Toward patient-centered, personalized and personal decision support and knowledge management: a survey.
OBJECTIVE
This paper summarizes the recent trends and highlights the challenges and opportunities in decision support and knowledge management for patient-centered, personalized, and personal health care.


METHODS
The discussions are based on a broad survey of related references, focusing on the most recent publications. Major advances are examined in the areas of i) shared decision making paradigms, ii) continuity of care infrastructures and architectures, iii) human factors and system design approaches, iv) knowledge management innovations, and v) practical deployment and change considerations.


RESULTS
Many important initiatives, projects, and plans with promising results have been identified. The common themes focus on supporting the individual patients who are playing an increasing central role in their own care decision processes. New collaborative decision making paradigms and information infrastructures are required to ensure effective continuity of care. Human factors and usability are crucial for the successful development and deployment of the relevant systems, tools, and aids. Advances in personalized medicine can be achieved through integrating genomic, phenotypic and other biological, individual, and population level information, and gaining useful insights from building and analyzing biological and other models at multiple levels of abstraction. Therefore, new Information and Communication Technologies and evaluation approaches are needed to effectively manage the scale and complexity of biomedical and health information, and adapt to the changing nature of clinical decision support.


CONCLUSIONS
Recent research in decision support and knowledge management combines heterogeneous information and personal data to provide cost-effective, calibrated, personalized support in shared decision making at the point of care. Current and emerging efforts concentrate on developing or extending conventional paradigms, techniques, systems, and architectures for the new predictive, preemptive, and participatory health care model for patient-centered, personalized medicine. There is also an increasing emphasis on managing complexity with changing care models, processes, and settings.
Medical Computing Laboratory, School of Computing, National University of Singapore, Computing 1, 13 Computing Drive, Singapore 117417. E-mail: leongty@comp.nus.edu.sg.
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Leong
D003299:Cooperative Behavior; D020000:Decision Support Systems, Clinical; D003695:Delivery of Health Care; D006801:Humans; D058436:Knowledge Management; D018802:Patient-Centered Care; D057285:Precision Medicine; D011795:Surveys and Questionnaires