patients) explain the difference between their findings and the present study. The present study's use of BMI percentile for age follows current recommendations for classifying a patient as obese or overweight.[23, 24, 25] However, the use of classifications other than BMI percentile for age would tend to bias toward the null hypothesis, whereas in Carroll's study children who were overweight or obese had increased resource utilization. Additionally, in the time frame between this publication and the current study, many hospitals worked to standardize asthma hospitalizations by creating weaning protocols for albuterol, thereby decreasing LOS for all asthmatics, which may also affect the differences in LOS between groups of obese and nonobese patients.[35]

Woolford et al. found approximately a one‐half‐day increase in LOS and $2,000 higher mean charges for patients admitted with status asthmaticus and a secondary diagnosis of obesity.[8, 9] Study location and differing methods for defining obesity may account for the discrepancy between Woolford's findings and our study. We examined children admitted to the inpatient floor of a tertiary care children's hospital compared to Woolford et al.'s examination of pediatric patients admitted to all hospitals via the Kids' Inpatient Database (Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality). That study also relied on the coding of obesity as an ICD‐9 diagnosis, rather than examining the BMI of all admitted patients. Previous research has demonstrated that relying on a coded diagnosis of obesity is not as sensitive as measurement.[26] By relying on ICD‐9 diagnosis coding, only patients with very high BMIs may be diagnosed with obesity during the admission and therefore only associations between very high BMI and status asthmaticus will be examined.

There are several limitations to our findings. First, our study was limited to a single, tertiary care children's hospital and may not be generalizable to other hospitals. Our hospital standardizes the treatment of inpatient status asthmatics by formation of a respiratory care plan, involving interval scoring of respiratory symptoms and automatic spacing of albuterol treatments. This likely minimizes physician‐to‐physician variation. Second, we included only those patients who were initially treated within the ED associated with the admitting hospital to minimize the effects of timing for treatments prior to admittance. This excluded those patients first cared for by their primary care physician or by an outlying ED. Therefore, our sample may be biased toward a study population less connected to a medical home and therefore possibly poorer asthma control. Third, to utilize the most accurate method to define obesity, we excluded approximately 5% of eligible patients because BMI was unavailable. This may have included children with more severe asthma symptoms, as a height measurement may have been deferred due to their higher acuity. Asthma severity or chronicity would be associated with our outcomes of interest. However, we were unable to collect reliable data on severity or chronicity. Finally, to measure the amount of total albuterol needed by a patient during the ED and inpatient admissions, albuterol treatments delivered by MDI, nebulizer, or continuously were converted into total albuterol. Although based upon total milligram dosing and studies comparing routes of albuterol administration,[34] the validity of this conversion is unknown.

CONCLUSION

Although BMI percentile for age is inversely associated with LOS for in‐hospital pediatric status asthmaticus, the impact of BMI on this outcome likely is not clinically meaningful. Future investigations should examine other elements of BMI and in‐hospital status asthmaticus, such as any associations between BMI and admission rates.

Acknowledgements

The authors offer their appreciation to their research assistant, Amy Lee, for her support and dedication to this project.

Disclosures

Internal funds from Children's Mercy Hospital and Clinics supported the conduct of this work. The authors report no conflicts of interest.

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Supplementary Information (1)
References
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  11. Forno E, Lescher R, Strunk R, Weiss S, Fuhlbrigge A, Celedon JC. Decreased response to inhaled steroids in overweight and obese asthmatic children. J Allergy Clin Immunol. 2011;127(3):741–749.
  12. Sutherland ER, Goleva E, Strand M, Beuther DA, Leung DYM. Body mass and glucocorticoid response in asthma. Am J Respir Crit Care Med. 2008;178(7):682–687.
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  16. Camargo CA, Boulet L‐P, Sutherland ER, et al. Body mass index and response to asthma therapy: fluticasone propionate/salmeterol versus montelukast. J Asthma. 2010;47(1):76–82.
  17. Dixon AE, Shade DM, Cohen RI, et al. Effect of obesity on clinical presentation and response to treatment in asthma. J Asthma. 2006;43(7):553–558.
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Article PDF
jhm2296.pdf
Issue
Journal of Hospital Medicine - 10(3)
Publications
Journal of Hospital Medicine
Page Number
160-164
Sections
Original Research
Author(s)
Jessica Bettenhausen, MD
Henry Puls, MD
Mary Ann Queen, MD
Christina Peacock, MD
Stephanie Burrus, DO
Christopher Miller, MD
Ashley Daly, MD
Jeffrey D. Colvin, MD, JD
Author(s)
Jessica Bettenhausen, MD
Henry Puls, MD
Mary Ann Queen, MD
Christina Peacock, MD
Stephanie Burrus, DO
Christopher Miller, MD
Ashley Daly, MD
Jeffrey D. Colvin, MD, JD
Files
Supplementary Information (1)
Files
Supplementary Information (1)
Article PDF
jhm2296.pdf
Article PDF
jhm2296.pdf

Pediatric hospitalizations for obesity‐related conditions have doubled in the last decade, mirroring the trend of higher levels of childhood obesity in the United States.[1, 2, 3] Recent studies have demonstrated worsened pediatric in‐hospital outcomes, including mortality and increased resource utilization, for children with obesity across a range of diagnoses.[4, 5, 6, 7, 8, 9, 10] Although the mechanisms driving the association between obesity and in‐hospital outcomes are not fully known, for asthma it is believed that adipocytes expressing inflammatory markers create a low level of systemic inflammation, thereby increasing the severity of allergic‐type illnesses and decreasing the response to anti‐inflammatory medications, such as steroids.[11, 12, 13, 14, 15, 16, 17, 18] The relationship of obesity and in‐hospital asthma outcomes is of particular interest because status asthmaticus is the most common reason for admission in children aged 3 to 12 years, accounting for approximately 150,000 admissions (7.4% of all hospitalizations for children and adolescents) and $835 million in hospital costs annually.[19]

Few prior studies have examined the association of obesity and asthma outcomes in the in‐hospital setting. The studies examining this association have found patients with obesity to have a longer hospital length of stay (LOS) and increased hospital costs.[8, 9, 20] Obesity has also been associated with increased respiratory treatments and supplemental oxygen requirements.[20] Associations between obesity and admission rates from the emergency department (ED) for pediatric asthma have been inconsistent.[21, 22] Most of these prior studies had several limitations in identifying patients with obesity, including using weight‐for‐age percentiles or International Classification of Diseases, Ninth Revision (ICD‐9) codes, rather than body mass index (BMI) percentile for age, the currently recommended method.[23, 24, 25] Methods other than BMI have the potential to either underestimate obesity (ie, ICD‐9 codes)[26] or to confound weight with adiposity (ie, weight‐for‐age percentiles),[27] thereby skewing the primary exposure of interest.

