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[Methodological Challenges and Lessons Learned in the Scientific Use of Data from a Private Health Insurance Company within the IPHA Project].

Katharina AchstetterJulia KöppenPhilipp HengelUlrike NimptschMiriam Blümel
Published in: Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) (2021)
The 11% of people with private health insurance (PHI) in Germany have so far been underrepresented in health services research. The scientific use of PHI data is rare. The aim of this research was to examine the scientific usability of PHI data and to highlight challenges and lessons learned in the process of data preparation and analysis using a linked dataset (n=3,109) of survey and claims data of one PHI company. Challenges were identified in the terminology of the PHI insurance, in the processing and validity of the data, and regarding insured persons without submitted billing receipts. With thorough preparation of the data and presentation of the limitations, PHI data can be used for health services research.
Keyphrases
  • health insurance
  • electronic health record
  • big data
  • affordable care act
  • healthcare
  • machine learning
  • mass spectrometry
  • deep learning
  • cross sectional
  • liquid chromatography