ArticleJournal of personalized medicine2020
An Implementation Science Framework to Develop a Clinical Decision Support Tool for Familial Hypercholesterolemia.
Article in Journal of personalized medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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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
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: systematic review and recommendations.Implementation science : IS · 2025Pooled it
- Clinical decision support for potentially sedating drugs in palliative care: a mixed-methods pilot study.BMC palliative care · 2026Article
- How Implementation Context Shapes Clinician Acceptance and Engagement with Guideline-Based Clinical Decision Support Systems in Primary Care: A Qualitative Study.Journal of healthcare leadership · 2026Article
- Cardiologist perceptions on automated alerts and messages to improve heart failure care.American heart journal · 2025Article
- Primary care clinician engagement in implementing a machine-learning algorithm for targeted screening of familial hypercholesterolemia.American journal of preventive cardiology · 2024Article
- Effect of clinical decision support for severe hypercholesterolemia on low-density lipoprotein cholesterol levels.NPJ digital medicine · 2024Article
- International Atherosclerosis Society guidance for implementing best practice in the care of familial hypercholesterolaemia.Nature reviews. Cardiology · 2023Review
- Clinician Perspectives on Clinical Decision Support for Familial Hypercholesterolemia.Journal of personalized medicine · 2023Article
- Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review.BMC primary care · 2023Article
- Addressing the underdiagnosis of familial hypercholesterolemia: A mixed methods study exploring the knowledge and practice behaviors of cardiology healthcare providers.Journal of clinical and translational science · 2023Article
- Web-Based Tool (FH Family Share) to Increase Uptake of Cascade Testing for Familial Hypercholesterolemia: Development and Evaluation.JMIR human factors · 2022Article
- Developing an Ophthalmology Clinical Decision Support System to Identify Patients for Low Vision Rehabilitation.Translational vision science & technology · 2021Article
- Therapeutic Inertia in Prescribing Biologics for Patients with Moderate-to-Severe Asthma: Workshop Summary.Patient preference and adherence · 2021Article
- Implementation Science to Increase Adoption of Genomic Medicine: An Urgent Need.Journal of personalized medicine · 2020Article
- Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
Electronic health record (EHR)-based clinical decision support (CDS) can address the low awareness and undertreatment of familial hypercholesterolemia (FH), a disorder associated with a markedly increased risk of coronary heart disease. We aimed to incorporate provider perspectives into the development and implementation of a CDS tool for FH. An implementation science framework and a user-centered design process were used to create a CDS tool for FH. Primary care physicians and specialist physicians participated in qualitative interviews, usability testing and an implementation survey. The CDS was configured in two formats-a best practice alert (BPA) and an in-basket message and subsequently deployed in the EHR in silent mode. The key themes that emerged from the analysis of interview transcripts included understanding and awareness of FH, clinical workflow, physician preferences and value of CDS tools, perspectives on patient needs and values and dissemination and implementation. Recommendations related to usability included preferred CDS format and placement, content, timing and frequency, and level of alert urgency/prioritization. In response to the survey, 84.6% of physicians agreed that the CDS would improve early FH diagnosis and 92.3% agreed that it would help them identify and manage FH patients. Physician feedback led to iterative CDS refinement. In summary, we developed a CDS tool for FH using an implementation science framework and physician feedback. Initial deployment revealed a significant burden of FH and the potential for the CDS tool to have a large impact.
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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.