In the present study, we sought to examine associations between obesity and in‐hospital outcomes for pediatric status asthmaticus using the currently endorsed method for identifying obesity in children, BMI percentile for age.[23, 24, 25] The outcomes of interest included a broad range of in‐hospital measures, including resource utilization (medication and radiology use), readmission rates, billed charges, and LOS. We hypothesize that obesity, due to its proinflammatory state, would result in increased LOS, increased resource utilization, and an increased readmission rate for children admitted with status asthmaticus.

METHODS

Data Sources

Data for this retrospective cross‐sectional study were obtained from 2 sources. First, we queried the Pediatric Health Information System (PHIS) administrative database, which draws information from multiple children's hospitals to identify patients at our 2 institutions of interest who met study criteria. The PHIS database also was used to collect patient demographic data. PHIS is an administrative database operated by Children's Hospital Association (Overland Park, KS) containing clinical and billing data from 43 tertiary care, freestanding children's hospitals, including data on 41 ICD‐9 diagnoses, billed charges, and LOS. Based on the primary diagnosis, PHIS assigns each discharge to an All Patient Refined‐Diagnosis Related Group (APR‐DRG v.24) (3M Health information Systems, St. Paul, MN). APR‐DRGs allow similar diagnoses to be grouped together.[28, 29] PHIS also uses ICD‐9 codes to identify patients with a complex chronic condition (CCC).[30, 31] CCCs are those conditions that can be reasonably expected to last at least 12 months (unless death intervenes) and to involve either several different organ systems or one system severely enough to require specialty pediatric care and probably some period of hospitalization in a tertiary care center.[30, 31] PHIS data quality is ensured through a collaborative effort of the participating hospitals, the Children's Hospital Association, and Truven Healthcare.

Second, standardized chart reviews were then performed to collect clinical data not found in PHIS: BMI, LOS in hours, and medications administered, including total number of albuterol treatments administered during both the admission and the associated preceding ED visit.

Study Setting and Participants

All admissions examined in this study were at Children's Mercy Hospitals. Children's Mercy Hospitals includes 2 separate hospitals: 1 hospital is a 354‐bed academic, tertiary care freestanding children's hospital located in Kansas City, Missouri; a second, smaller, 50‐bed freestanding hospital is located in Overland Park, Kansas. Both hospitals have pediatric emergency departments. Inclusion criteria included patients aged 5 to 17 years discharged for status asthmaticus (APR‐DRG 141) at Children's Mercy Hospital from October 1, 2011 to September 30, 2012, with a recorded BMI during the admission or within 30 days of the admission. Patients between the ages of 2 and 5 years old were not included because of the incidence of viral‐induced wheezing in this age group and therefore possible miscoding of the asthma diagnosis. Exclusion criteria included a concurrent diagnosis of a CCC or bacterial pneumonia because these conditions could alter LOS, resource utilization, and readmission rates independent of the subject's status asthmaticus. In addition, to account for differences in the amount of treatment given in the pre‐inpatient setting, patients not initially treated through the hospital's ED were excluded. For patients with multiple admissions during the study period for the same diagnosis, only the index admission was examined. The institutional review board at Children's Mercy Hospital approved this study with waiver of informed consent.

Study Definitions

BMI percentile for age was used as both a continuous and categorical predictor variable. As a categorical variable it was divided into 4 categories: underweight (BMI <5%), normal weight (BMI 5%84%), overweight (BMI 85%94%), and obese (BMI 95%).[23] Race was categorized non‐Hispanic white, non‐Hispanic black, and other. Other included Asian, Pacific Islander, American Indian, and other. Ethnicity was categorized as Hispanic and non‐Hispanic. Insurance categories included private (commercial or TRICARE), public (Medicaid and Title V), and other (uninsured, self‐pay, and other). Adjusted billed charges were calculated for each hospitalization. Adjusted billed charges are the billed charges adjusted by the US Centers of Medicare and Medicaid Services' price/wage index for the study site's location.[32, 33]

To compare albuterol of different delivery methods, albuterol equivalents were calculated. Based upon prior research demonstrating equal efficacy between albuterol administered by nebulizer and metered‐dose inhaler (MDI),[34] every 2.5 mg of albuterol administered by nebulizer was treated as equivalent to 2 sprays of albuterol (90 g/spray) administered by MDI. Therefore, albuterol 2.5 mg nebulized and 2 sprays of albuterol (90 g/spray) were each defined as 1 albuterol equivalent. To compare continuous administration of nebulized albuterol with intermittent administration of albuterol, the total milligrams of continuously nebulized albuterol were examined. Per protocol at the study site, 10 mg per hour of continuous albuterol are administered for patients 5 years and younger and, for children 6 years and older, 15 mg per hour of continuous albuterol are administered. Based upon milligrams of albuterol nebulized, 5‐year‐old subjects receiving an hour of continuous albuterol would equal 4 albuterol equivalents (or 4 treatments of nebulized albuterol 2.5 mg/treatment or 4 treatments of albuterol 90 g/spray 2 sprays/treatment); for patients 6 years and older, an hour of continuous albuterol would equal 6 albuterol equivalents (or 6 treatments of nebulized albuterol 2.5 mg/treatment or 6 treatments of albuterol 90 g/spray 2 sprays/treatment). The variable total albuterol was then created to include albuterol equivalents delivered by metered dose inhaler and as both single and continuous nebulized treatments.

Main Exposure

The main exposure of interest was BMI percentile for age.

Outcome Measures

The main outcome measure was inpatient LOS measured in hours. Secondary outcome measures included the total albuterol (in the inpatient setting as well as combined inpatient and ED settings) and the administration of intravenous IV fluids and intramuscular (IM) or IV systemic steroids. Other secondary measures included readmission for status asthmaticus during the study period, adjusted billed charges, and inpatient chest radiograph utilization.

Statistical Analyses

We summarized categorical variables with frequencies and percentages, and used [2] test across BMI categories. The non‐normal distribution of continuous dependent variables (LOS, number of albuterol treatments, billed charges) were summarized with medians and interquartile ranges (IQRs). Kruskal‐Wallis test was used to examine outcomes across BMI categories. For regression models, BMI percentile for age was divided into deciles and treated as a continuous predictor. Factors used in the regression models included age, gender, race, ethnicity, and insurance. Total albuterol received in the ED was also included in the model to adjust for differences in the amount of treatment received prior to admission. Incidence rate ratios were created using Poisson regression for continuous outcomes (LOS, billed charges, and number of albuterol equivalent treatments administered), and odds ratios were created using logistic regression for dichotomous outcomes. All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM, Armonk, NY), and P values <0.05 were considered statistically significant.

