ArticleDigital health
Adaptive design of a clinical decision support tool: What the impact on utilization rates means for future CDS research.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Impact of Clinical Decision Support on Antibiotic Prescribing for Acute Respiratory Infections: a Cluster Randomized Implementation Trial.Journal of general internal medicine · 2020Trial
- Clinical decision support for potentially sedating drugs in palliative care: a mixed-methods pilot study.BMC palliative care · 2026Article
- An Evaluation of Clinician and Informatician Perspectives on Medication Harm Risk Prediction Tools for Use in a Tertiary Hospital Setting.Journal of evaluation in clinical practice · 2026Article
- Barriers and Enablers for Sustaining Nurse-Led Use of Clinical Decision Support Tools for Antibiotic Stewardship: Qualitative Study.JMIR nursing · 2026Article
- Online Decision Support for Implementing Evidence-Based HPV Vaccination Strategies in Texas Safety-Net Pediatric Clinics: Impact on HPV, MCV, and Tdap Initiation.Healthcare (Basel, Switzerland) · 2026Article
- Nursing Performance Using Clinical Prediction Rules for Acute Respiratory Infection Management: A Case-Based Simulation.Applied clinical informatics · 2025Article
- Opportunities and Challenges Associated with the Pilot Implementation of Clinical Decision Support Systems in a Rural Hospital: A Qualitative Study.Applied clinical informatics · 2025Article
- Development of a Human Factors-Based Guideline to Support the Design, Evaluation, and Continuous Improvement of Clinical Decision Support.Mayo Clinic proceedings. Digital health · 2025Article
- "Be Really Careful about That": Clinicians' Perceptions of an Intelligence Augmentation Tool for In-Hospital Deterioration Detection.Applied clinical informatics · 2025Article
- The user-centered design and development of a childhood and adolescent obesity Electronic Health Record tool, a mixed-methods study.Frontiers in digital health · 2024Article
- Article
- Near-Live Simulations to the Rescue: Lessons Learned from Using Alternative Simulation Approaches for Evaluating New Technologies.Extended abstracts on Human factors in computing systems. CHI Conference · 2023Article
- Provider Perspectives on Patient- and Provider-Facing High Blood Pressure Clinical Decision Support.Applied clinical informatics · 2022Article
- Human-machine teaming is key to AI adoption: clinicians' experiences with a deployed machine learning system.NPJ digital medicine · 2022Article
- Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.Healthcare (Amsterdam, Netherlands) · 2022Article
- Implementation of an Anticoagulation Practice Guideline for COVID-19 via a Clinical Decision Support System in a Large Academic Health System and Its Evaluation: Observational Study.JMIR medical informatics · 2021Article
- Clinical Decision Support and Implications for the Clinician Burnout Crisis.Yearbook of medical informatics · 2020Review
- Article
- Use of a human-centered design approach to adapt a nurse-led cardiovascular disease prevention intervention in HIV clinics.Progress in cardiovascular diseasesArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectiveWe employed an agile, user-centered approach to the design of a clinical decision support tool in our prior integrated clinical prediction rule study, which achieved high adoption rates. To understand if applying this user-centered process to adapt clinical decision support tools is effective in improving the use of clinical prediction rules, we examined utilization rates of a clinical decision support tool adapted from the original integrated clinical prediction rule study tool to determine if applying this user-centered process to design yields enhanced utilization rates similar to the integrated clinical prediction rule study.
resultsWe hypothesized a well-validated, user-centered clinical decision support tool would lead to relatively high adoption rates. Then 6 months post-deployment, integrated clinical prediction rule study tool utilization rates were substantially lower than anticipated based on the original integrated clinical prediction rule study trial (68%) at 17% (Health System A) and 5% (Health System B). User feedback at 6 months resulted in recommendations for tool refinement, which were incorporated when possible into tool design; however, utilization rates at 12 months post-deployment remained low at 14% and 4% respectively. DISCUSSION: Although valuable, findings demonstrate the limitations of a user-centered approach given the complexity of clinical decision support.
conclusionStrategies for addressing persistent external factors impacting clinical decision support adoption should be considered in addition to the user-centered design and implementation of clinical decision support.
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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.