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Collective intelligence in medical decision-making: a systematic scoping review
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688241/ https://www.ncbi.nlm.nih.gov/pubmed/31399099 http://dx.doi.org/10.1186/s12911-019-0882-0 |
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author | Radcliffe, Kate Lyson, Helena C. Barr-Walker, Jill Sarkar, Urmimala |
author_facet | Radcliffe, Kate Lyson, Helena C. Barr-Walker, Jill Sarkar, Urmimala |
author_sort | Radcliffe, Kate |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0882-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6688241 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66882412019-08-14 Collective intelligence in medical decision-making: a systematic scoping review Radcliffe, Kate Lyson, Helena C. Barr-Walker, Jill Sarkar, Urmimala BMC Med Inform Decis Mak Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0882-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-09 /pmc/articles/PMC6688241/ /pubmed/31399099 http://dx.doi.org/10.1186/s12911-019-0882-0 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Radcliffe, Kate Lyson, Helena C. Barr-Walker, Jill Sarkar, Urmimala Collective intelligence in medical decision-making: a systematic scoping review |
title | Collective intelligence in medical decision-making: a systematic scoping review |
title_full | Collective intelligence in medical decision-making: a systematic scoping review |
title_fullStr | Collective intelligence in medical decision-making: a systematic scoping review |
title_full_unstemmed | Collective intelligence in medical decision-making: a systematic scoping review |
title_short | Collective intelligence in medical decision-making: a systematic scoping review |
title_sort | collective intelligence in medical decision-making: a systematic scoping review |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6688241/ https://www.ncbi.nlm.nih.gov/pubmed/31399099 http://dx.doi.org/10.1186/s12911-019-0882-0 |
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