Digital clinical decision support to improve care and to save costs: a pilot survey of the views of frontline healthcare professionals
- PMID: 40291100
- PMCID: PMC12026040
- DOI: 10.1080/08998280.2025.2465055
Digital clinical decision support to improve care and to save costs: a pilot survey of the views of frontline healthcare professionals
Abstract
Introduction: There has been much discourse about the features and impact of clinical decision support. However, until recently, there has been less evidence on how healthcare professionals use decision support to provide evidence-based care or on the potential cost savings that could emerge from its use. This study attempted to fill this gap by asking healthcare professionals to what extent they value digital clinical decision support as a means to apply evidence-based care and to save costs.
Methods: Frontline resident doctors were invited to complete an online semistructured questionnaire on if, and how, they used a clinical decision support resource to obtain and apply information to provide evidence-based care and/or to save costs.
Results: Among the respondents, 93% agreed or strongly agreed that the clinical decision support helped them obtain information to provide evidence-based care, and 93% agreed or strongly agreed that they could apply the information obtained from the resource to provide evidence-based care. Half of the respondents agreed or strongly agreed that using the resource helped them save healthcare costs.
Discussion: The results strongly support the idea that the doctors used the resource to provide evidence-based care; the results related to cost savings were not as strong.
Keywords: Clinical decision support; costs; healthcare professionals; improvement.
Copyright © 2025 Baylor University Medical Center.
Conflict of interest statement
The authors report no funding. KW works for BMJ; the other authors report no potential conflicts of interest.
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References
-
- Wasylewicz ATM, Scheepers-Hoeks AMJW.. 2019. Clinical decision support systems. In: Kubben P, Dumontier M, Dekker A, eds. Fundamentals of Clinical Data Science. Cham: Springer; 2018: Chapter 11. - PubMed
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