Health Recommender Systems: Concepts, Requirements, Technical Basics and Challenges

Martin Wiesner and Daniel Pfeifer
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Martin Wiesner: Department of Medical Informatics, Heilbronn University, Max-Planck-Str. 39, Heilbronn 74081, Germany
Daniel Pfeifer: Department of Medical Informatics, Heilbronn University, Max-Planck-Str. 39, Heilbronn 74081, Germany

IJERPH, 2014, vol. 11, issue 3, 1-28

Abstract: During the last decades huge amounts of data have been collected in clinical databases representing patients’ health states (e.g., as laboratory results, treatment plans, medical reports). Hence, digital information available for patient-oriented decision making has increased drastically but is often scattered across different sites. As as solution, personal health record systems (PHRS) are meant to centralize an individual’s health data and to allow access for the owner as well as for authorized health professionals. Yet, expert-oriented language, complex interrelations of medical facts and information overload in general pose major obstacles for patients to understand their own record and to draw adequate conclusions. In this context, recommender systems may supply patients with additional laymen-friendly information helping to better comprehend their health status as represented by their record. However, such systems must be adapted to cope with the specific requirements in the health domain in order to deliver highly relevant information for patients. They are referred to as health recommender systems (HRS). In this article we give an introduction to health recommender systems and explain why they are a useful enhancement to PHR solutions. Basic concepts and scenarios are discussed and a first implementation is presented. In addition, we outline an evaluation approach for such a system, which is supported by medical experts. The construction of a test collection for case-related recommendations is described. Finally, challenges and open issues are discussed.

Keywords: health recommender systems; information needs; personal health record; personalized medicine; health information seeking; Internet; relevance computation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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