RESULTS

Patient Characteristics

Of 788 patients admitted for status asthmaticus during the study period, 518 (65.7%) met inclusion criteria; 42 (5.3%) did not meet inclusion criteria due to lack of a documented BMI (Table 1). Most patients were normal weight (59.7%). Approximately one‐third (36.7%) were either overweight or obese. The median age was 8 years, with patients with obesity being significantly older than underweight patients (9 vs 7.5 years, P<0.001). The majority of patients were black/African American (56.9%) and non‐Hispanic (88.6%). The percentage of patients who were obese was higher in patients of other race (29.3%) than whites (20.2%) or blacks (16.3%) (P<0.05). Patients of Hispanic ethnicity had a higher rate of obesity compared to non‐Hispanic patients (37.3% vs 17.4%, P<0.01). There were no differences in BMI categories for insurance.

Patient Characteristics by Body Mass Index Category
Patient CharacteristicsTotalCategory of Body Mass Index Percentile for Age
UnderweightNormalOverweightObeseP*

  • NOTE: Abbreviations: IQR, interquartile range. *Categorical variables were compared by 2 test, and continuous variables were compared by Kruskall‐Wallis test.

Total patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7) 
Age, y, median (IQR)8 (611)7.5 (5.89)8 (610)8 (610)9 (712)<0.001
Gender, n (%)      
Male30912 (3.9)184 (59.5)46 (14.9)67 (21.7)0.27
Female2096 (2.9)126 (60.3)42 (20.1)35 (16.7) 
Race, n (%)      
Non‐Hispanic white1248 (6.5)76 (61.3)15 (12.1)25 (20.2)0.021
Non‐Hispanic black2957 (2.4)182 (61.7)58 (19.7)48 (16.3) 
Other993 (3.0)52 (52.5)15 (15.2)29 (29.3) 
Ethnicity, n (%)      
Hispanic591 (1.7)25 (42.4)11 (18.6)22 (37.3)0.002
Non‐Hispanic45917 (3.7)285 (62.1)77 (16.8)80 (17.4) 
Insurance, n (%)      
Private16310 (6.1)97 (59.5)28 (17.2)28 (17.2)0.48
Public3137 (2.2)190 (60.7)51 (16.3)65 (20.8) 
Other421 (2.4)23 (54.8)9 (21.4)9 (21.4) 

LOS and Resource Utilization

The median LOS for all patients was approximately 1 day (Table 2). The median number of albuterol treatments in the inpatient setting was 14 (IQR, 824). When albuterol treatments given in the ED were included, the median number of treatments increased to 38 (IQR, 2848). Approximately one‐half of patients required supplemental oxygen, one‐third received IV fluids, and one‐fifth received either IV or IM steroids (with all but 1.6% of the remaining patients receiving oral steroids). Less than 5% of the study population received magnesium sulfate, epinephrine, required intensive care unit (ICU) admission, or were readmitted for status asthmaticus within 30 days. Approximately 15% of patients received a chest radiograph. The median adjusted billed charge was approximately $7,000. There were no differences in any of these outcomes by BMI category (P>0.05).

Resource Utilization, Readmissions, Length of Stay, and Billed Charges for In‐Hospital Status Asthmaticus by Body Mass Index Category
 TotalBody Mass Index Category
UnderweightNormalOverweightObese

  • NOTE: Abbreviations: ICU, intensive care unit; IM, intramuscular; IQR, interquartile range; IV, intravenous. *All differences between body mass index categories were nonsignificant (P>0.05).

Total Patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7)
LOS, h, median (IQR)26 (1841)41 (19.560.5)26 (1841)26 (19.2540)31 (1942)
Inpatient albuterol equivalents, median (IQR)14(824)19 (9.528)14 (824)14 (8.522)16 (824)
Total albuterol equivalents, median (IQR)38 (2848)34 (2734)36 (2848)37 (2849.5)40 (3052)
Adjusted billed charges, $, median (IQR)6,999.5 (52929258)7,457 (56048536)6876 (52379390)7056 (54099061)7198 (53319306)
All readmits, n (%)44 (8.5)2 (11.1)29 (9.4)7 (8.0)6 (5.9)
Readmits within 30 days, n (%)11 (2.1)1 (5.6)7 (2.3)1 (1.1)2 (2.0)
ICU admissions, n (%)24 (4.6)0 (0)13 (4.2)7 (8.0)4 (3.9)
Chest radiograph, n (%)64 (12.4)5 (27.8)34 (11.0)12 (13.6)13 (12.7)
Oxygen, n (%)255 (49.2)11 (61.1)157 (50.6)42 (47.7)45 (44.1)
IV/IM steroid, n (%)93 (18.0)2 (11.1)53 (17.1)18 (20.5)20 (19.6)
Epinephrine, n (%)2 (0.4)0 (0)2 (0.6)0 (0)0 (0)
Magnesium, n (%)15 (2.9)0 (0)8 (2.6)3 (3.4)4 (3.9)
IV fluids, n (%)152 (29.3)4 (22.2)85 (27.4)31 (35.2)32 (31.4)

Multivariable Results

After adjusting for age, gender, race, ethnicity, and insurance, the decile of BMI percentile for age showed a small negative association with LOS. Specifically, for each decile increase for BMI percentile for age, LOS decreased by approximately 2%. BMI percentile for age was not associated with other measures of resource utilization including total albuterol use, adjusted billed charges, readmission, ICU care, receipt of supplemental oxygen or a chest radiograph, IV fluids, or other medications (IV/IM steroids, epinephrine, or magnesium sulfate).

DISCUSSION

Our study suggests that the decile of BMI percentile for age is inversely associated with LOS but did not have a clinically meaningful effect. Secondary measures, such as total albuterol needs and adjusted billed charges, did not show an association with BMI percentile for age. There were also no associations between BMI percentile for age and other resource utilization outcomes.

Our findings differ from previous studies examining in‐hospital status asthmaticus in children who are overweight or obese. In addition, the present study was able to adjust for therapies received prior to admission. Carroll et al. demonstrated an increased LOS of approximately 3 days for overweight or obese asthmatics admitted to the ICU with status asthmaticus as well as increased duration of supplemental oxygen, continuous albuterol, and intravenous steroids.[20] It is possible that differences in methodology (ie, weight‐for‐age percentile vs BMI percentile for age, inclusion of ED treatments), different thresholds for treatment of status asthmaticus outside the ICU, or differences in patient populations studied (ie, only ICU patients vs all in‐hospital patients) explain the difference between their findings and the present study. The present study's use of BMI percentile for age follows current recommendations for classifying a patient as obese or overweight.[23, 24, 25] However, the use of classifications other than BMI percentile for age would tend to bias toward the null hypothesis, whereas in Carroll's study children who were overweight or obese had increased resource utilization. Additionally, in the time frame between this publication and the current study, many hospitals worked to standardize asthma hospitalizations by creating weaning protocols for albuterol, thereby decreasing LOS for all asthmatics, which may also affect the differences in LOS between groups of obese and nonobese patients.[35]

Woolford et al. found approximately a one‐half‐day increase in LOS and $2,000 higher mean charges for patients admitted with status asthmaticus and a secondary diagnosis of obesity.[8, 9] Study location and differing methods for defining obesity may account for the discrepancy between Woolford's findings and our study. We examined children admitted to the inpatient floor of a tertiary care children's hospital compared to Woolford et al.'s examination of pediatric patients admitted to all hospitals via the Kids' Inpatient Database (Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality). That study also relied on the coding of obesity as an ICD‐9 diagnosis, rather than examining the BMI of all admitted patients. Previous research has demonstrated that relying on a coded diagnosis of obesity is not as sensitive as measurement.[26] By relying on ICD‐9 diagnosis coding, only patients with very high BMIs may be diagnosed with obesity during the admission and therefore only associations between very high BMI and status asthmaticus will be examined.

