title: Development and validation of a medication intensity scale derived from computerized pharmacy data that predicts emergency hospital utilization for persistent asthma.
abstract: OBJECTIVE
  To validate a risk stratification scheme using computerized pharmacy data to predict emergency hospital utilization for persistent asthma.
  
  
  METHODS
  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 hospital 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 beta-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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Kaiser Permanente Medical Center, 7060 Clairemont Mesa Blvd, San Diego, CA 92111, USA. michael.x.schatz@kp.org
authors.forename: Michael
authors.initials: M
authors.lastname: Schatz
authors.forename: Robert S
authors.initials: RS
authors.lastname: Zeiger
authors.forename: William M
authors.initials: WM
authors.lastname: Vollmer
authors.forename: David
authors.initials: D
authors.lastname: Mosen
authors.forename: Andrea J
authors.initials: AJ
authors.lastname: Apter
authors.forename: Thomas B
authors.initials: TB
authors.lastname: Stibolt
authors.forename: Albin
authors.initials: A
authors.lastname: Leong
authors.forename: Michael S
authors.initials: MS
authors.lastname: Johnson
authors.forename: Guillermo
authors.initials: G
authors.lastname: Mendoza
authors.forename: E Francis
authors.initials: EF
authors.lastname: Cook
mesh_terms: D000293:Adolescent; D000328:Adult; D018927:Anti-Asthmatic Agents / Q000627:therapeutic use; D001249:Asthma / Q000188:drug therapy*; D002908:Chronic Disease; D015331:Cohort Studies; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D019601:Pacific States; D010593:Pharmaceutical Services; D012189:Retrospective Studies
chemical_list: D018927:Anti-Asthmatic Agents