USE OF UB-92S AND MEDICARE COST REPORTS IN LARGE, MULTI-CENTER RANDOMIZED TRIAL- THE PURSUIT EXPERIENCE

Author(s)

Davidson-Ray L, Buell H, O’Neal B, McElwee N, Mark DB. Duke Clinical Research Institute, Durham, NC. Schering-Plough, Corp, Kenilworth, NJ, USA

Background: The conversion of hospital bill charges using Uniform Bill (UB)-92s and Medicare Ratios of Cost to Charges (RCCs) to costs in economic analyses is one of the most efficient, accurate and accessible ways of measuring resource consumption for US hospitalizations. Objectives: We used the hospital bill charge to cost conversion method in our analysis of over 3000 patients with 4700 hospital bills in the recently completed PURSUIT pharmacoeconomic substudy. Using the PURSUIT trial experience as a model, this workshop will provide a detailed explanation of the cost to charge conversion methodology. We will begin with a detailed procedure for incorporating this method of cost collection into a clinical trial’s overall protocol and case report form. We will explain how to ensure collection of bills for all patient hospitalizations and procedures; how to interpret the UB-92; how to extract charges from the UB-92 and convert those charges into costs using each hospital’s Medicare Ratio of Cost to Charges. This workshop will also explore mechanisms for ensuring successful compliance across sites in large, randomized clinical trials including inservice training for coordinators and common obstacles to successful and complete collection. In addition, the workshop will explore the limitations and strengths of this method compared with other cost collection methods. This workshop will be particularly useful to project leaders, clinical trial coordinators and database managers interested in performing economic analyses as part of larger clinical trials or as stand-alone endeavors.

Conference/Value in Health Info

1998-05, ISPOR 1998, Philadelphia, PA, USA

Value in Health, Vol. 1, No. 1 (May/June 1998)

Code

CM4

Topic

Real World Data & Information Systems

Topic Subcategory

Health & Insurance Records Systems

Disease

Multiple Diseases

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