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PharmacoEconomics

, Volume 27, Issue 2, pp 167–177 | Cite as

Challenges in Merging Medicaid and Medicare Databases to Obtain Healthcare Costs for Dual-Eligible Beneficiaries

Using Diabetes as an Example
  • Cecilia M. Prela
  • Greg A. Baumgardner
  • Gayle E. Reiber
  • Lynne V. McFarland
  • Charles Maynard
  • Nancy Anderson
  • Matthew Maciejewski
Original Research Article

Abstract

Background: Dual-eligible Medicaid-Medicare beneficiaries represent a group of people who are in the lowest income bracket in the US, have numerous co-morbidities and place a heavy financial burden on the US healthcare system. As cost-effectiveness analyses are used to inform national policy decisions and to determine the value of implemented chronic disease control programmes, it is imperative that complete and valid determination of healthcare utilization and costs can be obtained from existing state and federal databases. Differences and inconsistencies between the Medicaid and Medicare databases have presented significant challenges when extracting accurate data for dual-eligible beneficiaries.

Objectives: To describe the challenges inherent in merging Medicaid and Medicare claims databases and to present a protocol that would allow successful linkage between these two disparate databases.

Methods: Healthcare claims and costs were extracted from both Medicaid and Medicare databases for King County, Seattle, WA, USA. Three Medicaid files were linked to eight Medicare files for unique dual-eligible beneficiaries with type 2 diabetes mellitus.

Results: Although major differences were identified in how variables and claims were defined in each database, our method enabled us to link these two different databases to compile a complete and accurate assessment of healthcare use and costs for dual-eligible beneficiaries with a costly chronic condition. For example, of the 1759 dual-eligible beneficiaries with diabetes, the average cost of healthcare was $US15 981 per capita, with an average of 76 claims per person per year.

Conclusion: The resulting merged database provides a virtually complete documentation of both utilization and costs of medical care for a population who receives coverage from two different programmes. By identifying differences and implementing our linkage protocol, the merged database serves as a foundation for a broad array of analyses on healthcare use and costs for effectiveness research.

Keywords

Healthcare Utilization Medicaid Programme Skilled Nursing Facility Social Security Number King County 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The analyses upon which this publication is based were performed under contract number 500-99-WA02, funded by the Centers for Medicare & Medicaid Services, an agency of the US Department of Health and Human Services. Additional funding was from the Sandy MacColl Foundation, Seattle, Washington; The Robert Wood Johnson Foundation, Princeton, New York; Adventis Pharmaceuticals Inc. and Washington State Department of Health.

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the Department of Health and Human Services. The authors assume full responsibility for the accuracy and completeness of the ideas presented.

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Copyright information

© Adis Data Information BV 2009

Authors and Affiliations

  • Cecilia M. Prela
    • 1
  • Greg A. Baumgardner
    • 2
  • Gayle E. Reiber
    • 3
  • Lynne V. McFarland
    • 3
  • Charles Maynard
    • 3
  • Nancy Anderson
    • 4
  • Matthew Maciejewski
    • 5
  1. 1.Centers for Medicare and Medicaid Services, Medicare Plan Payment GroupDivision of Risk AdjustmentBaltimoreUSA
  2. 2.Data Analysis TeamQualis HealthSeattleUSA
  3. 3.Health Services Research and DevelopmentDepartment of Veterans Affairs Puget Sound Healthcare SystemSeattleUSA
  4. 4.Medical Assistance AdministrationOlympiaUSA
  5. 5.University of North CarolinaChapel HillUSA

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