DOCUMENTS

papers

Explaining prescription drug use and expenditures using the Adjusted Clinical Groups case-mix system in the population of British Columbia, Canada

Published: May 1, 2010
Category: Papers
Authors: Hanley GE, Morgan S, Reid RJ
Country: Canada
Language: null
Type: Population Health
Setting: Academic

Med Care 48:402-408.

Centre for Health Services and Policy Research, University of British Columbia, School of Population and Public Health, Vancouver, BC, Canada

BACKGROUND: Given that prescription drugs have become a major financial component of health care, there is an increased need to explain variations in the use of and expenditure on medicines. Case-mix systems built from existing administrative datasets may prove very useful for such prediction.

OBJECTIVE: We estimated the concurrent and prospective predictive validity of the adjusted clinical groups (ACG) system in pharmaceutical research and compared the ACG system with the Charlson index of comorbidity.

RESEARCH DESIGN: We ran a generalized linear models to examine the predictive validity of the ACG system and the Charlson index and report the correlation between the predicted and observed expenditures. We reported mean predictive ratios across medical condition and cost-defined groups. When predicting use of medicines, we used C-statistics to summarize the area under the receiver operating characteristic curve.

SUBJECTS: The 3,908,533 British Columbia residents who were registered for the universal health care plan for 275+ days in the calendar years 2004 and 2005.

MEASURES: Outcomes were total pharmaceutical expenditures, use of any medicines, and use of medicines from 4+ different therapeutic categories.

RESULTS: The ACG case mix system predicted drug expenditures better than the Charlson index. The mean predictive ratios for the ACG system models were all within 4% of the actual costs when examining medical condition group and the C-stats for the 2 dichotomous outcomes were between 0.82 and 0.89.

CONCLUSION: ACG case-mix adjusters are a valuable predictor of pharmaceutical use and expenditures with much higher predictive power than age, sex, and the Charlson index of comorbidity.

PMID: 20393369

Prescription Drug Use and Expenditures,Canada,Co-morbidity,Medical Conditions,Predictive Risk Modeling,Adolescent,Adult,Age Factors,British Columbia,Child,Cohort Studies,Drug Utilization,Gender,International Classification of Diseases,Linear Models,Middle Aged,Sex Factors,Young Adult

Please log in/register to access.

Log in/Register

© The Johns Hopkins University, The Johns Hopkins Hospital, and Johns Hopkins Health System.
All rights reserved. Terms of Use Privacy Statement

Back to top