Facilitators and Barriers of the Use of Prognostic Models for Clinical Decision Making in Acute Neurologic Care: A Systematic Review

Ellen X. Y. Hu, Evelien S. van Hoorn, Isabel R. A. Retel Helmrich, Susanne Muehlschlegel, Judith A. C. Rietjens and Hester F. Lingsma
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Ellen X. Y. Hu: Department of Health Services Management & Organisation, Erasmus University, Rotterdam, the Netherlands
Evelien S. van Hoorn: Department of Health Services Management & Organisation, Erasmus University, Rotterdam, the Netherlands
Isabel R. A. Retel Helmrich: Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
Susanne Muehlschlegel: Departments of Neurology, Anesthesiology/Critical Care Medicine and Neurosurgery, John Hopkins School of Medicine, Baltimore, MD, USA
Judith A. C. Rietjens: Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands
Hester F. Lingsma: Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands

Medical Decision Making, 2025, vol. 45, issue 6, 753-770

Abstract: Background Prognostic models are crucial for predicting patient outcomes and aiding clinical decision making. Despite their availability in acute neurologic care, their use in clinical practice is limited, with insufficient reflection on reasons for this scarce implementation. Purpose To summarize facilitators and barriers among clinicians affecting the use of prognostic models in acute neurologic care. Data Sources Systematic searches were conducted in Embase, Medline ALL, Web of Science Core Collection, and Cochrane Central Register of Controlled Trials from inception until February 2024. Study Selection Eligible studies included those providing clinicians’ perspectives on the use of prognostic models in acute neurologic care. Data Extraction Data were extracted concerning study characteristics, study aim, data collection and analysis, prognostic models, participant characteristics, facilitators, and barriers. Risk of bias was assessed using the Qualsyst tool. Data Synthesis Findings were structured around the Unified Theory of Acceptance and Use of Technology framework. Identified facilitators included improved communication with patients and surrogate decision makers ( n = 9), reassurance of clinical judgment ( n = 6) perceived improved patient outcomes ( n = 4), standardization of care ( n = 4), resource optimization ( n = 3), and extension of clinical knowledge ( n = 3). Barriers included perceived misinterpretation during risk communication ( n = 3), mistrust in data ( n = 3), perceived reduction of clinicians’ autonomy ( n = 3), and ethical considerations ( n = 2). In total, 15 studies were included, with all but 1 demonstrating good methodological quality. None were excluded due to poor quality ratings. Limitations This review identifies limitations, including study heterogeneity, exclusion of gray literature, and the scarcity of evaluations on model implementation. Conclusions Understanding facilitators and barriers may enhance prognostic model development and implementation. Bridging the gap between development and clinical use requires improved collaboration among researchers, clinicians, patients, and surrogate decision makers. Highlights This is the first systematic review to summarize published facilitators and barriers affecting the use of prognostic models in acute neurologic care from the clinicians’ perspective. Commonly reported barriers and facilitators were consistent with several domains of the Unified Theory of Acceptance and Use of Technology model, including effort expectancy, social influence, and facilitating conditions, with the focus on the performance expectancy domain. Future implementation research including collaboration with researchers from different fields, clinicians, patients, and their surrogate decision makers may be highly valuable for future model development and implementation.

Keywords: Prognostic models; acute neurological care; implementation; clinician perspectives; systematic review (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:45:y:2025:i:6:p:753-770

DOI: 10.1177/0272989X251343027

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