Long-Term Impact of Medicaid Expansion on Prostate Cancer Screening.

INTRODUCTION: Prostate cancer is the most common noncutaneous malignancy in men. The updated PSA testing 2018 United States Preventive Services Task Force guidelines recommend shared decision-making for men ages 55 to 69. In 2010, the Affordable Care Act expanded Medicaid coverage to childless adults earning < 138% of the federal poverty level. Thereafter, individual states have chosen to adopt or defer Medicaid expansion at different times. This allows for the opportunity to study the effects of expansion on a population that did not previously qualify for Medicaid. We examine the long-term association of Medicaid expansion on prostate cancer screening. METHODS: Data from the Behavioral Risk Factor Surveillance System were extracted for childless men earning less than 138% of the federal poverty level in states with different Medicaid expansion statuses from 2012 to 2020. States were classified into 4 expansion categories: very early expansion states, early expansion states, late expansion states, and nonexpansion states. Prevalence of PSA screening was determined for each category of expansion. Difference-in-difference analyses were used to understand variations in very early expansion states, early expansion states, and late expansion states trends with reference to nonexpansion states. RESULTS: PSA screening prevalence decreased in very early expansion states (27.76% vs 18.50%), early expansion states (33.79% vs 18.09%), late expansion states (36.08% vs 19.14%), and nonexpansion states (38.82% vs 24.40%) from 2012 to 2020. However, the difference-in-difference analyses did not show statistically significant results among any of the years and expansion category groups in our study period. CONCLUSIONS: PSA screening prevalence decreased in all states, regardless of expansion category. No long-term effect of Medicaid expansion on PSA screening prevalence was observed among states with different expansion statuses.

Prostate-specific antigen testing rates in high-risk populations: results from the All of Us Research Program.

BACKGROUND: Early detection of prostate cancer using prostate-specific antigen (PSA) remains controversial and disparities in the receipt of prostate cancer screening persist in the US. We sought to examine disparities in PSA testing rates among groups with higher prostate cancer risk and differential access to healthcare. METHODS: We identified a cohort of 37,706 males within the All of Us Research Program without a history of prostate cancer between the ages of 40 and 85 at time of enrollment (2017-2021). Incidence rate ratios (IRR) for the number of PSA tests received during follow-up through December 2021 were estimated using age- and multivariable-adjusted negative binomial regression models. PSA testing frequencies in the cohort were compared with population-based estimates from the 2020 Behavioral Risk Factor Surveillance System (BRFSS). RESULTS: A total of 6,486 males (17.2%) received at least one PSA test over the course of follow-up. In multivariable-adjusted models, non-Hispanic Black males received PSA tests at a 17% lower rate (IRR = 0.83, 95% CI 0.76, 0.90) than non-Hispanic White males. Higher educational attainment, higher annual income, having self-/employer-purchased insurance, having a spouse or domestic partner, and having a family history of prostate cancer were all associated with higher rates of PSA testing. The proportion of males ages 55 to 69 who received a PSA test within two years was lower in All of Us (12.4%, 95% CI 11.8-13.0%) relative to population-based estimates from the BRFSS (35.2%, 95% CI 34.2-36.3%). CONCLUSION: Absolute PSA testing rates in All of Us were lower than population-based estimates, but associations with PSA testing in the cohort mirrored previously reported disparities in prostate cancer screening. These findings highlight the importance of addressing barriers to care in order to reduce disparities in cancer screening.

Disparities in Travel-Related Barriers to Accessing Health Care From the 2017 National Household Travel Survey.

Importance: Geographic access, including mode of transportation, to health care facilities remains understudied. Objective: To identify sociodemographic factors associated with public vs private transportation use to access health care and identify the respondent, trip, and community factors associated with longer distance and time traveled for health care visits. Design, Setting, and Participants: This cross-sectional study used data from the 2017 National Household Travel Survey, including 16 760 trips or a nationally weighted estimate of 5 550 527 364 trips to seek care in the United States. Households that completed the recruitment and retrieval survey for all members aged 5 years and older were included. Data were analyzed between June and August 2022. Exposures: Mode of transportation (private vs public transportation) used to seek care. Main Outcomes and Measures: Survey-weighted multivariable logistic regression models were used to identify factors associated with public vs private transportation and self-reported distance and travel time. Then, for each income category, an interaction term of race and ethnicity with type of transportation was used to estimate the specific increase in travel burden associated with using public transportation compared a private vehicle for each race category. Results: The sample included 12 092 households and 15 063 respondents (8500 respondents [56.4%] aged 51-75 years; 8930 [59.3%] females) who had trips for medical care, of whom 1028 respondents (6.9%) were Hispanic, 1164 respondents (7.8%) were non-Hispanic Black, and 11 957 respondents (79.7%) were non-Hispanic White. Factors associated with public transportation use included non-Hispanic Black race (compared with non-Hispanic White: adjusted odds ratio [aOR], 3.54 [95% CI, 1.90-6.61]; P < .001) and household income less than $25 000 (compared with ≥$100 000: aOR, 7.16 [95% CI, 3.50-14.68]; P < .001). The additional travel time associated with use of public transportation compared with private vehicle use varied by race and household income, with non-Hispanic Black respondents with income of $25 000 to $49 999 experiencing higher burden associated with public transportation (mean difference, 81.9 [95% CI, 48.5-115.3] minutes) than non-Hispanic White respondents with similar income (mean difference, 25.5 [95% CI, 17.5-33.5] minutes; P < .001). Conclusions and Relevance: These findings suggest that certain racial, ethnic, and socioeconomically disadvantaged populations rely on public transportation to seek health care and that reducing delays associated with public transportation could improve care for these patients.

