The pharmacy care plan service: Evaluation and estimate of cost-effectiveness

Background: The UK Community Pharmacy Future group developed the Pharmacy Care Plan (PCP) service with a focus on patient activation, goal setting and therapy management. Objective: To estimate the effectiveness and cost-effectiveness of the PCP service from a health services perspective. Methods: Patients over 50 years of age prescribed one or more medicines including at least one for cardiovascular disease or diabetes were eligible. Medication review and person-centred consultation resulted in agreed health goals and actions towards achieving them. Clinical, process and cost-effectiveness data were collected at baseline and 12-months between February 2015 and June 2016. Mean differences are reported for clinical and process measures. Costs (NHS) and quality-adjusted life year scores were estimated and compared for 12 months pre-and post-baseline. Results: Seven hundred patients attended the initial consultation and 54% had a complete set of data obtained. There was a significant improvement in patient activation score (mean difference 5.39; 95% CI 3.9-6.9; p < 0.001), systolic (mean difference -2.90 mmHg; 95% CI -4.7 to -1; p=0.002) and diastolic blood pressure (mean difference -1.81 mmHg; 95% CI -2.8 to -0.8; p < 0.001), adherence (mean difference 0.26; 95% CI 0.1-0.4; p < 0.001) and quality of life (mean difference 0.029; 95% CI 0.015-0.044; p < 0.001). HDL cholesterol reduced significantly and QRisk2 scores increased significantly over the course of the 12 months. The mean incremental cost associated with the intervention was estimated to be 202.91 pound (95% CI 58.26 to 346.41) pound and the incremental QALY gain was 0.024 (95% CI 0.014 to 0.034), giving an incremental cost per QALY of 8495 pound. Conclusions: Enrolment in the PCP service was generally associated with an improvement over 12 months in key clinical and process metrics. Results also suggest that the service would be cost-effective to the health system even when using worst case assumptions.