Prognostic data-driven clinical decision support-Formulation and implications

Rinott, Ruty; Carmeli, Boaz; Kent, Carmel; Landau, Daphna; Maman, Yonatan; Rubin, Yoav and Slonim, Noam (2011). Prognostic data-driven clinical decision support-Formulation and implications. In: Moen, Anne; Andersen, Stig Kjær; Aarts, Jos and Hurlen, Petter eds. User Centred Networked Health Care, Volume 169. IOS Press, pp. 140–144.

DOI: https://doi.org/10.3233/978-1-60750-806-9-140

Abstract

Existing Clinical Decision Support Systems (CDSSs) typically rely on rule-based algorithms and focus on tasks like guidelines adherence and drug prescribing and monitoring. However, the increasing dominance of Electronic Health Record technologies and personalized medicine suggest great potential for prognostic data-driven CDSS. A major goal for such systems would be to accurately predict the outcome of patients' candidate treatments by statistical analysis of the clinical data stored at a Health Care Organization. We formally define the concepts involved in the development of such a system, highlight an inherent difficulty arising from bias in treatment allocation, and propose a general strategy to address this difficulty. Experiments over hypertension clinical data demonstrate the validity of our approach. ? 2011 European Federation for Medical Informatics. All rights reserved.

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