Trial reportJAMA network open2022
Effect of Clinical Decision Support at Community Health Centers on the Risk of Cardiovascular Disease: A Cluster Randomized Clinical Trial.
Trial report in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03001713 (CV Wizard), which is not on this map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
CV Wizard: Does a Prioritized, Point-of-Care Clinical Decision Support Tool Improve Guideline-Based CVD Risk Factor Control in Safety Net Clinics?
Who cites it
21 citing papers in PubMed, 30 citations in OpenAlex.
- Effect of a Digital-Driven Physician-Pharmacist Collaborative Model for Diabetes in Primary Health Care: Cluster Randomized Trial.Journal of medical Internet research · 2026Trial
- Clinical Decision Support and Cardiometabolic Medication Adherence: A Randomized Clinical Trial.JAMA network open · 2025 · on this mapTrial
- Does Clinical Decision Support Increase Appropriate Medication Prescribing for Cardiovascular Risk Reduction?Journal of the American Board of Family Medicine : JABFM · 2023Trial
- Sociotechnical Intervention for Improved Delivery of Preventive Cardiovascular Care to Rural Communities: Participatory Design Approach.Journal of medical Internet research · 2022Trial
- User-Centered Design Approach to Dynamic Clinical Decision Support in Primary Prevention of Cardiovascular Disease.Healthcare (Basel, Switzerland) · 2026Article
- Cardiovascular-Kidney-Metabolic Syndrome: Development of anJMIR diabetes · 2026Article
- Bridging the Gap: Multidisciplinary Decision Making to Address Systemic Barriers in Cardiovascular Care.Current cardiology reports · 2026Review
- EHR-derived cognitive load is associated with guideline-concordant statin initiation in primary care.BMC medical informatics and decision making · 2026Article
- Evaluating Cognitive Load in Clinical Workflows Highlights Leverage Points for Guideline-Concordant Statin Initiation.Research square · 2025Article
- Management capacity for stable coronary heart disease in Shanghai community medical institutions: a cross-sectional study.BMC health services research · 2025Article
- Factors Influencing Health Workers' Acceptance of Guideline-Based Clinical Decision Support Systems for Preventive Services in Thailand: Questionnaire-Based Study.JMIR human factors · 2025Article
- Do clinical decision support tools improve quality of care outcomes in the primary prevention of cardiovascular disease: A systematic review and meta-analysis.American journal of preventive cardiology · 2024Article
- Healthcare dashboard technologies and data visualization for lipid management: A scoping review.BMC medical informatics and decision making · 2024Article
- Article
- Barriers and Facilitators to Using a Clinical Decision Support Tool for Opioid Use Disorder in Primary Care.Journal of the American Board of Family Medicine : JABFM · 2024Article
- Pandemic-related practice changes and CVD risk management in community clinics.The American journal of managed care · 2024Article
- Cardiovascular disease risk management during COVID-19: in-person vs virtual visits.The American journal of managed care · 2024Article
- Adoption of shared decision-making and clinical decision support for reducing cardiovascular disease risk in community health centers.JAMIA open · 2023Article
- Adaptation of Autoencoder for Sparsity Reduction From Clinical Notes Representation Learning.IEEE journal of translational engineering in health and medicine · 2023Article
- Assessing the decision quality of artificial intelligence and oncologists of different experience in different regions in breast cancer treatment.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
18 authors at 3 institutions in 1 country.
Funding
Abstract
Importance: Management of cardiovascular disease (CVD) risk in socioeconomically vulnerable patients is suboptimal; better risk factor control could improve CVD outcomes. Objective: To evaluate the impact of a clinical decision support system (CDSS) targeting CVD risk in community health centers (CHCs). Design, Setting, and Participants: This cluster randomized clinical trial included 70 CHC clinics randomized to an intervention group (42 clinics; 8 organizations) or a control group that received no intervention (28 clinics; 7 organizations) from September 20, 2018, to March 15, 2020. Randomization was by CHC organization accounting for organization size. Patients aged 40 to 75 years with (1) diabetes or atherosclerotic CVD and at least 1 uncontrolled major risk factor for CVD or (2) total reversible CVD risk of at least 10% were the population targeted by the CDSS intervention. Interventions: A point-of-care CDSS displaying real-time CVD risk factor control data and personalized, prioritized evidence-based care recommendations. Main Outcomes and Measures: One-year change in total CVD risk and reversible CVD risk (ie, the reduction in 10-year CVD risk that was considered achievable if 6 key risk factors reached evidence-based levels of control). Results: Among the 18 578 eligible patients (9490 [51.1%] women; mean [SD] age, 58.7 [8.8] years), patients seen in control clinics (n = 7419) had higher mean (SD) baseline CVD risk (16.6% [12.8%]) than patients seen in intervention clinics (n = 11 159) (15.6% [12.3%]; P < .001); baseline reversible CVD risk was similarly higher among patients seen in control clinics. The CDSS was used at 19.8% of 91 988 eligible intervention clinic encounters. No population-level reduction in CVD risk was seen in patients in control or intervention clinics; mean reversible risk improved significantly more among patients in control (-0.1% [95% CI, -0.3% to -0.02%]) than intervention clinics (0.4% [95% CI, 0.3% to 0.5%]; P < .001). However, when the CDSS was used, both risk measures decreased more among patients with high baseline risk in intervention than control clinics; notably, mean reversible risk decreased by an absolute 4.4% (95% CI, -5.2% to -3.7%) among patients in intervention clinics compared with 2.7% (95% CI, -3.4% to -1.9%) among patients in control clinics (P = .001). Conclusions and Relevance: The CDSS had low use rates and failed to improve CVD risk in the overall population but appeared to have a benefit on CVD risk when it was consistently used for patients with high baseline risk treated in CHCs. Despite some limitations, these results provide preliminary evidence that this technology has the potential to improve clinical care in socioeconomically vulnerable patients with high CVD risk. Trial Registration: ClinicalTrials.gov Identifier: NCT03001713.
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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.