Personalization in biomedical-informatics: Methodological considerations and recommendations

Maurits Kaptein*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Over the last decades there has been an increasing interest in personalization: can we make sure that treatments are effective for individual patients? The quest for personalization affects biomedical informatics in two ways: first, we design systems—for example eHealth applications—that directly interact with patients and these systems might themselves one day be personalized. Hence, we seek effective methods to do so. Second, we design systems that collect the data which will one day be used to personalize treatments: hence, we need to critically consider design requirements that improve the utility of (e.g.,) personal health records for future treatment personalization. By clearly defining personalization and analyzing the effectiveness of different personalization methods this discussion highlights how we should embrace sequential experimentation—as opposed to the traditional randomized trial—if we want to personalize our informatics systems efficiently. Furthermore, we need to make sure that we capture the treatment assignment process in our health records: doing so will greatly increase the utility of the collected data for future personalization attempts.
Original languageEnglish
Article number103088
Number of pages7
JournalJournal of Biomedical Informatics
Volume90
DOIs
Publication statusPublished - 2019

Keywords

  • DOUBLY ROBUST ESTIMATION
  • FRAMEWORK
  • Health information systems
  • INFERENCE
  • MODEL
  • Personal health records
  • Personalization
  • Research methods
  • Sequential experimentation

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