Literature DB >> 27990498

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

Don Roosan1, Matthew Samore2, Makoto Jones2, Yarden Livnat3, Justin Clutter4.   

Abstract

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Entities:  

Keywords:  Big-Data; clinical reasoning; population decision support; population health data

Year:  2016        PMID: 27990498      PMCID: PMC5161104          DOI: 10.1109/ICHI.2016.39

Source DB:  PubMed          Journal:  IEEE Int Conf Healthc Inform


  20 in total

1.  Feasibility of Population Health Analytics and Data Visualization for Decision Support in the Infectious Diseases Domain: A pilot study.

Authors:  Don Roosan; Guilherme Del Fiol; Jorie Butler; Yarden Livnat; Jeanmarie Mayer; Matthew Samore; Makoto Jones; Charlene Weir
Journal:  Appl Clin Inform       Date:  2016-06-29       Impact factor: 2.342

2.  Deciding about fast and slow decisions.

Authors:  Pat Croskerry; David A Petrie; James B Reilly; Gordon Tait
Journal:  Acad Med       Date:  2014-02       Impact factor: 6.893

3.  Comparing diagnostic performance and the utility of clinical vignette-based assessment under testing conditions designed to encourage either automatic or analytic thought.

Authors:  Jonathan S Ilgen; Judith L Bowen; Lucas A McIntyre; Kenny V Banh; David Barnes; Wendy C Coates; Jeffrey Druck; Megan L Fix; Diane Rimple; Lalena M Yarris; Kevin W Eva
Journal:  Acad Med       Date:  2013-10       Impact factor: 6.893

4.  Using cognitive task analysis to identify critical decisions in the laparoscopic environment.

Authors:  Curtis Craig; Martina I Klein; John Griswold; Krishnanath Gaitonde; Thomas McGill; Ari Halldorsson
Journal:  Hum Factors       Date:  2012-12       Impact factor: 2.888

Review 5.  Clinical decision making: how surgeons do it.

Authors:  Wendy Crebbin; Spencer W Beasley; David A K Watters
Journal:  ANZ J Surg       Date:  2013-05-03       Impact factor: 1.872

6.  How I was prescribed an unnecessary antibiotic while traveling to a conference on antibiotic resistance.

Authors:  Kevin T Kavanagh
Journal:  JAMA Intern Med       Date:  2014-09       Impact factor: 21.873

7.  Medical decision support using machine learning for early detection of late-onset neonatal sepsis.

Authors:  Subramani Mani; Asli Ozdas; Constantin Aliferis; Huseyin Atakan Varol; Qingxia Chen; Randy Carnevale; Yukun Chen; Joann Romano-Keeler; Hui Nian; Jörn-Hendrik Weitkamp
Journal:  J Am Med Inform Assoc       Date:  2013-09-16       Impact factor: 4.497

8.  C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men.

Authors:  Paul M Ridker; Nina P Paynter; Nader Rifai; J Michael Gaziano; Nancy R Cook
Journal:  Circulation       Date:  2008-11-09       Impact factor: 29.690

9.  Diagnostic Value of Simultaneous Measurement of Procalcitonin, Interleukin-6 and hs-CRP in Prediction of Early-Onset Neonatal Sepsis.

Authors:  Alireza Abdollahi; Saeed Shoar; Fatemeh Nayyeri; Mamak Shariat
Journal:  Mediterr J Hematol Infect Dis       Date:  2012-05-06       Impact factor: 2.576

10.  Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

Authors:  Roosan Islam; Charlene R Weir; Makoto Jones; Guilherme Del Fiol; Matthew H Samore
Journal:  BMC Med Inform Decis Mak       Date:  2015-11-30       Impact factor: 2.796

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  3 in total

1.  Improving Medication Information Presentation Through Interactive Visualization in Mobile Apps: Human Factors Design.

Authors:  Don Roosan; Yan Li; Anandi Law; Huy Truong; Mazharul Karim; Jay Chok; Moom Roosan
Journal:  JMIR Mhealth Uhealth       Date:  2019-11-25       Impact factor: 4.773

2.  Improving Team-Based Decision Making Using Data Analytics and Informatics: Protocol for a Collaborative Decision Support Design.

Authors:  Don Roosan; Anandi V Law; Mazharul Karim; Moom Roosan
Journal:  JMIR Res Protoc       Date:  2019-11-27

Review 3.  Pharmacogenomics cascade testing (PhaCT): a novel approach for preemptive pharmacogenomics testing to optimize medication therapy.

Authors:  Don Roosan; Angela Hwang; Moom R Roosan
Journal:  Pharmacogenomics J       Date:  2020-08-25       Impact factor: 3.550

  3 in total

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