Literature DB >> 25715002

Knowledge bases, clinical decision support systems, and rapid learning in oncology.

Peter Paul Yu1.   

Abstract

One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care.
Copyright © 2015 by American Society of Clinical Oncology.

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Year:  2015        PMID: 25715002     DOI: 10.1200/JOP.2014.000620

Source DB:  PubMed          Journal:  J Oncol Pract        ISSN: 1554-7477            Impact factor:   3.840


  8 in total

1.  Implementation of Clinical Practice Guidelines in the Health Care Setting: A Concept Analysis.

Authors:  Melissa Beauchemin; Elizabeth Cohn; Rachel C Shelton
Journal:  ANS Adv Nurs Sci       Date:  2019 Oct/Dec       Impact factor: 1.824

2.  All together now: findings from a PCORI workshop to align patient-reported outcomes in the electronic health record.

Authors:  Roxanne E Jensen; Claire F Snyder; Ethan Basch; Lori Frank; Albert W Wu
Journal:  J Comp Eff Res       Date:  2016-09-02       Impact factor: 1.744

3.  Can Big Data guide prognosis and clinical decisions in epilepsy?

Authors:  Xiaojin Li; Licong Cui; Guo-Qiang Zhang; Samden D Lhatoo
Journal:  Epilepsia       Date:  2021-02-02       Impact factor: 5.864

Review 4.  Clinical Decision Support Systems.

Authors:  Andreas Teufel; Harald Binder
Journal:  Visc Med       Date:  2021-09-28

Review 5.  Decision Support Systems in Oncology.

Authors:  Seán Walsh; Evelyn E C de Jong; Janna E van Timmeren; Abdalla Ibrahim; Inge Compter; Jurgen Peerlings; Sebastian Sanduleanu; Turkey Refaee; Simon Keek; Ruben T H M Larue; Yvonka van Wijk; Aniek J G Even; Arthur Jochems; Mohamed S Barakat; Ralph T H Leijenaar; Philippe Lambin
Journal:  JCO Clin Cancer Inform       Date:  2019-02

6.  AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research.

Authors:  Tamra Lysaght; Hannah Yeefen Lim; Vicki Xafis; Kee Yuan Ngiam
Journal:  Asian Bioeth Rev       Date:  2019-09-12

7.  Workflow-driven clinical decision support for personalized oncology.

Authors:  Anca Bucur; Jasper van Leeuwen; Nikolaos Christodoulou; Kamana Sigdel; Katerina Argyri; Lefteris Koumakis; Norbert Graf; Georgios Stamatakos
Journal:  BMC Med Inform Decis Mak       Date:  2016-07-21       Impact factor: 2.796

8.  Indication of Measures of Uncertainty for Statistical Significance in Abstracts of Published Oncology Trials: A Systematic Review and Meta-analysis.

Authors:  Samuel M Rubinstein; Elizabeth A Sigworth; Shervin Etemad; Richard L Martin; Qingxia Chen; Jeremy L Warner
Journal:  JAMA Netw Open       Date:  2019-12-02
  8 in total

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