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Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools

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Title: Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools
Authors: Ming, D
Nguyen, QH
An, LP
Chanh, HQ
Tam, DTH
Truong, NT
Huy, VX
Hernandez, B
Van Nuil, JI
Paton, C
Georgiou, P
Nguyen, NM
Holmes, A
Tho, PV
Yacoub, S
Item Type: Journal Article
Abstract: Background Dengue is a common viral illness and severe disease results in life-threatening complications. Healthcare services in low- and middle-income countries treat the majority of dengue cases worldwide. However, the clinical decision-making processes which result in effective treatment are poorly characterised within this setting. In order to improve clinical care through interventions relating to digital clinical decision-support systems (CDSS), we set out to establish a framework for clinical decision-making in dengue management to inform implementation. Methods We utilised process mapping and task analysis methods to characterise existing dengue management at the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. This is a tertiary referral hospital which manages approximately 30,000 patients with dengue each year, accepting referrals from Ho Chi Minh city and the surrounding catchment area. Initial findings were expanded through semi-structured interviews with clinicians in order to understand clinical reasoning and cognitive factors in detail. A grounded theory was used for coding and emergent themes were developed through iterative discussions with clinician-researchers. Results Key clinical decision-making points were identified: (i) at the initial patient evaluation for dengue diagnosis to decide on hospital admission and the provision of fluid/blood product therapy, (ii) in those patients who develop severe disease or other complications, (iii) at the point of recurrent shock in balancing the need for fluid therapy with complications of volume overload. From interviews the following themes were identified: prioritising clinical diagnosis and evaluation over existing diagnostics, the role of dengue guidelines published by the Ministry of Health, the impact of seasonality and caseload on decision-making strategies, and the potential role of digital decision-support and disease scoring tools. Conclusions The study highlights the contemporary priorities in delivering clinical care to patients with dengue in an endemic setting. Key decision-making processes and the sources of information that were of the greatest utility were identified. These findings serve as a foundation for future clinical interventions and improvements in healthcare. Understanding the decision-making process in greater detail also allows for development and implementation of CDSS which are suited to the local context.
Issue Date: 2-Feb-2023
Date of Acceptance: 19-Jan-2023
URI: http://hdl.handle.net/10044/1/102809
DOI: 10.1186/s12911-023-02116-4
ISSN: 1472-6947
Publisher: BioMed Central
Start Page: 1
End Page: 9
Journal / Book Title: BMC Medical Informatics and Decision Making
Volume: 23
Copyright Statement: © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativeco mmons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data
Publication Status: Published
Article Number: 24
Online Publication Date: 2023-02-02
Appears in Collections:Department of Infectious Diseases
Faculty of Medicine



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