There are several limitations to our findings. First, our study was limited to a single, tertiary care children's hospital and may not be generalizable to other hospitals. Our hospital standardizes the treatment of inpatient status asthmatics by formation of a respiratory care plan, involving interval scoring of respiratory symptoms and automatic spacing of albuterol treatments. This likely minimizes physician‐to‐physician variation. Second, we included only those patients who were initially treated within the ED associated with the admitting hospital to minimize the effects of timing for treatments prior to admittance. This excluded those patients first cared for by their primary care physician or by an outlying ED. Therefore, our sample may be biased toward a study population less connected to a medical home and therefore possibly poorer asthma control. Third, to utilize the most accurate method to define obesity, we excluded approximately 5% of eligible patients because BMI was unavailable. This may have included children with more severe asthma symptoms, as a height measurement may have been deferred due to their higher acuity. Asthma severity or chronicity would be associated with our outcomes of interest. However, we were unable to collect reliable data on severity or chronicity. Finally, to measure the amount of total albuterol needed by a patient during the ED and inpatient admissions, albuterol treatments delivered by MDI, nebulizer, or continuously were converted into total albuterol. Although based upon total milligram dosing and studies comparing routes of albuterol administration,[34] the validity of this conversion is unknown.

CONCLUSION

Although BMI percentile for age is inversely associated with LOS for in‐hospital pediatric status asthmaticus, the impact of BMI on this outcome likely is not clinically meaningful. Future investigations should examine other elements of BMI and in‐hospital status asthmaticus, such as any associations between BMI and admission rates.

Acknowledgements

The authors offer their appreciation to their research assistant, Amy Lee, for her support and dedication to this project.

Disclosures

Internal funds from Children's Mercy Hospital and Clinics supported the conduct of this work. The authors report no conflicts of interest.

Pediatric hospitalizations for obesity‐related conditions have doubled in the last decade, mirroring the trend of higher levels of childhood obesity in the United States.[1, 2, 3] Recent studies have demonstrated worsened pediatric in‐hospital outcomes, including mortality and increased resource utilization, for children with obesity across a range of diagnoses.[4, 5, 6, 7, 8, 9, 10] Although the mechanisms driving the association between obesity and in‐hospital outcomes are not fully known, for asthma it is believed that adipocytes expressing inflammatory markers create a low level of systemic inflammation, thereby increasing the severity of allergic‐type illnesses and decreasing the response to anti‐inflammatory medications, such as steroids.[11, 12, 13, 14, 15, 16, 17, 18] The relationship of obesity and in‐hospital asthma outcomes is of particular interest because status asthmaticus is the most common reason for admission in children aged 3 to 12 years, accounting for approximately 150,000 admissions (7.4% of all hospitalizations for children and adolescents) and $835 million in hospital costs annually.[19]

Few prior studies have examined the association of obesity and asthma outcomes in the in‐hospital setting. The studies examining this association have found patients with obesity to have a longer hospital length of stay (LOS) and increased hospital costs.[8, 9, 20] Obesity has also been associated with increased respiratory treatments and supplemental oxygen requirements.[20] Associations between obesity and admission rates from the emergency department (ED) for pediatric asthma have been inconsistent.[21, 22] Most of these prior studies had several limitations in identifying patients with obesity, including using weight‐for‐age percentiles or International Classification of Diseases, Ninth Revision (ICD‐9) codes, rather than body mass index (BMI) percentile for age, the currently recommended method.[23, 24, 25] Methods other than BMI have the potential to either underestimate obesity (ie, ICD‐9 codes)[26] or to confound weight with adiposity (ie, weight‐for‐age percentiles),[27] thereby skewing the primary exposure of interest.

In the present study, we sought to examine associations between obesity and in‐hospital outcomes for pediatric status asthmaticus using the currently endorsed method for identifying obesity in children, BMI percentile for age.[23, 24, 25] The outcomes of interest included a broad range of in‐hospital measures, including resource utilization (medication and radiology use), readmission rates, billed charges, and LOS. We hypothesize that obesity, due to its proinflammatory state, would result in increased LOS, increased resource utilization, and an increased readmission rate for children admitted with status asthmaticus.

METHODS

Data Sources

Data for this retrospective cross‐sectional study were obtained from 2 sources. First, we queried the Pediatric Health Information System (PHIS) administrative database, which draws information from multiple children's hospitals to identify patients at our 2 institutions of interest who met study criteria. The PHIS database also was used to collect patient demographic data. PHIS is an administrative database operated by Children's Hospital Association (Overland Park, KS) containing clinical and billing data from 43 tertiary care, freestanding children's hospitals, including data on 41 ICD‐9 diagnoses, billed charges, and LOS. Based on the primary diagnosis, PHIS assigns each discharge to an All Patient Refined‐Diagnosis Related Group (APR‐DRG v.24) (3M Health information Systems, St. Paul, MN). APR‐DRGs allow similar diagnoses to be grouped together.[28, 29] PHIS also uses ICD‐9 codes to identify patients with a complex chronic condition (CCC).[30, 31] CCCs are those conditions that can be reasonably expected to last at least 12 months (unless death intervenes) and to involve either several different organ systems or one system severely enough to require specialty pediatric care and probably some period of hospitalization in a tertiary care center.[30, 31] PHIS data quality is ensured through a collaborative effort of the participating hospitals, the Children's Hospital Association, and Truven Healthcare.

Second, standardized chart reviews were then performed to collect clinical data not found in PHIS: BMI, LOS in hours, and medications administered, including total number of albuterol treatments administered during both the admission and the associated preceding ED visit.

Study Setting and Participants

All admissions examined in this study were at Children's Mercy Hospitals. Children's Mercy Hospitals includes 2 separate hospitals: 1 hospital is a 354‐bed academic, tertiary care freestanding children's hospital located in Kansas City, Missouri; a second, smaller, 50‐bed freestanding hospital is located in Overland Park, Kansas. Both hospitals have pediatric emergency departments. Inclusion criteria included patients aged 5 to 17 years discharged for status asthmaticus (APR‐DRG 141) at Children's Mercy Hospital from October 1, 2011 to September 30, 2012, with a recorded BMI during the admission or within 30 days of the admission. Patients between the ages of 2 and 5 years old were not included because of the incidence of viral‐induced wheezing in this age group and therefore possible miscoding of the asthma diagnosis. Exclusion criteria included a concurrent diagnosis of a CCC or bacterial pneumonia because these conditions could alter LOS, resource utilization, and readmission rates independent of the subject's status asthmaticus. In addition, to account for differences in the amount of treatment given in the pre‐inpatient setting, patients not initially treated through the hospital's ED were excluded. For patients with multiple admissions during the study period for the same diagnosis, only the index admission was examined. The institutional review board at Children's Mercy Hospital approved this study with waiver of informed consent.

