How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy / A.H. Morris, C. Horvat, B. Stagg, D.W. Grainger, M. Lanspa, J. Orme, T.P. Clemmer, L.K. Weaver, F.O. Thomas, C.K. Grissom, E. Hirshberg, T.D. East, C.J. Wallace, M.P. Young, D.F. Sittig, M. Suchyta, J.E. Pearl, A. Pesenti, M. Bombino, E. Beck, K.A. Sward, C. Weir, S. Phansalkar, G.R. Bernard, B.T. Thompson, R. Brower, J. Truwit, J. Steingrub, R.D. Hiten, D.F. Willson, J.J. Zimmerman, V. Nadkarni, A.G. Randolph, M.A.Q. Curley, C.J.L. Newth, J. Lacroix, M.S.D. Agus, K.H. Lee, B.P. Deboisblanc, F.A. Moore, R.S. Evans, D.K. Sorenson, A. Wong, M.V. Boland, W.H. Dere, A. Crandall, J. Facelli, S.M. Huff, P.J. Haug, U. Pielmeier, S.E. Rees, D.S. Karbing, S. Andreassen, E. Fan, R.M. Goldring, K.I. Berger, B.W. Oppenheimer, E.W. Ely, B.W. Pickering, D.A. Schoenfeld, I. Tocino, R.S. Gonnering, P.J. Pronovost, L.A. Savitz, D. Dreyfuss, A.S. Slutsky, J.D. Crapo, M.R. Pinsky, B. James, D.M. Berwick. - In: JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION. - ISSN 1067-5027. - 30:1(2022 Sep 19), pp. 178-194. [Epub ahead of print] [10.1093/jamia/ocac143]

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

A. Pesenti;
2022

Abstract

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.
automated clinical care; clinical; clinicians; closed-loop; computers; decision-support
Settore MED/41 - Anestesiologia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/944823
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