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Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design
BACKGROUND: Clinical experts’ cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665869/ https://www.ncbi.nlm.nih.gov/pubmed/26620881 http://dx.doi.org/10.1186/s12911-015-0221-z |
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author | Islam, Roosan Weir, Charlene R. Jones, Makoto Del Fiol, Guilherme Samore, Matthew H. |
author_facet | Islam, Roosan Weir, Charlene R. Jones, Makoto Del Fiol, Guilherme Samore, Matthew H. |
author_sort | Islam, Roosan |
collection | PubMed |
description | BACKGROUND: Clinical experts’ cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. METHODS: We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. RESULTS: The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners’ perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. CONCLUSION: The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-015-0221-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4665869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46658692015-12-02 Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design Islam, Roosan Weir, Charlene R. Jones, Makoto Del Fiol, Guilherme Samore, Matthew H. BMC Med Inform Decis Mak Research Article BACKGROUND: Clinical experts’ cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. METHODS: We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. RESULTS: The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners’ perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. CONCLUSION: The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-015-0221-z) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-30 /pmc/articles/PMC4665869/ /pubmed/26620881 http://dx.doi.org/10.1186/s12911-015-0221-z Text en © Islam et al. 2015 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 Islam, Roosan Weir, Charlene R. Jones, Makoto Del Fiol, Guilherme Samore, Matthew H. Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
title | Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
title_full | Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
title_fullStr | Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
title_full_unstemmed | Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
title_short | Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
title_sort | understanding complex clinical reasoning in infectious diseases for improving clinical decision support design |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4665869/ https://www.ncbi.nlm.nih.gov/pubmed/26620881 http://dx.doi.org/10.1186/s12911-015-0221-z |
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