Availability of essential diagnostics in ten low-income and middle-income countries: results from national health facility surveys

Abstract

Background: Pathology and laboratory medicine diagnostics and diagnostic imaging are crucial to achieving universal health coverage. We analysed Service Provision Assessments (SPAs) from ten low-income and middle-income countries to benchmark diagnostic availability.

Methods: Diagnostic availabilities were determined for Bangladesh, Haiti, Malawi, Namibia, Nepal, Kenya, Rwanda, Senegal, Tanzania, and Uganda, with multiple timepoints for Haiti, Kenya, Senegal, and Tanzania. A smaller set of diagnostics were included in the analysis for primary care facilities compared with those expected at hospitals, with 16 evaluated in total. Surveys spanned 2004-18, including 8512 surveyed facilities. Country-specific facility types were mapped to basic primary care, advanced primary care, or hospital tiers. We calculated percentages of facilities offering each diagnostic, accounting for facility weights, stratifying by tier, and for some analyses, region. The tier-level estimate of diagnostic availability was defined as the median of all diagnostic-specific availabilities at each tier, and country-level estimates were the median of all diagnostic-specific availabilities of each of the tiers. Associations of country-level diagnostic availability with country income as well as (within-country) region-level availability with region-specific population densities were determined by multivariable linear regression, controlling for appropriate covariates including tier.

Findings: Median availability of diagnostics was 19·1% in basic primary care facilities, 49·2% in advanced primary care facilities, and 68·4% in hospitals. Availability varied considerably between diagnostics, ranging from 1·2% (ultrasound) to 76·7% (malaria) in primary care (basic and advanced) and from 6·1% (CT scan) to 91·6% (malaria) in hospitals. Availability also varied between countries, from 14·9% (Bangladesh) to 89·6% (Namibia). Availability correlated positively with log(income) at both primary care tiers but not the hospital tier, and positively with region-specific population density at the basic primary care tier only.

Interpretation: Major gaps in diagnostic availability exist in many low-income and middle-income countries, particularly in primary care facilities. These results can serve as a benchmark to gauge progress towards implementing guidelines such as the WHO Essential Diagnostics List and Priority Medical Devices initiatives.

Funding: Bill & Melinda Gates Foundation.

Figure 1

Availability of diagnostics by tier and country The heat map provides information on the proportion of facilities offering the diagnostic. Percentages in parentheses after each country name is the median diagnostic availability of all cells in each row. For countries with more than one survey, only the most recent was included. Countries are ranked in descending order of median availability. Availability are also sorted left to right in decreasing order of availability across countries.

Figure 2

Availability by GDP per capita Plot of marginal effects showing the association between median country-level diagnostic availability by tier with income, after adjusting with a covariate for year of survey. The interaction of income and tier had p values of 0·044 for basic primary care and 0·057 for advanced primary care tiers (appendix p 10). The interaction between tier and income is evidenced by more sloped lines at primary care tiers as compared with the hospital tier. Separate linear regressions performed independently for each tier, with Year as covariate, produced significant coefficients for basic primary care (p=0·00155), advanced primary care (p=0·0345), but not hospital (p=0·1996) tiers. GDP=gross domestic product.

Figure 3

Variation of diagnostic availability among regions of each country, by tiers In this dot plot, the IQR and QCD of region-specific availabilities are calculated for each country and tier. Outliers are depicted with asterisks and determined as described in the methods section. QCD=quartile coefficient of dispersion.

Figure 4

Region-specific availability by regional population density, by tiers Plot of marginal effects showing the association between region-level diagnostic availability and population density by tier. The interaction of population density with tier is shown by a more sloped line at the basic primary care tier than other tiers. Since the regional population density is Z score transformed within-country, the regression coefficient of 5·4 for the interaction term population density:basic primary care means a Z score population density shift of 1 is associated with an increase of 5·4 percentage points in availability at the basic primary care tier (eg, shift from 50·0% to 55·4%). See appendix p 16.