Study Definitions

BMI percentile for age was used as both a continuous and categorical predictor variable. As a categorical variable it was divided into 4 categories: underweight (BMI <5%), normal weight (BMI 5%84%), overweight (BMI 85%94%), and obese (BMI 95%).[23] Race was categorized non‐Hispanic white, non‐Hispanic black, and other. Other included Asian, Pacific Islander, American Indian, and other. Ethnicity was categorized as Hispanic and non‐Hispanic. Insurance categories included private (commercial or TRICARE), public (Medicaid and Title V), and other (uninsured, self‐pay, and other). Adjusted billed charges were calculated for each hospitalization. Adjusted billed charges are the billed charges adjusted by the US Centers of Medicare and Medicaid Services' price/wage index for the study site's location.[32, 33]

To compare albuterol of different delivery methods, albuterol equivalents were calculated. Based upon prior research demonstrating equal efficacy between albuterol administered by nebulizer and metered‐dose inhaler (MDI),[34] every 2.5 mg of albuterol administered by nebulizer was treated as equivalent to 2 sprays of albuterol (90 g/spray) administered by MDI. Therefore, albuterol 2.5 mg nebulized and 2 sprays of albuterol (90 g/spray) were each defined as 1 albuterol equivalent. To compare continuous administration of nebulized albuterol with intermittent administration of albuterol, the total milligrams of continuously nebulized albuterol were examined. Per protocol at the study site, 10 mg per hour of continuous albuterol are administered for patients 5 years and younger and, for children 6 years and older, 15 mg per hour of continuous albuterol are administered. Based upon milligrams of albuterol nebulized, 5‐year‐old subjects receiving an hour of continuous albuterol would equal 4 albuterol equivalents (or 4 treatments of nebulized albuterol 2.5 mg/treatment or 4 treatments of albuterol 90 g/spray 2 sprays/treatment); for patients 6 years and older, an hour of continuous albuterol would equal 6 albuterol equivalents (or 6 treatments of nebulized albuterol 2.5 mg/treatment or 6 treatments of albuterol 90 g/spray 2 sprays/treatment). The variable total albuterol was then created to include albuterol equivalents delivered by metered dose inhaler and as both single and continuous nebulized treatments.

Main Exposure

The main exposure of interest was BMI percentile for age.

Outcome Measures

The main outcome measure was inpatient LOS measured in hours. Secondary outcome measures included the total albuterol (in the inpatient setting as well as combined inpatient and ED settings) and the administration of intravenous IV fluids and intramuscular (IM) or IV systemic steroids. Other secondary measures included readmission for status asthmaticus during the study period, adjusted billed charges, and inpatient chest radiograph utilization.

Statistical Analyses

We summarized categorical variables with frequencies and percentages, and used [2] test across BMI categories. The non‐normal distribution of continuous dependent variables (LOS, number of albuterol treatments, billed charges) were summarized with medians and interquartile ranges (IQRs). Kruskal‐Wallis test was used to examine outcomes across BMI categories. For regression models, BMI percentile for age was divided into deciles and treated as a continuous predictor. Factors used in the regression models included age, gender, race, ethnicity, and insurance. Total albuterol received in the ED was also included in the model to adjust for differences in the amount of treatment received prior to admission. Incidence rate ratios were created using Poisson regression for continuous outcomes (LOS, billed charges, and number of albuterol equivalent treatments administered), and odds ratios were created using logistic regression for dichotomous outcomes. All statistical analyses were performed using IBM SPSS Statistics version 20 (IBM, Armonk, NY), and P values <0.05 were considered statistically significant.

RESULTS

Patient Characteristics

Of 788 patients admitted for status asthmaticus during the study period, 518 (65.7%) met inclusion criteria; 42 (5.3%) did not meet inclusion criteria due to lack of a documented BMI (Table 1). Most patients were normal weight (59.7%). Approximately one‐third (36.7%) were either overweight or obese. The median age was 8 years, with patients with obesity being significantly older than underweight patients (9 vs 7.5 years, P<0.001). The majority of patients were black/African American (56.9%) and non‐Hispanic (88.6%). The percentage of patients who were obese was higher in patients of other race (29.3%) than whites (20.2%) or blacks (16.3%) (P<0.05). Patients of Hispanic ethnicity had a higher rate of obesity compared to non‐Hispanic patients (37.3% vs 17.4%, P<0.01). There were no differences in BMI categories for insurance.

Patient Characteristics by Body Mass Index Category
Patient CharacteristicsTotalCategory of Body Mass Index Percentile for Age
UnderweightNormalOverweightObeseP*

  • NOTE: Abbreviations: IQR, interquartile range. *Categorical variables were compared by 2 test, and continuous variables were compared by Kruskall‐Wallis test.

Total patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7) 
Age, y, median (IQR)8 (611)7.5 (5.89)8 (610)8 (610)9 (712)<0.001
Gender, n (%)      
Male30912 (3.9)184 (59.5)46 (14.9)67 (21.7)0.27
Female2096 (2.9)126 (60.3)42 (20.1)35 (16.7) 
Race, n (%)      
Non‐Hispanic white1248 (6.5)76 (61.3)15 (12.1)25 (20.2)0.021
Non‐Hispanic black2957 (2.4)182 (61.7)58 (19.7)48 (16.3) 
Other993 (3.0)52 (52.5)15 (15.2)29 (29.3) 
Ethnicity, n (%)      
Hispanic591 (1.7)25 (42.4)11 (18.6)22 (37.3)0.002
Non‐Hispanic45917 (3.7)285 (62.1)77 (16.8)80 (17.4) 
Insurance, n (%)      
Private16310 (6.1)97 (59.5)28 (17.2)28 (17.2)0.48
Public3137 (2.2)190 (60.7)51 (16.3)65 (20.8) 
Other421 (2.4)23 (54.8)9 (21.4)9 (21.4) 

LOS and Resource Utilization

The median LOS for all patients was approximately 1 day (Table 2). The median number of albuterol treatments in the inpatient setting was 14 (IQR, 824). When albuterol treatments given in the ED were included, the median number of treatments increased to 38 (IQR, 2848). Approximately one‐half of patients required supplemental oxygen, one‐third received IV fluids, and one‐fifth received either IV or IM steroids (with all but 1.6% of the remaining patients receiving oral steroids). Less than 5% of the study population received magnesium sulfate, epinephrine, required intensive care unit (ICU) admission, or were readmitted for status asthmaticus within 30 days. Approximately 15% of patients received a chest radiograph. The median adjusted billed charge was approximately $7,000. There were no differences in any of these outcomes by BMI category (P>0.05).

