Identifying the most effective essential medicines policies for quality use of medicines: A replicability study using three World Health Organisation data-sets

Abstract

Background: Poor quality use of medicines (QUM) has adverse outcomes. Governments' implementation of essential medicines (EM) policies is often suboptimal and there is limited information on which policies are most effective.

Methods: We analysed data on policy implementation from World Health Organisation (WHO) surveys in 2007 and 2011, and QUM data from surveys during 2006-2012 in developing and transitional countries. We compared QUM scores in countries that did or did not implement specific policies and regressed QUM composite scores on the numbers of policies implemented. We compared the ranking of policies in this and two previous studies, one from the same WHO databases (2003-2007) the other from data obtained during country visits in South-East Asia (2010-2015). The rankings of a common set of 17 policies were correlated and we identified those that were consistently highly ranked.

Findings: Fifty-three countries had data on both QUM and policy implementation. Forty policies were associated with effect sizes ranging from +13% to -5%. There was positive correlation between the composite QUM indicator and the number of policies reported implemented: (r) = 0.437 (95% CI 0.188 to 0.632). Comparison of policy rankings between the present and previous studies showed positive correlation with the WHO 2003-7 study: Spearman's rank correlation coefficient 0.498 (95% CI 0.022 to 0.789). Across the three studies, five policies were in the top five ranked positions 11 out of a possible 15 times: drugs available free at the point of care; a government QUM unit; undergraduate training of prescribers in standard treatment guidelines, antibiotics not available without prescription and generic substitution in the public sector.

Interpretation: Certain EM policies are associated with better QUM and impact increases with co-implementation. Analysis across three datasets provides a policy short-list as a minimum investment by countries trying to improve QUM and reduce antimicrobial drug misuse.

Fig 1. Differences in quality use of medicines between countries that did versus did not report implementation of specific medicine policies.

Bars and numbers represent the estimated mean effect and 95% CI for the mean effect of each policy on a composite measure of QUM. X-axis acronyms: AMR = antimicrobial resistance; EML = Essential Medicines List; QUM = Quality Use of Medicines; STG = Standard Treatment Guideline; OTC = Over-the-Counter; DTC = Drug and Therapeutic Committee; ADR = Adverse Drug Reaction; CME = Continuing Medical Education.

Fig 2. Scatter-gram of the composite QUM indicator score versus the number of policies reported implemented.

Data is good enough to show better QUM with implementation of more policies, but not to benchmark country performance.

Fig 3. Scatter-gram of the % upper respiratory tract infection cases treated with antibiotics versus the number of policies reported implemented.

Data is good enough to show less antibiotic use in upper respiratory tract infection with implementation of more policies, but not to benchmark country performance.