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. 2016 Jan;116(1):26-30.
doi: 10.1016/j.anai.2015.10.014. Epub 2015 Nov 6.

Developing a risk stratification model for predicting future health care use in asthmatic children

Jill R Hanson  1 , Brian R Lee  2 , David D Williams  3 , Helen Murphy  4 , Kevin Kennedy  5 , Stephen A DeLurgio Sr  3 , Jay Portnoy  6 , Mamta Reddy  6
Affiliations

Developing a risk stratification model for predicting future health care use in asthmatic children

Jill R Hanson et al. Ann Allergy Asthma Immunol. 2016 Jan.

Abstract

Background: Previous studies have stratified pediatric asthma patients for risk of future exacerbation and/or health care use, but most incorporate multiple clinical parameters.

Objective: To determine whether historical acute care visits (ACVs) alone could predict risk of future health care use.

Methods: Children seen for asthma in an outpatient visit during a 3-year period were identified. The number of ACVs in the 12 months before and after the outpatient visit was determined. Logistic regression models were used to determine the odds of a future ACV. Models were adjusted for age, sex, race, and insurance status.

Results: Of 28,047 outpatient visits, 21,099 (75.2%) had no historical ACVs. The probability of a future ACV increased from 30% with one historical ACV to 87% with 5 or more historical ACVs. Outpatient visits with one historical ACV had significantly higher odds of a future ACV compared with those with no historical ACVs (adjusted odds ratio [OR], 3.60; 95% confidence interval [CI], 3.14-4.12; P < .001). The OR increased with each additional historical ACV to an adjusted OR of 58.71 (95% CI, 24.34-141.61; P < .001) with 5 or more historical ACVs. Outpatient visits with 5 or more historical ACVs represented only 1.1% of the study sample but accounted for a higher mean number of future ACVs.

Conclusion: The historical count of ACVs was predictive of future ACVs. A significant increase in the probability of future ACVs was observed with each additional historical visit, effectively stratifying risk by the historical visit count. Notably, a small group of patients accounted for a disproportionate number of future ACVs.

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