Producing comparable cost and quality results from all-payer claims databases

Am J Manag Care. 2019 May 1;25(5):e138-e144.

Abstract

Objectives: To describe how all-payer claims databases (APCDs) can be used for multistate analysis, evaluating the feasibility of overcoming the common barrier of a lack of standardization across data sets to produce comparable cost and quality results for 4 states. This study is part of a larger project to better understand the cost and quality of healthcare services across delivery organizations.

Study design: Descriptive account of the process followed to produce healthcare quality and cost measures across and within 4 regional APCDs.

Methods: Partners from Colorado, Massachusetts, Oregon, and Utah standardized the calculations for a set of cost and quality measures using 2014 commercial claims data collected in each state. This work required a detailed understanding of the data sets, collaborative relationships with each other and local partners, and broad standardization. Partners standardized rules for including payers, data set elements, measure specifications, SAS code, and adjustments for population differences in age and gender.

Results: This study resulted in the development of a Uniform Data Structure file format that can be scaled across populations, measures, and research dimensions to provide a consistent method to produce comparable findings.

Conclusions: This study demonstrates the feasibility of using state-based claims data sets and standardized processes to develop comparable healthcare performance measures that inform state, regional, and organizational healthcare policy.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Colorado
  • Costs and Cost Analysis / statistics & numerical data*
  • Databases as Topic
  • Female
  • Humans
  • Information Dissemination
  • Insurance Claim Reporting / economics
  • Insurance Claim Reporting / statistics & numerical data*
  • Insurance Claim Review / economics
  • Insurance Claim Review / organization & administration*
  • Insurance, Health / economics
  • Insurance, Health / statistics & numerical data*
  • Insurance, Health, Reimbursement / economics
  • Insurance, Health, Reimbursement / statistics & numerical data*
  • Male
  • Massachusetts
  • Oregon
  • Utah