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Personalization in biomedical-informatics: Methodological considerations and recommendations.

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Personalization in healthcare requires new methods. Embracing sequential experimentation and capturing treatment data in health records are key for effective personalized informatics systems.

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Area of Science:

  • Biomedical Informatics
  • Health Informatics
  • Personalized Medicine

Background:

  • Increasing interest in personalized treatments to ensure efficacy for individual patients.
  • Personalization impacts biomedical informatics through patient-facing systems (e.g., eHealth) and data collection for future treatment personalization.
  • Need for effective methods to personalize informatics systems and enhance the utility of personal health records.

Purpose of the Study:

  • To define personalization and analyze the effectiveness of different personalization methods.
  • To highlight the importance of sequential experimentation for efficient personalization of informatics systems.
  • To emphasize the need for capturing treatment assignment processes in health records for future personalization.

Main Methods:

  • Analysis of personalization methods in biomedical informatics.
  • Comparison of sequential experimentation with traditional randomized trials for personalization.
  • Review of design requirements for personal health records to support treatment personalization.

Main Results:

  • Sequential experimentation is more efficient for personalizing informatics systems than traditional randomized trials.
  • Capturing the treatment assignment process in health records significantly enhances data utility for future personalization.
  • Clear definition and analysis of personalization methods are crucial.

Conclusions:

  • Adopt sequential experimentation for efficient personalization of informatics systems.
  • Ensure health records capture treatment assignment for improved future personalization.
  • Develop robust methods for personalizing eHealth applications and utilizing collected data.