Resource Utilization, Readmissions, Length of Stay, and Billed Charges for In‐Hospital Status Asthmaticus by Body Mass Index Category
 TotalBody Mass Index Category
UnderweightNormalOverweightObese

  • NOTE: Abbreviations: ICU, intensive care unit; IM, intramuscular; IQR, interquartile range; IV, intravenous. *All differences between body mass index categories were nonsignificant (P>0.05).

Total Patients, n (%)51818 (3.5)310 (59.8)88 (17.0)102 (19.7)
LOS, h, median (IQR)26 (1841)41 (19.560.5)26 (1841)26 (19.2540)31 (1942)
Inpatient albuterol equivalents, median (IQR)14(824)19 (9.528)14 (824)14 (8.522)16 (824)
Total albuterol equivalents, median (IQR)38 (2848)34 (2734)36 (2848)37 (2849.5)40 (3052)
Adjusted billed charges, $, median (IQR)6,999.5 (52929258)7,457 (56048536)6876 (52379390)7056 (54099061)7198 (53319306)
All readmits, n (%)44 (8.5)2 (11.1)29 (9.4)7 (8.0)6 (5.9)
Readmits within 30 days, n (%)11 (2.1)1 (5.6)7 (2.3)1 (1.1)2 (2.0)
ICU admissions, n (%)24 (4.6)0 (0)13 (4.2)7 (8.0)4 (3.9)
Chest radiograph, n (%)64 (12.4)5 (27.8)34 (11.0)12 (13.6)13 (12.7)
Oxygen, n (%)255 (49.2)11 (61.1)157 (50.6)42 (47.7)45 (44.1)
IV/IM steroid, n (%)93 (18.0)2 (11.1)53 (17.1)18 (20.5)20 (19.6)
Epinephrine, n (%)2 (0.4)0 (0)2 (0.6)0 (0)0 (0)
Magnesium, n (%)15 (2.9)0 (0)8 (2.6)3 (3.4)4 (3.9)
IV fluids, n (%)152 (29.3)4 (22.2)85 (27.4)31 (35.2)32 (31.4)

Multivariable Results

After adjusting for age, gender, race, ethnicity, and insurance, the decile of BMI percentile for age showed a small negative association with LOS. Specifically, for each decile increase for BMI percentile for age, LOS decreased by approximately 2%. BMI percentile for age was not associated with other measures of resource utilization including total albuterol use, adjusted billed charges, readmission, ICU care, receipt of supplemental oxygen or a chest radiograph, IV fluids, or other medications (IV/IM steroids, epinephrine, or magnesium sulfate).

DISCUSSION

Our study suggests that the decile of BMI percentile for age is inversely associated with LOS but did not have a clinically meaningful effect. Secondary measures, such as total albuterol needs and adjusted billed charges, did not show an association with BMI percentile for age. There were also no associations between BMI percentile for age and other resource utilization outcomes.

Our findings differ from previous studies examining in‐hospital status asthmaticus in children who are overweight or obese. In addition, the present study was able to adjust for therapies received prior to admission. Carroll et al. demonstrated an increased LOS of approximately 3 days for overweight or obese asthmatics admitted to the ICU with status asthmaticus as well as increased duration of supplemental oxygen, continuous albuterol, and intravenous steroids.[20] It is possible that differences in methodology (ie, weight‐for‐age percentile vs BMI percentile for age, inclusion of ED treatments), different thresholds for treatment of status asthmaticus outside the ICU, or differences in patient populations studied (ie, only ICU patients vs all in‐hospital patients) explain the difference between their findings and the present study. The present study's use of BMI percentile for age follows current recommendations for classifying a patient as obese or overweight.[23, 24, 25] However, the use of classifications other than BMI percentile for age would tend to bias toward the null hypothesis, whereas in Carroll's study children who were overweight or obese had increased resource utilization. Additionally, in the time frame between this publication and the current study, many hospitals worked to standardize asthma hospitalizations by creating weaning protocols for albuterol, thereby decreasing LOS for all asthmatics, which may also affect the differences in LOS between groups of obese and nonobese patients.[35]

Woolford et al. found approximately a one‐half‐day increase in LOS and $2,000 higher mean charges for patients admitted with status asthmaticus and a secondary diagnosis of obesity.[8, 9] Study location and differing methods for defining obesity may account for the discrepancy between Woolford's findings and our study. We examined children admitted to the inpatient floor of a tertiary care children's hospital compared to Woolford et al.'s examination of pediatric patients admitted to all hospitals via the Kids' Inpatient Database (Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality). That study also relied on the coding of obesity as an ICD‐9 diagnosis, rather than examining the BMI of all admitted patients. Previous research has demonstrated that relying on a coded diagnosis of obesity is not as sensitive as measurement.[26] By relying on ICD‐9 diagnosis coding, only patients with very high BMIs may be diagnosed with obesity during the admission and therefore only associations between very high BMI and status asthmaticus will be examined.

There are several limitations to our findings. First, our study was limited to a single, tertiary care children's hospital and may not be generalizable to other hospitals. Our hospital standardizes the treatment of inpatient status asthmatics by formation of a respiratory care plan, involving interval scoring of respiratory symptoms and automatic spacing of albuterol treatments. This likely minimizes physician‐to‐physician variation. Second, we included only those patients who were initially treated within the ED associated with the admitting hospital to minimize the effects of timing for treatments prior to admittance. This excluded those patients first cared for by their primary care physician or by an outlying ED. Therefore, our sample may be biased toward a study population less connected to a medical home and therefore possibly poorer asthma control. Third, to utilize the most accurate method to define obesity, we excluded approximately 5% of eligible patients because BMI was unavailable. This may have included children with more severe asthma symptoms, as a height measurement may have been deferred due to their higher acuity. Asthma severity or chronicity would be associated with our outcomes of interest. However, we were unable to collect reliable data on severity or chronicity. Finally, to measure the amount of total albuterol needed by a patient during the ED and inpatient admissions, albuterol treatments delivered by MDI, nebulizer, or continuously were converted into total albuterol. Although based upon total milligram dosing and studies comparing routes of albuterol administration,[34] the validity of this conversion is unknown.

CONCLUSION

Although BMI percentile for age is inversely associated with LOS for in‐hospital pediatric status asthmaticus, the impact of BMI on this outcome likely is not clinically meaningful. Future investigations should examine other elements of BMI and in‐hospital status asthmaticus, such as any associations between BMI and admission rates.

Acknowledgements

The authors offer their appreciation to their research assistant, Amy Lee, for her support and dedication to this project.

Disclosures

Internal funds from Children's Mercy Hospital and Clinics supported the conduct of this work. The authors report no conflicts of interest.

