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Key considerations when using health insurance claims data in advanced data analyses: an experience report

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  • Renata Konrad
  • Wenchang Zhang
  • Margrét Bjarndóttir
  • Ruben Proaño

Abstract

Health claims have become a popular source of data for healthcare analytics, with numerous applications ranging from disease burden estimation and policy evaluation to drug event detection and advanced predictive analytics. Independent of the application, a researcher utilising claims information will likely encounter challenges in using the data, which include dealing with several coding systems and coding irregularities. We highlight some of these challenges and approaches for successful analysis that may reduce implementation time and help in avoiding common pitfalls. We describe the experiences of a group of academic researchers in using an extensive seven-year repository of US medical and pharmaceutical claims data in a research study, and provide an overview of the challenges encountered with handling claims records for data analysis while sharing suggestions on how to address these challenges. To illustrate our experiences, we use the example of defining episodes of care for a bundled payment reimbursement system in the US context.

Suggested Citation

  • Renata Konrad & Wenchang Zhang & Margrét Bjarndóttir & Ruben Proaño, 2020. "Key considerations when using health insurance claims data in advanced data analyses: an experience report," Health Systems, Taylor & Francis Journals, vol. 9(4), pages 317-325, October.
    • Handle: RePEc:taf:thssxx:v:9:y:2020:i:4:p:317-325
    DOI: 10.1080/20476965.2019.1581433
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    Cited by:

    1. Weziak-Bialowolska, Dorota & Lee, Matthew T. & Cowden, Richard G. & Bialowolski, Piotr & Chen, Ying & VanderWeele, Tyler J. & McNeely, Eileen, 2023. "Psychological caring climate at work, mental health, well-being, and work-related outcomes: Evidence from a longitudinal study and health insurance data," Social Science & Medicine, Elsevier, vol. 323(C).

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