Evaluating urban-rural access to pathology and laboratory medicine services in Tanzania.

Placement of pathology and laboratory medicine (PALM) services requires balancing efficiency (maximizing test volume) with equitable urban-rural access. We compared the association between population density (proxy for efficiency) and travel time to the closest facility (proxy for equitable access) across levels of Tanzania's public sector health system. We linked geospatial data for Tanzania from multiple sources. Data on facility locations and other geographic measures were collected from government and non-governmental databases. We classified facilities assuming increasing PALM availability by tier: (1) dispensaries, (2) health centres, (3) district hospitals and (4) regional/referral hospitals. We used the AccessMod 5 algorithm to estimate travel time to the closest facility for each tier across Tanzania with 500-m resolution. District-level average population density and travel time to the closest facility were calculated and presented using medians and interquartile ranges. Spatial correlations between these variables were estimated using the global Moran's I and bivariate Local Indicator of Spatial Autocorrelation, specifying a queen's neighbourhood matrix. Spatial analysis was restricted to 171 contiguous districts. The study included 5406 dispensaries, 675 health centres, 186 district hospitals and 37 regional/referral hospitals. District-level travel times were shortest for Tier 1 (median: [IQR]: 45.4 min [30.0-74.7]) and longest for Tier 4 facilities (160.2 min [107.3-260.0]). There was a weak spatial autocorrelation across tiers (Tier 1: -0.289, Tier 2: -0.292, Tier 3: -0.271 and Tier 4: -0.258) and few districts were classified as significant spatial outliers. Across tiers, geographic patterns of populated districts surrounded by neighbours with short travel time and sparsely populated districts surrounded by neighbours with long travel time were observed. Similar spatial correlation measures across health system levels suggest that Tanzania's health system reflects equitable urban-rural access to different PALM services. Longer travel times to hospital-based care could be ameliorated by shifting specialized diagnostics to more accessible lower tiers.

Geospatial evaluation of trade-offs between equity in physical access to healthcare and health systems efficiency.

INTRODUCTION: Decisions regarding the geographical placement of healthcare services require consideration of trade-offs between equity and efficiency, but few empirical assessments are available. We applied a novel geospatial framework to study these trade-offs in four African countries. METHODS: Geolocation data on population density (a surrogate for efficiency), health centres and cancer referral centres in Kenya, Malawi, Tanzania and Rwanda were obtained from online databases. Travel time to the closest facility (a surrogate for equity) was estimated with 1 km resolution using the Access Mod 5 least cost distance algorithm. We studied associations between district-level average population density and travel time to closest facility for each country using Pearson's correlation, and spatial autocorrelation using the Global Moran's I statistic. Geographical clusters of districts with inefficient resource allocation were identified using the bivariate local indicator of spatial autocorrelation. RESULTS: Population density was inversely associated with travel time for all countries and levels of the health system (Pearson's correlation range, health centres: -0.89 to -0.71; cancer referral centres: -0.92 to -0.43), favouring efficiency. For health centres, negative spatial autocorrelation (geographical clustering of dissimilar values of population density and travel time) was weaker in Rwanda (-0.310) and Tanzania (-0.292), countries with explicit policies supporting equitable access to rural healthcare, relative to Kenya (-0.579) and Malawi (-0.543). Stronger spatial autocorrelation was observed for cancer referral centres (Rwanda: -0.341; Tanzania: -0.259; Kenya: -0.595; Malawi: -0.666). Significant geographical clusters of sparsely populated districts with long travel times to care were identified across countries. CONCLUSION: Negative spatial correlations suggested that the geographical distribution of health services favoured efficiency over equity, but spatial autocorrelation measures revealed more equitable geographical distribution of facilities in certain countries. These findings suggest that even when prioritising efficiency, thoughtful decisions regarding geographical allocation could increase equitable physical access to services.

Age-Standardized Mortality Rates in the Caribbean: One Source, Three Different Interpretations.

Purpose A recent publication in Morbidity and Mortality Weekly Report ( MMWR) provided the opportunity to calculate differences in published cancer mortality estimates for Caribbean jurisdictions from three organizations: MMWR, the International Agency for Research on Cancer, and the Institute for Health Metrics and Evaluation. This comparison study serves to educate end users of these data. Methods We downloaded the publicly available cancer mortality estimates for 15 jurisdictions and the United States from the three organizations. We compared reported age-standardized mortality rates for each jurisdiction and calculated the range among estimates for each jurisdiction. We repeated this analysis after applying the same world population standard to all estimates. Results For males, the ranges of the Caribbean estimates were between 49% (Grenada and Trinidad) and 201% (US Virgin Islands) of the MMWR value, with an average of 88%. For females, the ranges were between 15% (Trinidad) and 171% (US Virgin Islands) of the MMWR value, with an average of 64%. After all estimates were compared using the same population standard, the ranges of the Caribbean estimates for males were between 6% (Grenada) and 111% (US Virgin Islands) of the MMWR value, with an average of 34%. For females, the ranges were between 7% (Grenada) and 97% (US Virgin Islands), with an average of 28%. Conclusion The use of different standard populations complicates comparisons across organizations. Data modeling does not completely compensate for quality of source data, as our analysis demonstrated by the differences in mortality rates despite the good quality of the vital registration in the Caribbean.

Global Health Pathology Research: Purpose and Funding.

Like in all areas of science, it is important for funders and investigators of pathology to work together to develop a well-designed, well-executed clinical research agenda. In the first section of this article, the authors discuss how the National Institutes of Health (NIH) peer-review process applies to global health pathology research projects. Then, the authors present an illustrative sampling of NIH-funded projects with performance sites in low- and middle-income countries with 2 examples focused on cancer and anatomic pathology. Finally, the authors relate the research agenda to overarching strategic recommendations for enhancing global pathology.