References
  1. Cunningham SA, Kramer MR, Narayan KMV. Incidence of childhood obesity in the United States. N Engl J Med. 2014;370(5):403–411.
  2. Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr. 2014;168(6):561–566.
  3. Trasande L, Liu Y, Fryer G, Weitzman M. Effects of childhood obesity on hospital care and costs, 1999–2005. Health Affairs. 2009;28(4):w751–w760.
  4. Bechard LJ, Rothpletz‐Puglia P, Touger‐Decker R, Duggan C, Mehta NM. Influence of obesity on clinical outcomes in hospitalized children: a systematic review. JAMA Pediatr. 2013;167(5):476–482.
  5. Davies DA, Yanchar NL. Appendicitis in the obese child. J Pediatr Surg. 2007;42(5):857–861.
  6. Patel L, Cowden JD, Dowd D, Hampl S, Felich N. Obesity: influence on length of hospital stay for the pediatric burn patient. J Burn Care Res. 2010;31(2):251–256.
  7. Brown CVR, Neville AL, Salim A, Rhee P, Cologne K, Demetriades D. The impact of obesity on severely injured children and adolescents. J Pediatr Surg. 2006;41(1):88–91.
  8. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Incremental hospital charges associated with obesity as a secondary diagnosis in children. Obesity (Silver Spring). 2007;15(7):1895–1901.
  9. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Persistent gap of incremental charges for obesity as a secondary diagnosis in common pediatric hospitalizations. J Hosp Med. 2009;4(3):149–156.
  10. Hampl SE, Carroll CA, Simon SD, Sharma V. Resource utilization and expenditures for overweight and obese children. Arch Pediatr Adolesc Med. 2007;161(1):11–14.
  11. Forno E, Lescher R, Strunk R, Weiss S, Fuhlbrigge A, Celedon JC. Decreased response to inhaled steroids in overweight and obese asthmatic children. J Allergy Clin Immunol. 2011;127(3):741–749.
  12. Sutherland ER, Goleva E, Strand M, Beuther DA, Leung DYM. Body mass and glucocorticoid response in asthma. Am J Respir Crit Care Med. 2008;178(7):682–687.
  13. Sutherland ER, Lehman EB, Teodorescu M, Wechsler ME; National Heart, Lung, and Blood Institute's Asthma Clinical Research Network. Body mass index and phenotype in subjects with mild‐to‐moderate persistent asthma. J Allergy Clin Immunol. 2009;123(6):1328–1334.e1.
  14. Stream AR, Sutherland ER. Obesity and asthma disease phenotypes. Curr Opin Allergy Clin Immunol. 2012;12(1):76–81.
  15. Sin DD, Sutherland ER. Obesity and the lung: 4. Obesity and asthma. Thorax. 2008;63(11):1018–1023.
  16. Camargo CA, Boulet L‐P, Sutherland ER, et al. Body mass index and response to asthma therapy: fluticasone propionate/salmeterol versus montelukast. J Asthma. 2010;47(1):76–82.
  17. Dixon AE, Shade DM, Cohen RI, et al. Effect of obesity on clinical presentation and response to treatment in asthma. J Asthma. 2006;43(7):553–558.
  18. Suglia SF, Chambers EC, Rosario A, Duarte CS. Asthma and obesity in three‐year‐old urban children: role of sex and home environment. J Pediatr. 2011;159(1):14–20.
  19. Owens PL, Thompson J, Elixhauser A, Ryan K. Care of Children and Adolescents in U.S. Hospitals. Rockville, MD: Agency for Healthcare Research and Quality; 2003. Available at: http://archive.ahrq.gov/data/hcup/factbk4/factbk4.pdf. Accessed February 12, 2014.
  20. Carroll CL, Bhandari A, Zucker AR, Schramm CM. Childhood obesity increases duration of therapy during severe asthma exacerbations. Pediatr Crit Care Med. 2006;7(6):527–531.
  21. Carroll CL, Stoltz P, Raykov N, Smith SR, Zucker AR. Childhood overweight increases hospital admission rates for asthma. Pediatr. 2007;120(4):734–740.
  22. Ginde AA, Santillan AA, Clark S, Camargo CA. Body mass index and acute asthma severity among children presenting to the emergency department. Pediatr Allergy Immunol. 2009;21(3):480–488.
  23. Centers for Disease Control and Prevention. Basics about childhood obesity. Available at: http://www.cdc.gov/obesity/childhood/basics.html. Accessed February 12, 2014.
  24. Whitlock EP. Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Pediatrics. 2005;116(1):e125–e144.
  25. Barlow SE; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164–S192.
  26. Kuhle S, Kirk SFL, Ohinmaa A, Veugelers PJ. Comparison of ICD code‐based diagnosis of obesity with measured obesity in children and the implications for health care cost estimates. BMC Med Res Methodol. 2011;11(1):173.
  27. Krebs NF, Jacobson MS; American Academy of Pediatrics Committee on Nutrition. Prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424–430.
  28. Hughes J. Development of the 3M all patient‐refined diagnosis‐related groups (APR DRGs). Available at: http//www.ahrq.gov/legacy/qual/mortality/Hughes3.htm. Accessed March 1, 2014.
  29. Hughes J. 3M Health Information Systems (HIS) APR‐DRG classification software: overview. Available at: http://www.ahrq.gov/legacy/qual/mortality/Hughessumm.htm. Accessed March 1, 2014.
  30. Feudtner C, Feinstein JA, Satchell M, Zhao H, Kang TI. Shifting place of death among children with complex chronic conditions in the United States, 1989–2003. JAMA. 2007;297(24):2725–2732.
  31. Feudtner C, Christakis DA, Connell FA. Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997. Pediatrics. 2000;106(1 pt 2):205–209.
  32. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256–263.
  33. Weiss AK, Hall M, Lee GE, Kronman MP, Sheffler‐Collins S, Shah SS. Adjunct corticosteroids in children hospitalized with community‐acquired pneumonia. Pediatrics. 2011;127(2):e255–e263.
  34. Cates CJ, Welsh EJ, Rowe BH. Holding chambers (spacers) versus nebulisers for beta‐agonist treatment of acute asthma. Cochrane Database Syst Rev. 2013;9:CD000052.
  35. Johnson KB, Blaisdell CJ, Walker A, Eggleston P. Effectiveness of a clinical pathway for inpatient asthma management. Pediatrics. 2000;106(5):1006–1012.
References
  1. Cunningham SA, Kramer MR, Narayan KMV. Incidence of childhood obesity in the United States. N Engl J Med. 2014;370(5):403–411.
  2. Skinner AC, Skelton JA. Prevalence and trends in obesity and severe obesity among children in the United States, 1999–2012. JAMA Pediatr. 2014;168(6):561–566.
  3. Trasande L, Liu Y, Fryer G, Weitzman M. Effects of childhood obesity on hospital care and costs, 1999–2005. Health Affairs. 2009;28(4):w751–w760.
  4. Bechard LJ, Rothpletz‐Puglia P, Touger‐Decker R, Duggan C, Mehta NM. Influence of obesity on clinical outcomes in hospitalized children: a systematic review. JAMA Pediatr. 2013;167(5):476–482.
