Cited by 109Electronic Health Records SystemsHealth Promotion and Cardiovascular PreventionClinical practice guidelines implementation

Integrated electronic decision support increases cardiovascular disease risk assessment four fold in routine primary care practice

Open access
Wells, Sue, Furness, Sue, Rafter, Natasha, Horn, Elaine, Whittaker, Robyn, Stewart, Alistair, Moodabe, Kate, Roseman, Paul +3 more·2008·European Journal of Cardiovascular Prevention & Rehabilitation

Abstract

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1097/hjr.0b013e3282f13af4

Cites

22 of 22 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Integrating a web-based decision-support system (PREDICT-CVD) with primary care electronic medical record software improved CVD risk documentation fourfold in a practice of 3564 patients.

    “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”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. The management of raised blood pressure in New Zealand. A consensus development conference report. In: Wellington: National Advisory Committee on Core health and Disability Support Services; 1992.
  2. National Heart Foundation. Clinical guidelines for the assessment and management of dyslipidaemia. NZ Med J 1996; 109:224-232.
  3. Arroll B, Goodyear-Smith F, Kerse N, Lloyd T. Four clinical guidelines-their use and usefulness to GPs. NZ Fam Phys 2002; 29:177-183.

Cited by

Sorted by citations

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
Venue
European Journal of Cardiovascular Prevention & Rehabilitation
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
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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review