ArticlePEC innovation2023
Implementing patient decision aids into general practice clinical decision support systems: Feasibility study in cardiovascular disease prevention.
Article in PEC innovation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Factors Influencing the Uptake of Digital Health Interventions for Cardiovascular Disease Prevention Among Healthcare Providers: A Systematic Review.Global heart · 2026Pooled it
- Implementing decision aids for cardiovascular disease prevention: stakeholder interviews and case studies in Australian primary care.BMC primary care · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Patient decision aids (DA) facilitate shared decision making, but implementation remains a challenge. This study tested the feasibility of integrating a cardiovascular disease (CVD) prevention DA into general practice software. Methods: We developed a desktop computer application (app) to auto-populate a CVD prevention DA from general practice medical records. 4 practices received monthly practice reports from July-Nov 2021, and 2 practices use the app with limited engagement. CVD risk assessment data and app use were monitored. Results: The proportion of eligible patients with complete CVD risk assessment data ranged from 59 to 94%. Monthly app use ranged from 0 to 285 sessions by 13 individual practice staff including GPs and nurses, with staff using the app an average of 67 sessions during the study period. High users in the 5-month study period continued to use the app for 10 months. Low use was attributed to reduced staff capacity during COVID-19 and technical issues. Conclusion: High users sustained interest in the app, but additional strategies are required for low users. The study will inform implementation plans for new guidelines. Innovation: This study showed it is feasible to integrate patient decision aids with Australian general practice software, despite the challenges of COVID-19 at the time of the study.
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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.