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Integrated electronic decision support increases cardiovascular disease risk assessment four fold in routine primary care practice
Open accessAbstract
BACKGROUND: A decade of cardiovascular disease (CVD) risk-based guidelines, education programmes and widespread availability of paper-based risk prediction charts have not significantly influenced targeting of CVD risk management in New Zealand primary care practice. A web-based decision support system (PREDICT-CVD), integrated with primary care electronic medical record software was developed as one strategy to address this problem. METHODS: A before-after audit of 3564 electronic patient records assessed the impact of electronic decision support on documentation of CVD risk and CVD risk factors. Participants were patients meeting national guideline criteria for CVD risk assessment, registered with 84/107 (78.5%) general practitioners (GPs) in one large primary care organization who used electronic patient medical records, and had PREDICT-CVD installed. The GPs received group education sessions, practice IT support and a small risk assessment payment. Four weeks of practice visit records were audited from 1 month after installation of PREDICT-CVD, and during the same 4-week period 12 months earlier. RESULTS: Less than 3% of eligible patients had a documented CVD risk before PREDICT-CVD installation. This increased four-fold (RR=4.0; 95% confidence interval 2.4-6.5) after installation and documentation of all relevant CVD risk factors also increased significantly. CONCLUSION: Documentation of CVD risk in primary care patient records in New Zealand is negligible, despite being recommended as a prerequisite for targeted treatment for over 10 years, suggesting that previous strategies were ineffective. We demonstrate that integrated electronic decision support can quadruple CVD risk assessment in just one cycle of patient visits.
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“integration of a web-based decisionsupport system (PREDICT-CVD) with primary care electronic medical record software improved CVD risk documentation fourfold in a primary care practice of 3564 patients.551”
From European Guidelines on cardiovascular disease prevention in clinical practice (version 2012) (2012) · cites this paper as [551]
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European Guidelines on cardiovascular disease prevention in clinical practice (version 2012)
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Metadata
- Authors
- Wells, S., Furness, S., Rafter, N., Horn, E., Whittaker, R., Stewart, A., Moodabe, K., Roseman, P., Selak, V., Bramley, D., & Jackson, R.
- Affiliations
- University of Auckland (NZ)
- ProCare Health Ltd, Auckland, New Zealand
- Corresponding author
- Wells, Sue
- ORCID
- Venue
- European Journal of Cardiovascular Prevention & Rehabilitation
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-04
- Volume
- 15
- Issue
- 2
- Pages
- 173-178
- ISSN
- 1741-8267 (ISSN-L)
- OpenAlex
- W2096963542
- Cited by
- 109
- References
- 22
- Citations by year
- 2025: 3 · 2024: 8 · 2023: 1 · 2022: 2 · 2021: 4 · 2020: 3 · 2019: 3 · 2018: 4 · 2017: 5 · 2016: 6 · 2015: 6 · 2014: 7 · 2013: 12 · 2012: 18
- FWCI
- 18.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- European Journal of Cardiovascular Prevention & Rehabilitation (publishedVersion)
- PubMed (publishedVersion)
- ResearchSpace (University of Auckland) (submittedVersion, cc-by)
- Funders
- Waitemata District Health Board
- Ministry of Health, New Zealand
- Health Research Council of New Zealand
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- cardiovascular disease risk assessment, electronic decision support, primary care, electronic health records, general practitioners, practice audit
- MeSH terms
- Cardiovascular Diseases, Decision Support Techniques, Family Practice, Humans, Medical Audit, New Zealand, Primary Health Care, Retrospective Studies, Risk Factors, Software, Time Factors, Reproducibility of Results, Program Evaluation, Medical Records Systems, Computerized, Risk Assessment, Decision Support Systems, Clinical, Internet
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