478 THE AMERICAN JOURNAL OF MANAGED CARE AUGUST 2006 METHODS A sthma is a common chronic medical condition that exacts a high human and economic cost in our society. 1,2 The prevalence and impact of asthma, along with the availability of effective controller therapy, make it an appropriate disease for population management, which involves disease identification, risk stratification, and therapeutic intervention in specified populations. Risk stratification is used in population management to identify those asthmatic patients who are most likely to experience morbidity and resource utilization, and for whom targeted intervention should reduce these risks. In addition, risk adjustment is nec- essary when using databases to evaluate the effects of interventions on asthma outcomes. Several prior studies developed and validated risk stratification schemes based on electronic data to predict subsequent emergency hospital utilization for asthma. 3-6 However, all of these schemes included prior emergency hospital utilization as an important compo- nent of the risk prediction algorithm. Computerized pharmacy data are becoming increasingly available, but frequently they are not linked to hospital utilization data. Even if utilization data that could be linked to phar- macy data were available, it would be simpler to be able to use only 1 computer system for risk stratification. We are aware of 3 prior studies that attempted to pre- dict subsequent emergency hospital care based on strat- ification of computerized pharmacy data. Two were published only in abstract form, 7,8 and the other one was not validated in a separate population. 9 Thus, we thought it would be important to develop and validate a risk stratification scheme based on computerized phar- macy data alone that would predict subsequent emer- gency hospital utilization and identify patients for targeted intervention. In addition, we compared the per- formance of this medication-derived scale with that of a previously validated scale that included baseline emer- gency hospital utilization as well as pharmacy data. 6 METHODS This study is a retrospective cohort database study using 1 sample (the development sample) to develop the risk stratification scheme and a separate sample (the Development and Validation of a Medication Intensity Scale Derived From Computerized Pharmacy Data That Predicts Emergency Hospital Utilization for Persistent Asthma Michael Schatz, MD; Robert S. Zeiger, MD, PhD; William M. Vollmer, PhD; David Mosen, PhD; Andrea J. Apter, MD; Thomas B. Stibolt, MD; Albin Leong, MD; Michael S. Johnson, MS; Guillermo Mendoza, MD; and E. Francis Cook, ScD Objective: To validate a risk stratification scheme using comput- erized pharmacy data to predict emergency hospital utilization for persistent asthma. Study Design: Retrospective cohort. Methods: The development sample consisted of 1079 HMO members aged 18 to 56 years with persistent asthma. The scale used medication cut-points as predictors for next-year emergency hospi- tal utilization in a stepwise logistic regression model. Prediction properties were evaluated in a validation sample of 24 370 patients aged 18 to 56 years in a separate persistent-asthma database. Results: Increasing use of β-agonists (odds ratio [OR] of 2.2 for 5-13 vs 0-4 canisters; OR of 2.4 for >13 vs 5-13 canisters) and oral corticosteroids (OR of 2.6 for >2 vs 0-2 dispensing events) in the first year independently predicted emergency hospital utilization in the second year. Assigning 1 point for exceeding each of the above 3 medication thresholds led to a 4-level medication intensity scale that was significantly (P < .0001) related to validated measures of asthma symptom severity, asthma control, and asthma quality of life in the development sample. In the validation sample, this scheme identified a high-risk group that was 6 times more likely than the low-risk group to require subsequent emergency hospital care, with overall sensitivity of 65% and specificity of 54%. This scale did not perform as well as a scale based on both baseline emergency hospital care and pharmacy data. Conclusion: This simple risk stratification scheme can be used for populations with persistent asthma for whom computerized pharmacy data, but not computerized prior utilization data, are available. (Am J Manag Care. 2006;12:478-484) From the Departments of Allergy at San Diego (MS, RSZ), Sacramento (AL), and Vacaville (GM), Calif, the Center for Health Research, Portland, Ore (WMV), and the Care Management Institute, Oakland, Calif (DM, TBS, MSJ), Kaiser Permanente Medical Care Program; the Division of Allergy-Immunology, Department of Pulmonary and Critical Care Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pa (AJA); and the Department of Epidemiology, Harvard School of Public Health, Boston, Mass (EFC). This research was supported by the Kaiser Permanente Medical Care Program. Address correspondence to: Michael Schatz, MD, Chief, Department of Allergy, Kaiser Permanente Medical Center, 7060 Clairemont Mesa Blvd, San Diego, CA 92111. E-mail: michael.x.schatz@kp.org.