Donald J Bachman

• Risk Adjustment Using Automated Ambulatory Pharmacy Data

  Paul Fishman, Paul A Fishman et al.•ARTICLE•Medical Care•2003•Referências: 14

  Incluir item

  OBJECTIVES: Develop and estimate the RxRisk model, a risk assessment instrument that uses automated ambulatory pharmacy data to identify chronic conditions and predict future health care cost. The RxRisk model's performance in predicting cost is compared with a demographic-only model, the Ambulatory Clinical Groups (ACG), and Hierarchical Coexisting Conditions (HCC) ICD-9-CM diagnosis-based risk assessment instruments. Each model's power to forec…

• Using Risk-Adjustment Models to Identify High-Cost Risks

  Richard T Meenan, Michael J Goodman et al.•ARTICLE•Medical Care•2003•Referências: 7

  Incluir item

  BACKGROUND: We examine the ability of various publicly available risk models to identify high-cost individuals and enrollee groups using multi-HMO administrative data. METHODS: Five risk-adjustment models (the Global Risk-Adjustment Model [GRAM], Diagnostic Cost Groups [DCGs], Adjusted Clinical Groups [ACGs], RxRisk, and Prior-expense) were estimated on a multi-HMO administrative data set of 1.5 million individual-level observations for 1995-1996…

• The Sensitivity and Specificity of Forecasting High-Cost Users of Medical Care

  Richard T Meenan, Maureen C O'Keeffe-Rosetti et al.•ARTICLE•Medical Care•1999•Referências: 7

  Incluir item

  OBJECTIVES: This study compares the ability of 3 risk-assessment models to distinguish high and low expense-risk status within a managed care population. Models are the Global Risk-Assessment Model (GRAM) developed at the Kaiser Permanente Center for Health Research; a logistic version of GRAM; and a prior-expense model. GRAM was originally developed for use in adjusting Medicare payments to health plans. METHODS: Our sample of 98,985 cases was d…

• The Sensitivity and Specificity of Forecasting High-Cost Users of Medical Care

  Richard T Meenan, Maureen C O'Keeffe-Rosetti et al.•ARTICLE•Medical Care•1999•Referências: 7

  Incluir item

  OBJECTIVES: This study compares the ability of 3 risk-assessment models to distinguish high and low expense-risk status within a managed care population. Models are the Global Risk-Assessment Model (GRAM) developed at the Kaiser Permanente Center for Health Research; a logistic version of GRAM; and a prior-expense model. GRAM was originally developed for use in adjusting Medicare payments to health plans. METHODS: Our sample of 98,985 cases was d…

• Risk Adjustment Using Automated Ambulatory Pharmacy Data

  Paul Fishman, Paul A Fishman et al.•ARTICLE•Medical Care•2003•Referências: 14

  Incluir item

  OBJECTIVES: Develop and estimate the RxRisk model, a risk assessment instrument that uses automated ambulatory pharmacy data to identify chronic conditions and predict future health care cost. The RxRisk model's performance in predicting cost is compared with a demographic-only model, the Ambulatory Clinical Groups (ACG), and Hierarchical Coexisting Conditions (HCC) ICD-9-CM diagnosis-based risk assessment instruments. Each model's power to forec…

• Using Risk-Adjustment Models to Identify High-Cost Risks

  Richard T Meenan, Michael J Goodman et al.•ARTICLE•Medical Care•2003•Referências: 7

  Incluir item

  BACKGROUND: We examine the ability of various publicly available risk models to identify high-cost individuals and enrollee groups using multi-HMO administrative data. METHODS: Five risk-adjustment models (the Global Risk-Adjustment Model [GRAM], Diagnostic Cost Groups [DCGs], Adjusted Clinical Groups [ACGs], RxRisk, and Prior-expense) were estimated on a multi-HMO administrative data set of 1.5 million individual-level observations for 1995-1996…

Health care (3 obras) · Medicine (3 obras) · Actuarial science (2 obras) · Business (2 obras) · Health Systems, Economic Evaluations, Quality of Life (2 obras) · Healthcare Policy and Management (2 obras) · Mathematics (2 obras) · Statistics (2 obras) · Ambulatory (1 obras) · Ambulatory care (1 obras)