Dataset sources
All medications, with some exceptions, from countries’ NEMLs hosted in the WHO’s National Essential Medicines Lists Repository were extracted and recorded in an Excel database (10,11). NEMLs for 137 countries were identified (10).
Countries received an amenable mortality score, calculated by measuring age standardized mortality rates, for ischemic heart disease, cerebrovascular disease and hypertensive heart disease (4). HAQ score was part of a larger study that combined 32 causes to create a composite, HAQ Index for 195 countries (4).
Inclusion Criteria
Countries were included if they had a NEML captured by the Global Essential Medicines (GEM) database and a HAQ score for ischemic heart disease, cerebrovascular disease and hypertensive heart disease.
Data collection
In order to identify which medications were relevant to the three causes of interest (ischemic heart disease, cerebrovascular disease and hypertensive heart disease), we used the following procedure. Guidelines for ischemic heart disease, cerebrovascular disease and hypertensive heart disease were searched for on the WHO website in June 2019. Four international guidelines distributed by the WHO, an internationally recognized health authority, were selected: Prevention and Control of Non-communicable Diseases: Guidelines for primary health care in low-resource settings (12), WHO Package of Essential Non-communicable Diseases Interventions for Primary Health Care in Low-Resource Settings (13), Technical Package for cardiovascular disease management in primary health care- evidence-based treatment protocols (7), Tackling NCDs: “Best Buys” and other recommended interventions for the prevention and control of non-communicable diseases (14). Although it is not an internationally recognized guideline, additional guidance from the American Heart Association’s website was used to ensure all relevant medicines were captured (15). These guidelines along with the WHO Model List 20th edition (16) were used to identify medicines used for treatment of ischemic heart disease, cerebrovascular disease and hypertensive heart disease. Guidelines were searched using the causes and associated International Classification of Diseases 10th revision codes provided by the HAQ score (4).
Population size, health expenditure and life expectancy were retrieved from the Global Health Observatory (17); prevalence for ischemic heart disease, cerebrovascular disease and hypertensive heart disease was retrieved from the Global Burden of Disease Study (1). Most data was for the year 2016; if 2016 data was not available, data from the closest year to 2016 was retrieved. Country characteristics can be found in Table 1.
Data extraction
Using the identified guidelines for ischemic heart disease, cerebrovascular disease and hypertensive heart disease, medications used to treat these conditions were abstracted. If a guideline indicated a therapeutic class of medicines, that class was fully expanded to include all medicines because medicines within the same chemical subgroup may be considered therapeutically similar. The WHO Model List recognizes interchangeability of certain medicines on their list for others within the same therapeutic class. (16) Using this principle, 4th level Anatomical Therapeutic Chemical Classification (ATC) codes (18) were used to guide which medicines are in the same therapeutic class. If a therapeutic class was mentioned and specific alternatives were stated, only those medicines were included (no therapeutic class expansion was done).
Medicines listed on the WHO Model List or those from guidelines appearing on the WHO Model List (in a form that is usable for the conditions or cause), with a square box symbol, were fully expanded based on the 4th level, chemical subgroup of the ATC code to include all medicines within that therapeutic class. If the medicine is not denoted with a square box it was not expanded. If specific medicines considered equivalent were stated, only those medicines were included. A medicine coverage score was created by summing the number of medicines on a country’s NEML that were also listed on our list of medicines used to treat each HAQ cause.
Data analysis
Data was analyzed using IBM SPSS Statistics version 26 (IBM Corp., 2018), and a p-value ≤ 0.05 was considered significant. An ordinary least squares linear regression model was used to test the hypothesis that there would be a positive relationship between listing medicines (medicine coverage score) and HAQ scores. HAQ score was used as the dependent variable and the previously calculated medicine coverage score was used as the independent variable. Linear regression results are reported for both unadjusted and adjusted with health expenditure, population, life expectancy and prevalence as covariates.