Budget impact analysis for dapagliflozin in type 2 diabetes in Egypt

Perceptions of and Preparedness for the Application of Pharmacoeconomics in Practice, among Final Year Bachelor of Pharmacy Students in South Africa: A National Cross-Sectional Study

For the improvement of access to health, many countries including South Africa, have adopted universal healthcare. However, this requires skills to apply health technology assessments for the facilitation of investment decisions. This study aimed to ascertain final year Bachelor of Pharmacy (BPharm) students' perceptions of the relevance of pharmacoeconomics in pharmacy practice, and their level of preparedness to apply pharmacoeconomic principles, using a quantitative, cross-sectional, and descriptive design. Data were collected using a self-administered questionnaire over 12 months, and included student demographics, knowledge about pharmacoeconomics and its applicability in practice, as well as students' satisfaction with the appropriateness of the curriculum content. Five of nine universities offering pharmacy education took part. The overallstudent response rate was 38.1% (189/496), with 26.2% (45/172) of students signifying a good understanding of basic pharmacoeconomic concepts. Pharmacoeconomics application in South Africa was perceived to be relevant by 87.5% (140/160); however, 47.0% (79/168) felt they were not prepared to apply pharmacoeconomic principles in medicine management, and 86.7% (137/158) wanted to acquire additional pharmacoeconomic knowledge. Whilst students' perceptions of the relevance of pharmacoeconomics were positive, results indicated a gap in knowledge, understanding, and application. Addressing this gap may increase students' preparedness to apply pharmacoeconomic principles and better equip them for the practical application of pharmacoeconomics post qualification. Consequently, we have started this process.

Budget Impact Analysis of Diabetes Drugs: A Systematic Literature Review

Background: Budget impact analysis (BIA) is an economic assessment that estimates the financial consequences of adopting a new intervention. BIA is used to make informed reimbursement decisions, as a supplement to cost-effectiveness analyses (CEAs). Objectives: We systematically reviewed BIA studies associated with anti-diabetic drugs and assessed the extent to which international BIA guidelines were followed in these studies. Methods: We conducted a literature search on PubMed, Web of Science, Econlit, Medline, China National Knowledge Infrastructure (CNKI), Wanfang Data knowledge Service platform from database inception to June 30, 2021. ISPOR good practice guidelines were used as a methodological standard for assessing BIAs. We extracted and compared the study characteristics outlined by the ISPOR BIA Task Force to evaluate the guideline compliance of the included BIA. Results: A total of eighteen studies on the BIA for anti-diabetic drugs were identified. More than half studies were from developed countries. Seventeen studies were based on model and one study was based on real-world data. Overall, analysis considered a payer perspective, reported potential budget impacts over 1-5 years. Assumptions were mainly made about target population size, market share uptake of new interventions, and scope of cost. The data used for analysis varied among studies and was rarely justified. Model validation and sensitivity analysis were lacking in the current BIA studies. Rebate analysis was conducted in a few studies to explore the price discount that was required for new interventions to demonstrate cost equivalence to comparators. Conclusion: Existing studies evaluating budget impact for anti-diabetic drugs vary greatly in methodology, some of which showed low compliance to good practice guidelines. In order for the BIA to be useful for assisting in health plan decision-making, it is important for future studies to optimize compliance to national or ISPOR good practice guidelines on BIA. Model validation and sensitivity analysis should also be improved in future BIA studies. Continued improvement of BIA using real-world data is necessary to ensure high-quality analyses and to provide reliable results.