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Published in: BMC Medical Informatics and Decision Making 1/2019

Open Access 01-12-2019 | Research article

Collective intelligence in medical decision-making: a systematic scoping review

Authors: Kate Radcliffe, Helena C. Lyson, Jill Barr-Walker, Urmimala Sarkar

Published in: BMC Medical Informatics and Decision Making | Issue 1/2019

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Abstract

Background

Collective intelligence, facilitated by information technology or manual techniques, refers to the collective insight of groups working on a task and has the potential to generate more accurate information or decisions than individuals can make alone. This concept is gaining traction in healthcare and has potential in enhancing diagnostic accuracy. We aim to characterize the current state of research with respect to collective intelligence in medical decision-making and describe a framework for diverse studies in this topic.

Methods

For this systematic scoping review, we conducted a systematic search for published literature using PubMed, Embase, Web of Science, and CINAHL on August 8, 2017. We included studies that combined the insights of two or more medical experts to make decisions related to patient care. Studies that examined medical decisions such as diagnosis, treatment, and management in the context of an actual or theoretical patient case were included. We include studies of complex medical decision-making rather than identification of a visual finding, as in radiology or pathology. We differentiate between medical decisions, in which synthesis of multiple types of information is required over time, and studies of radiological scans or pathological specimens, in which objective identification of a visual finding is performed. Two reviewers performed article screening, data extraction, and final inclusion for analysis.

Results

Of 3303 original articles, 15 were included. Each study examined the medical decisions of two or more individuals; however, studies were heterogeneous in their methods and outcomes. We present a framework to characterize these diverse studies, and future investigations, based on how they operationalize collective intelligence for medical decision-making: 1) how the initial decision task was completed (group vs. individual), 2) how opinions were synthesized (information technology vs. manual vs. in-person), and 3) the availability of collective intelligence to participants.

