Quantifying the Physician Contribution to Managed Care Pharmacy Expenses

BACKGROUND: Despite the availability of more sophisticated techniques, few alternatives to ordinary least squares (OLS) regression have been utilized to profile physician prescribing in managed care. It is not known to what extent the modest R values derived from OLS models reflect incomplete risk adjustment or widely varying physician prescribing patterns. OBJECTIVES: To quantify the role of interphysician variability relative to overall variability in managed care pharmacy expenses, and to examine the extent to which different statistical approaches generate meaningful differences in profile results. RESEARCH DESIGN: Comparison of three basic statistical modeling approaches: OLS, fixed effects regression, and random effects (ie, hierarchical) regression models. SETTING: Two managed care populations that differed more than 2-fold in per member pharmacy expenditures in 1999, one from the Midwestern United States, the other from three Western States. MAIN OUTCOME MEASURES: The intraclass correlation coefficient (ICC, the proportion of variability in expenses attributable to differences among physicians) and the range of projected expenses attributed to each physician's prescribing style. RESULTS: The ICCs were small for aggregated pharmacy expenditures, 0.04 or less in both populations. As determined by OLS, the most costly physician contributed 94,399 U.S. dollars in excess expenses to the organization whereas the most parsimonious saved 89,940 U.S. dollars. When derived from random effects models, the range in performance was 63% of that derived from OLS. CONCLUSIONS: In the populations studied, systematic prescribing differences among physicians were small relative to the overall variability in pharmacy expenses, suggesting other factors were more likely driving these costs. Random effects models generated smaller estimates of the individual physicians' contribution to costs, sometimes considerably, relative to those derived from OLS and fixed effects approaches

Actuarial science · Business · Econometrics · Economics · Family medicine · Health care · Intraclass correlation · Linear regression · Managed care · Multilevel model · Ordinary least squares · Random effects model · Regression · Regression analysis · Statistics · Economic and Financial Impacts of Cancer · Healthcare Policy and Management · Mathematics · Medication Adherence and Compliance · Medicine · Pharmacy

• Efforts to Better Understand Pharmaceutical Use, Costs, and Outcome

  Julie M Zito•Medical Care•2002

  Añadir item

• Meaningful Variation in Performance

  Joseph V Selby, Julie A Schmittdiel et al.•Medical Care•2010

  Añadir item

• Meaningful Variation in Performance

  Vicki Fung, Julie A Schmittdiel et al.•Medical Care•2010

  Añadir item

• Random-Effects Models for Longitudinal Data

  Nan M Laird, James H Ware•Biometrics•1982

  Añadir item

• Adverse Events Associated With Prescription Drug Cost-Sharing Among Poor and Elderly Persons

  Robyn Tamblyn•JAMA•2001

  Añadir item

• Regression Analysis for Correlated Data

  K Y Liang, Kung‐Yee Liang et al.•Annual Review of Public Health•1993

  Añadir item

• Consistency in Performance Among Primary Care Practitioners

  R Heather Palmer, ELIZABETH A WRIGHT et al.•Medical Care•1996

  Añadir item

• The Medicaid Rx Model

  Todd Gilmer, Richard Kronick et al.•Medical Care•2001

  Añadir item

• Estimating Physician Costliness

  Michael E Miller, Siu L Hui et al.•Medical Care•1993

  Añadir item

• Variations in the Utilization of Coronary Angiography for Elderly Patients with an Acute Myocardial Infarction

  Constantine Gatsonis, Constantine A Gatsonis et al.•Medical Care•1995

  Añadir item

• Casemix Adjustment of Managed Care Claims Data Using the Clinical Classification for Health Policy Research Method

  Open Access•Mark E Cowen, David J Dusseau et al.•Medical Care•1998

  Añadir item

• Issues of Variability and Bias Affecting Multisite Measurement of Quality of Care

  Endel John Orav, ELIZABETH A WRIGHT et al.•Medical Care•1996

  Añadir item