OBJECTIVES: The purpose of this paper is to examine past and present medical decision support systems and the environment in which they operate and to propose specific research tracks that improve integration and adoption of these systems in today's health care systems. METHODS: In preamble, we examine the objectives, decision models, and performances of past decision support systems. RESULTS: Medical decision support tools were essentially formulated from a technical capability perspective and this view has met limited adoption and slowed down new development as well as integration of these important systems into patient management work flows and clinical information systems. The science base of these systems needs to include evidence-based medicine and clinical practice guidelines and the paradigms need to be extended to include a collaborative provider model, the users and the organization perspectives. The availability of patient record and medical terminology standards is essential to the dissemination of decision support systems and so is their integration into the care process. CONCLUSION: To build new decision support systems based on practice guidelines and taking into account users preferences, we do not so much advocate new technological solutions but rather suggest that technology is not enough to ensure successful adoption by the users, the integration into practice workflow, and consequently, the realisation of improved health care outcomes.
OBJECTIVES: The purpose of this paper is to examine past and present medical decision support systems and the environment in which they operate and to propose specific research tracks that improve integration and adoption of these systems in today's health care systems. METHODS: In preamble, we examine the objectives, decision models, and performances of past decision support systems. RESULTS: Medical decision support tools were essentially formulated from a technical capability perspective and this view has met limited adoption and slowed down new development as well as integration of these important systems into patient management work flows and clinical information systems. The science base of these systems needs to include evidence-based medicine and clinical practice guidelines and the paradigms need to be extended to include a collaborative provider model, the users and the organization perspectives. The availability of patient record and medical terminology standards is essential to the dissemination of decision support systems and so is their integration into the care process. CONCLUSION: To build new decision support systems based on practice guidelines and taking into account users preferences, we do not so much advocate new technological solutions but rather suggest that technology is not enough to ensure successful adoption by the users, the integration into practice workflow, and consequently, the realisation of improved health care outcomes.
Authors: Samson W Tu; James R Campbell; Julie Glasgow; Mark A Nyman; Robert McClure; James McClay; Craig Parker; Karen M Hrabak; David Berg; Tony Weida; James G Mansfield; Mark A Musen; Robert M Abarbanel Journal: J Am Med Inform Assoc Date: 2007-06-28 Impact factor: 4.497
Authors: Petra Welter; Thomas M Deserno; Benedikt Fischer; Rolf W Günther; Cord Spreckelsen Journal: BMC Med Inform Decis Mak Date: 2011-10-27 Impact factor: 2.796
Authors: Nathan Mensah; Felix Sukums; Timothy Awine; Andreas Meid; John Williams; Patricia Akweongo; Jens Kaltschmidt; Walter E Haefeli; Antje Blank Journal: Glob Health Action Date: 2015-01-27 Impact factor: 2.640