Pcv130 - Value of Implementation of Pharmaceutical Care for Cardiovascular Diseases in Lmics: A Hypothetical Simulation for Decision Making

Abstract

1.04-1.68), >12 to 18 (HR 1.17, 95% CI 1.10-1.83), and >18 (HR 1.21, 95% CI 1.26-2.03) month intervals had elevated risk for CVD (p for trend <0.001). In total strokes, the risk-increasing effect of CVD with longer lipid testing interval is stronger than MI or CHD and this positive association was preserved among subgroups according to drug adherence and outpatient department visits. CONCLUSIONS: Lipid testing intervals of more than 6 months may lead to increased risk of CVD among newly diagnosed dyslipidemia patients. Newly diagnosed dyslipidemia patients should be encouraged to check lipid profile at 6 months interval in order to reducing risk for CVD. OBJECTIVES:To assess the value of implementation of pharmaceutical care (PC) for cardiovascular diseases in low-middle-income countries (LMICs). METHODS: This is a health care use and policy study based on health care management, which has evaluated the value of implementation (VOI) of PC from a societal and Brazilian Public Health System (BPHS) perspective. During 2009, a PC program enlisted 104 patients covered by the BPHS. Direct medical and non-medical costs and social costs were considered. Markov modeling projected over 10-years systemic arterial hypertension complications (ischemic heart disease, stroke, peripheral arterial disease, heart failure, chronic kidney disease). The treatment effect was calculated by comparing PC and conventional care and discount rates of 5% and 3% were applied to costs/outcomes, respectively. In a cash flow model, the net present value based on the return on investment (ROI) over 10 years was calculated, which represented a quantitative measure of the pharmaceutical care (PC) acceptance effect, and was converted into a net health benefit (NHB). The systematizing of the epidemiological and NHB impact provided the calculation and sensitivity analysis of VOI according to the variation for 10,000 Monte Carlo's iterations of 38 inputs from the expected value of PC implementation. RESULTS: The ROI was USD $1,712,710 (95%CI 1,146,000-2,216,000), which represented a cost-benefit ratio of 30.03 (95%CI, 26.74e34.28). The social variables presented an important impact on NHB, they were able to change the ROI from USD $1,283,206 to USD $1,962,401. Lambda was estimated as the largest limit of willingness to pay for QALY, usually in LMICs; in Brazil it is three times the GDP, USD $28,000. Thus, the calculated NHB was 2.8 per patient (95%CI 2.67 -3.04) and NHB ROI¼5.41%. CONCLUSIONS: The impact of implementation was higher than implementation of net beneficial technology, which presents a great opportunity cost for PC.