Diabetes and Cardiovascular Diseases Risk Assessment in Community Pharmacies: An Implementation Study.
Sarah RondeauxTessa BraeckmanMieke BeckwéNatacha BisetJoris MaesschalckNathalie DuquetIsabelle De WulfDirk DevroeyCarine De VriesePublished in: International journal of environmental research and public health (2022)
The implementation of a new service is often challenging when translating research findings into routine clinical practices. This paper presents the results of the implementation study of a pilot project for a diabetes and cardiovascular diseases risk-assessment service in Belgian community pharmacies. To evaluate the implementation of the service, a mixed method was used that follows the RE-AIM framework. During the testing stage, 37 pharmacies participated, including five that dropped out due to a lack of time or COVID-19-related temporary obligations. Overall, 502 patients participated, of which 376 (74.9%) were eligible for according-to-protocol analysis. Of these, 80 patients (21.3%) were identified as being at high risk for the targeted diseases, and 100 (26.6%) were referred to general practice for further investigation. We presented the limited effectiveness and the key elements influencing optimal implementation. Additional strategies, such as interprofessional workshops, a data-sharing platform, and communication campaigns, should be considered to spread awareness of the new role of pharmacists. Such strategies could also promote collaboration with general practitioners to ensure the follow-up of patients at high risk. Overall, this service was considered easy to perform and feasible in practice but would require financial and external support to ensure its effectiveness, sustainability, and larger-scale implementation.
Keyphrases
- healthcare
- primary care
- end stage renal disease
- risk assessment
- mental health
- cardiovascular disease
- quality improvement
- ejection fraction
- chronic kidney disease
- general practice
- randomized controlled trial
- newly diagnosed
- type diabetes
- peritoneal dialysis
- prognostic factors
- systematic review
- sars cov
- patient safety
- coronavirus disease
- clinical trial
- social media
- heavy metals
- insulin resistance
- skeletal muscle
- metabolic syndrome
- high throughput
- machine learning
- study protocol
- glycemic control
- adipose tissue
- deep learning
- clinical practice
- double blind