ArticleDigital health
User-centred design of a clinical decision support system for palliative care: Insights from healthcare professionals.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Participatory Design of AI-Based Clinical Decision Support Systems: Scoping Review.JMIR medical informatics · 2026Article
- Clinical decision support for potentially sedating drugs in palliative care: a mixed-methods pilot study.BMC palliative care · 2026Article
- Review
- Exploring the application of Artificial Intelligence in palliative care and its practical, technical and ethical considerations: a scoping review.BMC palliative care · 2026Article
- Supporting Parental Decision-Making After Life-Limiting Fetal Diagnoses: The Role of Perinatal Hospice and the NOVA-L Decision Support System.Healthcare (Basel, Switzerland) · 2026Article
- Developing an AI-Assisted Tool That Identifies Patients With Multimorbidity and Complex Polypharmacy to Improve the Process of Medication Reviews: Qualitative Interview and Focus Group Study.Journal of medical Internet research · 2026Article
- Clinical Decision Support Systems and Artificial Intelligence in ADHD Assessment and Rehabilitation: Opportunities and Challenges for Technology-Assisted Care.Healthcare (Basel, Switzerland) · 2025Article
- Artificial intelligence-based approaches for advance care planning: a scoping review.BMC palliative care · 2025Article
- Integrating PRISM with User-centered Design (PRISM+UCD): Designing clinical decision support for safe opioid prescribing.Research square · 2025Article
- Realizing the Full Potential of Clinical Decision Support: Translating Usability Testing into Routine Practice in Health Care Operations.Applied clinical informatics · 2024Article
- The user experiences of AI-based clinical decision support systems and implications for usage over time: A scoping review.Digital healthReview
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Although clinical decision support systems (CDSS) have many benefits for clinical practice, they also have several barriers to their acceptance by professionals. Our objective in this study was to design and validate The Methods: We performed two rounds of individual evaluation sessions with potential users. Each session included a model evaluation, a task test and a usability and UX assessment. Results: The machine learning (ML) predictive models outperformed the participants in the three predictive tasks. System Usability Scale (SUS) reported 62.7 ± 14.1 and 65 ± 26.2 on a 100-point rating scale for both rounds, respectively, while User Experience Questionnaire - Short Version (UEQ-S) scores were 1.42 and 1.5 on the -3 to 3 scale. Conclusions: The think-aloud method and including the UX dimension helped us to identify most of the workflow implementation issues. The system has good UX hedonic qualities; participants were interested in the tool and responded positively to it. Performance regarding usability was modest but acceptable.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.