Methodology

Overview

The Exemplars in Primary Health Care study aims to systematically and comprehensively identify countries whose primary health care (PHC) systems have performed exceptionally well over the past 20 years relative to their total health spending.

Country selection

Exemplar countries were selected through a tiered process combining econometric and descriptive analyses, validated by expert input.

The selection process aimed to identify countries based on core assumptions about what makes for a strong PHC system. PHC Exemplar countries get more for each dollar spent on health, protect the most vulnerable segments of their populations, and can offer PHC improvement lessons to other countries.

Ghana falls into the second group: countries that improved their universal health coverage (UHC) effective coverage while also increasing total health expenditure (THE) per capita. Ghana’s effective coverage index increased by 25% between 2000 and 2018, and its total health spending per capita increased by 100%.¹ For reference, global health spending per capita increased 55% during the same period.²

To determine Exemplar countries, a group of low- and middle-income countries (per World Bank classifications) were ranked by technical efficiency, which is defined as overall health system performance relative to THE. Performance was measured using the Global Burden of Disease 2019 universal health coverage effective index, which comprises 23 “effective coverage” indicators (including promotion, prevention, and treatment) and five age groups.³ Effective coverage of an intervention is defined as the fraction of the potential population gains from it, adjusted for quality.

As a result, 60 countries with the highest technical efficiency—measured by a stochastic frontier analysis regressing effective coverage index data against total health expenditure for the study period—were shortlisted for further analysis.

We identified four “archetypes” of PHC performance (Figure 20):

• Countries that have strong sustained performance
• Countries that have increased spend and improved performance
• Countries that have improved performance while keeping spend near constant
• Countries that have improved performance while spending has been disrupted

Next, we examined health system performance equity, via PHC services coverage and financial protection. Equity in PHC was assessed using a published indicator of geographical inequality DTP3 coverage⁴ and out-of-pocket spending as a proportion of THE, respectively.

The final step was to identify the countries most influential to study based on the transferability of findings—namely, population size, geographic diversity, data availability—to ensure that lessons from the Exemplar countries would be widely applicable.

Conceptual framework

Country analyses were informed by the WHO-UNICEF Measurement Framework for PHC’s definition of PHC as “a whole-of-society approach to health that aims to maximize the level and distribution of health and wellbeing” through three components (Figure 21.)

• Primary care and essential public health at the core of integrated health services
• Multisectoral policy and action
• Empowered people and communities

To identify the key reform strategies in each country that improved efficiency in these domains, and the subsystems driving positive change, researchers adopted a mixed-methods approach triangulating data from a variety of sources.

Country specific retrospective study methods

The work reflected within this narrative relies on mixed methods for data collection and analysis, across national and subnational systems levels.

• Researchers first identified policies and sub-systems that were critical to achieving high PHC efficiency, and linkages between them at the national level. Data extraction included time series analysis of secondary data with a focus on financing, outputs and outcomes indicators, literature reviews of published and grey sources, key informant interviews to understand stakeholder perceptions of drivers of efficiency, and qualitative systems dynamic modeling – a technique to specify the dynamic relationships and feedback loops through which interventions and reforms improved PHC performance.
• Researchers then stratified subnational units (regions) to understand high and low performance between them – and to analyze the critical, sub-systems, linkages and operations down to health facility level. Stochastic frontier analysis was leveraged to rank subnational units according to PHC efficiency and to identify exogenous drivers (sociodemographic characteristics) that may have affected it. Site visits, primary data collection with the development and adaptation of a survey protocol, and document review were leveraged to capture operational data and details.
• Researchers then synthesized findings and transferable lessons. Findings were synthesized and integrated, controlling for context and constraints in each setting.

For more detailed and country-specific information on the PHC Exemplars methods, please refer to our research partner’s published academic manuscripts (Coming soon).

Data disclaimer

The country selection analytical process took place in 2020 and primarily leveraged Global Burden of Disease Study (GBD) data through 2018, the latest publicly available at the time. Therefore, country selection graphics and references reflect trend data from 2000 to 2018. Other references might reflect updated data, including data collection from dates outside the range of country selection years, as well as more recent GBD estimates.