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

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. Electronic supplementary material The online version of this article (10.1186/s13012-019-0927-x) contains supplementary material, which is available to authorized users.

Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey

“…Further research is needed to determine whether the behavioral outcomes of heart age calculators can be improved by linking it to additional behavior change strategies known to improve lifestyle change (eg, action planning) [ 16 ] and whether absolute risk formats used in clinical practice can be equally engaging [ 28 ]. There is very little research comparing different labels for the general concept of biological age , but one study has found differences in the way that young people interpret heart age compared with fitness age even when the same numerical age result is used [ 29 ].…”

Measurement of sustainment of prevention programs and initiatives: the sustainment measurement system scale

“…The SMSS can be used to conduct audits and provide feedback to grantees committed to sustaining prevention programs and initiatives once initial funding has ended. are recognized as important for prevention [19,20], much of the relevant science on feedback in health has involved improvement in clinical performance [21][22][23][24][25][26][27]. This includes clinical supervision and use of technology like electronic dashboards in measurement-based quality improvement (MBQI) strategies that monitor patient behavior and clinician activity [28][29][30], while prevention has a more limited history of using computational technologies for monitoring [31][32][33][34].…”

Measurement of Sustainment of Prevention Programs and Initiatives: The Sustainment Measurement System Scale

“…One of the reasons for developing a valid and reliable measure of sustainment is to provide a means of conducting an audit and providing feedback to organizations engaged in implementing innovative and evidence-based programs and practices. While monitoring and feedback are recognized as important for prevention [18,19], much of the relevant science on feedback in health has involved improvement in clinical performance [20][21][22][23][24][25][26]. This includes clinical supervision and use of technology like electronic dashboards in measurement-based quality improvement (MBQI) strategies that monitor patient behavior and clinician activity [27][28][29], while prevention has a more limited history of using computational technologies for monitoring [30][31][32][33].…”