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

Autor: Nguyen QH; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam., Ming DK; Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London, UK. d.ming@imperial.ac.uk., Luu AP; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam., Chanh HQ; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam., Tam DTH; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam., Truong NT; Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam., Huy VX; Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam., Hernandez B; Centre for BioInspired Technology, Imperial College London, London, UK., Van Nuil JI; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam., Paton C; Department of Information Science, University of Otago, Dunedin, New Zealand.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK., Georgiou P; Centre for BioInspired Technology, Imperial College London, London, UK., Nguyen NM; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam., Holmes A; Centre for Antimicrobial Optimisation (CAMO), Imperial College London, London, UK., Tho PV; Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam., Yacoub S; Centre for Tropical Medicine, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Jazyk: angličtina
Zdroj: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2023 Feb 02; Vol. 23 (1), pp. 24. Date of Electronic Publication: 2023 Feb 02.
DOI: 10.1186/s12911-023-02116-4
Abstrakt: 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.
(© 2023. The Author(s).)
Databáze: MEDLINE
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