Discussion

Collective intelligence in medical decision-making is gaining popularity to advance medical decision-making and holds promise to improve patient outcomes. However, heterogeneous methods and outcomes make it difficult to assess the utility of collective intelligence approaches across settings and studies. A better understanding of collective intelligence and its applications to medicine may improve medical decision-making.
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Literature
1.
go back to reference Woolley AW, Chabris CF, Pentland A, et al. Evidence for a collective intelligence factor in the performance of human groups. Science. 2010;330(6004):686.CrossRef Woolley AW, Chabris CF, Pentland A, et al. Evidence for a collective intelligence factor in the performance of human groups. Science. 2010;330(6004):686.CrossRef
3.
go back to reference Surowiecki J. The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations. New York: Doubleday Books; 2004. Surowiecki J. The wisdom of crowds: why the many are smarter than the few and how collective wisdom shapes business, economies, societies, and nations. New York: Doubleday Books; 2004.
14.
go back to reference Institute of Medicine Committee on Quality of Health Care in A. In: Kohn LT, Corrigan JM, Donaldson MS, eds. To Err is human: building a safer health system. Washington (DC): National Academies Press (US) Copyright 2000 by the National Academy of Sciences. All rights reserved. 2000. Institute of Medicine Committee on Quality of Health Care in A. In: Kohn LT, Corrigan JM, Donaldson MS, eds. To Err is human: building a safer health system. Washington (DC): National Academies Press (US) Copyright 2000 by the National Academy of Sciences. All rights reserved. 2000.
15.
go back to reference Institute of Medicine Committee on the Health Professions Education S. Health professions education: a bridge to quality. In: Greiner AC, Knebel E, editors. . Washington (DC): National Academies Press (US) Copyright 2003 by the National Academy of Sciences. All rights reserved; 2003. Institute of Medicine Committee on the Health Professions Education S. Health professions education: a bridge to quality. In: Greiner AC, Knebel E, editors. . Washington (DC): National Academies Press (US) Copyright 2003 by the National Academy of Sciences. All rights reserved; 2003.
19.
go back to reference Institute of Medicine Committee on Standards for Systematic Reviews of Comparative Effectiveness R. In: Eden J, Levit L, Berg A, et al., eds. Finding what works in health care: standards for systematic reviews. Washington (DC): National Academies Press (US) copyright 2011 by the National Academy of Sciences. All rights reserved. 2011. Institute of Medicine Committee on Standards for Systematic Reviews of Comparative Effectiveness R. In: Eden J, Levit L, Berg A, et al., eds. Finding what works in health care: standards for systematic reviews. Washington (DC): National Academies Press (US) copyright 2011 by the National Academy of Sciences. All rights reserved. 2011.
20.
go back to reference Institute of Medicine (US) Committee on Standards for Systematic Reviews of Comparative Effectiveness Research; Eden J, Levit L, Berg A, Morton S, editors. Finding what works in health care: standards for systematic reviews. Washington (DC): National Academies Press (US); 2011. Institute of Medicine (US) Committee on Standards for Systematic Reviews of Comparative Effectiveness Research; Eden J, Levit L, Berg A, Morton S, editors. Finding what works in health care: standards for systematic reviews. Washington (DC): National Academies Press (US); 2011.
22.
go back to reference Alby F. Zucchermaglio, et al. diagnostic decision making in oncology: creating shared knowledge and managing complexity. Mind Culture Activity. 2015;22(1):4–22.CrossRef Alby F. Zucchermaglio, et al. diagnostic decision making in oncology: creating shared knowledge and managing complexity. Mind Culture Activity. 2015;22(1):4–22.CrossRef
23.
go back to reference Christensen C, Larson, et al. Decision making of clinical teams: communication patterns and diagnostic error. Med Decis Mak. 2000;20(1):45–50.CrossRef Christensen C, Larson, et al. Decision making of clinical teams: communication patterns and diagnostic error. Med Decis Mak. 2000;20(1):45–50.CrossRef
25.
go back to reference Gagliardi AR, Wright, et al. The role of collegial interaction in continuing professional development. J Contin Educ Heal Prof. 2007;27(4):214–9.CrossRef Gagliardi AR, Wright, et al. The role of collegial interaction in continuing professional development. J Contin Educ Heal Prof. 2007;27(4):214–9.CrossRef
26.
go back to reference Hautz WE, Kämmer JE, Schauber SK, et al. Diagnostic performance by medical students working individually or in teams. JAMA. 2015;313(3):303–4.CrossRef Hautz WE, Kämmer JE, Schauber SK, et al. Diagnostic performance by medical students working individually or in teams. JAMA. 2015;313(3):303–4.CrossRef
27.
go back to reference Kalf AJ, Spruijt M, et al. Variation in diagnoses: influence of specialists' training on selecting and ranking relevant information in geriatric case vignettes. Soc Sci Med. 1996;42(5):705–12.CrossRef Kalf AJ, Spruijt M, et al. Variation in diagnoses: influence of specialists' training on selecting and ranking relevant information in geriatric case vignettes. Soc Sci Med. 1996;42(5):705–12.CrossRef
29.
go back to reference Kunina-Habenicht O, Hautz WE, Knigge M, et al. Assessing clinical reasoning (ASCLIRE): instrument development and validation. Adv Health Sci Educ Theory Pract. 2015;20(5):1205–24.CrossRef Kunina-Habenicht O, Hautz WE, Knigge M, et al. Assessing clinical reasoning (ASCLIRE): instrument development and validation. Adv Health Sci Educ Theory Pract. 2015;20(5):1205–24.CrossRef
30.
go back to reference Lajoie SP, Lu, et al. Supporting collaboration with technology: does shared cognition lead to co-regulation in medicine? Metacogn Learn. 2012;7(1):45–62.CrossRef Lajoie SP, Lu, et al. Supporting collaboration with technology: does shared cognition lead to co-regulation in medicine? Metacogn Learn. 2012;7(1):45–62.CrossRef
31.
go back to reference Larson JR Jr, et al. Diagnosing groups: charting the flow of information in medical decision-making teams. J Pers Soc Psychol. 1996;71(2):315–30.CrossRef Larson JR Jr, et al. Diagnosing groups: charting the flow of information in medical decision-making teams. J Pers Soc Psychol. 1996;71(2):315–30.CrossRef
32.
go back to reference Larson JR Jr, et al. Diagnosing groups: the pooling, management, and impact of shared and unshared case information in team-based medical decision making. J Pers Soc Psychol. 1998;75(1):93–108.CrossRef Larson JR Jr, et al. Diagnosing groups: the pooling, management, and impact of shared and unshared case information in team-based medical decision making. J Pers Soc Psychol. 1998;75(1):93–108.CrossRef
34.
go back to reference Semigran HL, Levine DM, Nundy S, et al. Comparison of physician and computer diagnostic accuracy. JAMA Intern Med. 2016;176(12):1860–1.CrossRef Semigran HL, Levine DM, Nundy S, et al. Comparison of physician and computer diagnostic accuracy. JAMA Intern Med. 2016;176(12):1860–1.CrossRef
Metadata
Title
Collective intelligence in medical decision-making: a systematic scoping review
Authors
Kate Radcliffe
Helena C. Lyson
Jill Barr-Walker
Urmimala Sarkar
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2019
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-019-0882-0

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