Factors influencing the implementation of cardiovascular risk scoring in primary care: a mixed-method systematic review

Abstract

Background: Cardiovascular disease (CVD) such as ischemic heart disease and stroke is the leading causes of death and disability globally with a growing burden in low and middle-income countries. A credible way of managing the incidence and prevalence of cardiovascular diseases is by reducing risk factors. This understanding has led to the development and recommendation for the clinical use of cardiovascular risk stratification tools. These tools enhance clinical decision-making. However, there is a lag in the implementation of these tools in most countries. This systematic review seeks to synthesise the current knowledge of the factors influencing the implementation of cardiovascular risk scoring in primary care settings. Methods: We searched bibliographic databases and grey literature for studies of any design relating to the topic. Titles, abstracts and full texts were independently assessed for eligibility by two reviewers. This was followed by quality assessment and data extraction. We analysed data using an integrated and best fit framework synthesis approach to identify these factors. Quantitative and qualitative forms of data were combined into a single mixedmethods synthesis. The Consolidated Framework for Implementation Research was used as the guiding tool and template for this analysis. Results: Twenty-five studies (cross-sectional n = 12, qualitative n = 9 and mixed-methods n = 4) were included in this review. Twenty (80%) of these were conducted in high-income countries. Only four studies (16%) included patients as participants. This review reports on a total of eleven cardiovascular risk stratification tools. The factors influencing the implementation of cardiovascular risk scoring are related to clinical setting and healthcare system (resources, priorities, practice culture and organisation), users (attributes and interactions between users) and the specific cardiovascular risk tool (characteristics, perceived role and effectiveness). Conclusions: While these findings bolster the understanding of implementation complexity, there exists limited research in the context of low and middle-income countries. Notwithstanding the need to direct resources in bridging this gap, it is also crucial that these efforts are in concert with providing high-quality evidence on the clinical effectiveness of using cardiovascular risk scoring to improve cardiovascular disease outcomes of mortality and morbidity. Trial registration: PROSPERO registration number: CRD42018092679.

A Systematic Approach to Identifying and Developing Implementation Strategies to Support the Uptake of a Risk Tool to Aid in Clinical Management of Patients with Syncope: A Qualitative Study

“…Key barriers included uncertainty around when and how to apply the CSRS recommendations, lack of resources (e.g., cardiac monitors), lack of buy-in from the broader medical team, discomfort (hesitancy) using CSRS, and lack of evidence about the impact on patient outcomes. Surprisingly, no reference on workload or time constraint was brought up, as is often found in other studies (39)(40)(41)(42). Our ndings suggest that physician capability should be a central target of implementation supports, speci cally the capability to interpret CSRSbased criteria and apply it across a range of clinical presentations.…”

Guía de práctica clínica mexicana para el diagnóstico y tratamiento de las dislipidemias y enfermedad cardiovascular aterosclerótica

“…Algunos factores de riesgo no son modificables, como la edad, el sexo, la etnia o la carga genética; y algunos otros factores, como niveles anormales de lípidos en suero, la HAS, la exposición al humo del cigarro, el estilo de vida sedentario, la obesidad o el estrés (entre otros) sí son modificables. Se considera que la suma de todos estos factores explica en un 90% el riesgo de presentar un evento por ECVA 37 .…”

“…Los autores incluyeron 25 estudios y reportan el uso de 11 diferentes herramientas de RCV. Las herramientas empleadas fueron la ESC SCORE risk, desarrollada por la ESC y la Evaluación Sistemática de Riesgo Coronario, el Framingham Risk Score y su modificación, el Cardiovascular Risk PROCAM Score , el AGLA Risk Score y el WHO/ISH Cardiovascular Risk Prediction Charts desarrollado por la OMS y la Sociedad Internacional de Hipertensión (ISH), entre otras menos empleadas 37 .…”

Novel Urinary Glycan Biomarkers Predict Cardiovascular Events in Patients With Type 2 Diabetes: A Multicenter Prospective Study With 5-Year Follow Up (U-CARE Study 2)

“…Cardiovascular disease (CVD) is a global burden especially in low- and middle-income countries and the leading cause of disability and mortality ( 1 ). The understanding of CVD risk factors is quite important to establish the cardiovascular risk prediction models.…”