  5. Davies DA, Yanchar NL. Appendicitis in the obese child. J Pediatr Surg. 2007;42(5):857–861.
  6. Patel L, Cowden JD, Dowd D, Hampl S, Felich N. Obesity: influence on length of hospital stay for the pediatric burn patient. J Burn Care Res. 2010;31(2):251–256.
  7. Brown CVR, Neville AL, Salim A, Rhee P, Cologne K, Demetriades D. The impact of obesity on severely injured children and adolescents. J Pediatr Surg. 2006;41(1):88–91.
  8. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Incremental hospital charges associated with obesity as a secondary diagnosis in children. Obesity (Silver Spring). 2007;15(7):1895–1901.
  9. Woolford SJ, Gebremariam A, Clark SJ, Davis MM. Persistent gap of incremental charges for obesity as a secondary diagnosis in common pediatric hospitalizations. J Hosp Med. 2009;4(3):149–156.
  10. Hampl SE, Carroll CA, Simon SD, Sharma V. Resource utilization and expenditures for overweight and obese children. Arch Pediatr Adolesc Med. 2007;161(1):11–14.
  11. Forno E, Lescher R, Strunk R, Weiss S, Fuhlbrigge A, Celedon JC. Decreased response to inhaled steroids in overweight and obese asthmatic children. J Allergy Clin Immunol. 2011;127(3):741–749.
  12. Sutherland ER, Goleva E, Strand M, Beuther DA, Leung DYM. Body mass and glucocorticoid response in asthma. Am J Respir Crit Care Med. 2008;178(7):682–687.
  13. Sutherland ER, Lehman EB, Teodorescu M, Wechsler ME; National Heart, Lung, and Blood Institute's Asthma Clinical Research Network. Body mass index and phenotype in subjects with mild‐to‐moderate persistent asthma. J Allergy Clin Immunol. 2009;123(6):1328–1334.e1.
  14. Stream AR, Sutherland ER. Obesity and asthma disease phenotypes. Curr Opin Allergy Clin Immunol. 2012;12(1):76–81.
  15. Sin DD, Sutherland ER. Obesity and the lung: 4. Obesity and asthma. Thorax. 2008;63(11):1018–1023.
  16. Camargo CA, Boulet L‐P, Sutherland ER, et al. Body mass index and response to asthma therapy: fluticasone propionate/salmeterol versus montelukast. J Asthma. 2010;47(1):76–82.
  17. Dixon AE, Shade DM, Cohen RI, et al. Effect of obesity on clinical presentation and response to treatment in asthma. J Asthma. 2006;43(7):553–558.
  18. Suglia SF, Chambers EC, Rosario A, Duarte CS. Asthma and obesity in three‐year‐old urban children: role of sex and home environment. J Pediatr. 2011;159(1):14–20.
  19. Owens PL, Thompson J, Elixhauser A, Ryan K. Care of Children and Adolescents in U.S. Hospitals. Rockville, MD: Agency for Healthcare Research and Quality; 2003. Available at: http://archive.ahrq.gov/data/hcup/factbk4/factbk4.pdf. Accessed February 12, 2014.
  20. Carroll CL, Bhandari A, Zucker AR, Schramm CM. Childhood obesity increases duration of therapy during severe asthma exacerbations. Pediatr Crit Care Med. 2006;7(6):527–531.
  21. Carroll CL, Stoltz P, Raykov N, Smith SR, Zucker AR. Childhood overweight increases hospital admission rates for asthma. Pediatr. 2007;120(4):734–740.
  22. Ginde AA, Santillan AA, Clark S, Camargo CA. Body mass index and acute asthma severity among children presenting to the emergency department. Pediatr Allergy Immunol. 2009;21(3):480–488.
  23. Centers for Disease Control and Prevention. Basics about childhood obesity. Available at: http://www.cdc.gov/obesity/childhood/basics.html. Accessed February 12, 2014.
  24. Whitlock EP. Screening and interventions for childhood overweight: a summary of evidence for the US Preventive Services Task Force. Pediatrics. 2005;116(1):e125–e144.
  25. Barlow SE; Expert Committee. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164–S192.
  26. Kuhle S, Kirk SFL, Ohinmaa A, Veugelers PJ. Comparison of ICD code‐based diagnosis of obesity with measured obesity in children and the implications for health care cost estimates. BMC Med Res Methodol. 2011;11(1):173.
  27. Krebs NF, Jacobson MS; American Academy of Pediatrics Committee on Nutrition. Prevention of pediatric overweight and obesity. Pediatrics. 2003;112(2):424–430.
  28. Hughes J. Development of the 3M all patient‐refined diagnosis‐related groups (APR DRGs). Available at: http//www.ahrq.gov/legacy/qual/mortality/Hughes3.htm. Accessed March 1, 2014.
  29. Hughes J. 3M Health Information Systems (HIS) APR‐DRG classification software: overview. Available at: http://www.ahrq.gov/legacy/qual/mortality/Hughessumm.htm. Accessed March 1, 2014.
  30. Feudtner C, Feinstein JA, Satchell M, Zhao H, Kang TI. Shifting place of death among children with complex chronic conditions in the United States, 1989–2003. JAMA. 2007;297(24):2725–2732.
  31. Feudtner C, Christakis DA, Connell FA. Pediatric deaths attributable to complex chronic conditions: a population‐based study of Washington State, 1980–1997. Pediatrics. 2000;106(1 pt 2):205–209.
  32. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256–263.
  33. Weiss AK, Hall M, Lee GE, Kronman MP, Sheffler‐Collins S, Shah SS. Adjunct corticosteroids in children hospitalized with community‐acquired pneumonia. Pediatrics. 2011;127(2):e255–e263.
  34. Cates CJ, Welsh EJ, Rowe BH. Holding chambers (spacers) versus nebulisers for beta‐agonist treatment of acute asthma. Cochrane Database Syst Rev. 2013;9:CD000052.
  35. Johnson KB, Blaisdell CJ, Walker A, Eggleston P. Effectiveness of a clinical pathway for inpatient asthma management. Pediatrics. 2000;106(5):1006–1012.
Issue
Journal of Hospital Medicine - 10(3)
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Journal of Hospital Medicine - 10(3)
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160-164
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160-164
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Childhood obesity and in‐hospital asthma resource utilization
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Childhood obesity and in‐hospital asthma resource utilization
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Jessica Bettenhausen, MD
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Address for correspondence and reprint requests: Jessica Bettenhausen, MD, Department of Pediatrics, Children's Mercy Hospitals and Clinics, 2401 Gillham Road, Kansas City, MO 64108; Telephone: 816‐802‐1493; Fax: 816‐559‐9530; E‐mail: jlbettenhausen@cmh.edu
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