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Implement Sci. 2019 Aug 30;14(1):86. doi: 10.1186/s13012-019-0927-x.

Implementing cardiovascular disease prevention guidelines to translate evidence-based medicine and shared decision making into general practice: theory-based intervention development, qualitative piloting and quantitative feasibility.

Author information

1
The University of Sydney, Sydney School of Public Health, ASK-GP Centre of Research Excellence, Rm 128 Edward Ford Building (A27), Sydney, NSW, Australia. carissa.bonner@sydney.edu.au.
2
The University of Sydney, Sydney School of Public Health, ASK-GP Centre of Research Excellence, Rm 128 Edward Ford Building (A27), Sydney, NSW, Australia.
3
Bond University, Faculty of Health Sciences & Medicine, ASK-GP Centre of Research Excellence, Robina, QLD, Australia.

Abstract

BACKGROUND:

The use of cardiovascular disease (CVD) prevention guidelines based on absolute risk assessment is poor around the world, including Australia. Behavioural barriers amongst GPs and patients include capability (e.g. difficulty communicating/understanding risk) and motivation (e.g. attitudes towards guidelines/medication). This paper outlines the theory-based development of a website for GP guidelines, and piloting of a new risk calculator/decision aid.

METHODS:

Stage 1 involved identifying evidence-based solutions using the Behaviour Change Wheel (BCW) framework, informed by previous research involving 400 GPs and 600 patients/consumers. Stage 2 co-developed website content with GPs. Stage 3 piloted a prototype website at a national GP conference. Stage 4 iteratively improved the website based on "think aloud" interviews with GPs and patients. Stage 5 was a feasibility study to evaluate potential efficacy (guidelines-based recommendations for each risk category), acceptability (intended use) and demand (actual use over 1 month) amongst GPs (n = 98).

RESULTS:

Stage 1 identified GPs as the target for behaviour change; the need for a new risk calculator/decision aid linked to existing audit and feedback training; and online guidelines as a delivery format. Stage 2-4 iteratively improved content and format based on qualitative feedback from GP and patient user testing over three rounds of website development. Stage 5 suggested potential efficacy with improved identification of hypothetical high risk patients (from 26 to 76%) and recommended medication (from 57 to 86%) after viewing the website (n = 42), but prescribing to low risk patients remained similar (from 19 to 22%; n = 37). Most GPs (89%) indicated they would use the website in the next month, and 72% reported using it again after one month (n = 98). Open feedback identified implementation barriers including a need for integration with medical software, low health literacy resources and pre-consultation assessment.

CONCLUSIONS:

Following a theory-based development process and user co-design, the resulting intervention was acceptable to GPs with high intentions for use, improved identification of patient risk categories and more guidelines-based prescribing intentions for high risk but not low risk patients. The effectiveness of linking the intervention to clinical practice more closely to address implementation barriers will be evaluated in future research.

KEYWORDS:

Audit and feedback; Behaviour change; Cardiovascular disease; Decision aids; Evidence-based medicine; Primary care; Risk assessment; Risk communication; Shared decision making

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