Access to definitive treatment and survival for intermediate-risk and high-risk prostate cancer at hospital systems serving health disparity populations.

INTRODUCTION: Although socioeconomic and racial disparities in prostate cancer (CaP) have been attributed to patient-level and physician-level factors, there is growing interest in investigating the role of the facility of care in driving cancer disparities. We sought to examine the receipt of guideline-concordant definitive treatment, time to treatment initiation (TTI), and overall survival (OS) for men with CaP receiving care at hospital systems serving health disparity populations (HSDPs). METHODS: We retrospective analyzed the National Cancer Database (2004-2016). We identified men with intermediate-risk or high-risk CaP eligible for definitive treatment. The primary outcomes were receipt of definitive treatment and TTI within 90 days of diagnosis. The secondary outcome was OS. We defined HSDPs as minority-serving hospitals-facilities in the highest decile of proportion of non-Hispanic Black (NHB) or Hispanic cancer patients-and/or high-burden safety-net hospitals-facilities in the highest quartile of proportion of underinsured patients. We used mixed-effect models with facility-level random intercept to compare outcomes between HSDPs and non-HSDPs among the entire cohort and among men who received definitive treatment. RESULTS: We included 968 non-HSDPs (72.2%) and 373 HSDPs (27.8%) facilities. Treatment at HSDPs was associated with lower adjusted odds of receipt of definitive treatment (aOR 0.64; 95% CI 0.57-0.71; P < 0.001), lower odds of TTI within 90 days of diagnosis (aOR 0.74; 95% CI 0.68-0.79; P < 0.001), and worse OS (aHR 1.05; 95% CI 1.02-1.09; P = .003) when accounting for covariates. However, no difference was found in OS if patients received definitive treatment (aHR 1.03; 95% CI 0.99-1.07; P = 0.1). NHB men at HSDPs had worse outcomes than NHB men treated at non-HSDPs as well as NHW men treated at HSDPs. CONCLUSION: Patients treated at HSDPs were less likely to receive timely definitive treatment and had worse OS, independent of their race. NHB men have worse outcomes than NHW at HSDPs. Thus, NHB men with CaP are doubly disadvantaged since they are more likely to be treated at hospitals with worse outcomes and have worse outcomes than other patients at those same institutions.

Relative impact of genetic ancestry and neighborhood socioeconomic status on all-cause mortality in self-identified African Americans.

Self-identified race/ethnicity is a correlate of both genetic ancestry and socioeconomic factors, both of which may contribute to racial disparities in mortality. Investigators often hold a priori assumptions, rarely made explicit, regarding the relative importance of these factors. We studied 2,239 self-identified African Americans (SIAA) from the Prostate, Lung, Colorectal and Ovarian screening trial enrolled from 1993-1998 and followed prospectively until 2019 or until death, whichever came first. Percent African genetic ancestry was estimated using the GRAF-Pop distance-based method. A neighborhood socioeconomic status (nSES) index was estimated using census tract measures of income, housing, and employment and linked to participant residence in 2012. We used Directed Acyclic Graphs (DAGs) to represent causal models favoring (1) biomedical and (2) social causes of mortality. Hazard ratios were estimated using Cox models adjusted for sociodemographic, behavioral, and neighborhood covariates guided by each DAG. 901 deaths occurred over 40,767 person-years of follow-up. In unadjusted (biomedical) models, a 10% increase in percent African ancestry was associated with a 7% higher rate of all-cause mortality (HR: 1.07, 95% CI: 1.02, 1.12). This effect was attenuated in covariate adjusted (social) models (aHR: 1.01, 95% CI: 0.96, 1.06). Mortality was lower comparing participants in the highest to lowest nSES quintile following adjustment for covariates and ancestry (aHR: 0.74, 95% CI: 0.57, 0.98, Ptrend = 0.017). Higher African ancestry and lower nSES were associated with higher mortality, but African ancestry was not associated with mortality following covariate adjustment. Socioeconomic factors may be more important drivers of mortality in African Americans.

Comparing absolute and relative distance and time travel measures of geographic access to healthcare facilities in rural Haiti.

INTRODUCTION: While travel distance and time are important proxies of physical access to health facilities, obtaining valid measures with an appropriate modelling method remains challenging in many settings. We compared five measures of geographic accessibility in Haiti, producing recommendations that consider available analytic resources and geospatial goals. METHODS: Eight public hospitals within the ministry of public health and population were included. We estimated distance and time between hospitals and geographic centroids of Haiti's section communes and population-level accessibility. Geographic feature data were obtained from public administrative databases, academic research databases and government satellites. We used validated geographic information system methods to produce five geographic access measures: (1) Euclidean distance (ED), (2) network distance (ND), (3) network travel time (NTT), (4) AccessMod 5 (AM5) distance (AM5D) and (5) AM5 travel time (AM5TT). Relative ranking of section communes across the measures was assessed using Pearson correlation coefficients, while mean differences were assessed using analysis of variance (ANOVA) and pairwise t-tests. RESULTS: All five geographic access measures were highly correlated (range: 0.78-0.99). Of the distance measures, ED values were consistently the shortest, followed by AM5D values, while ND values were the longest. ND values were as high as 2.3 times ED values. NTT models generally produced longer travel time estimates compared with AM5TT models. ED consistently overestimated population coverage within a given threshold compared with ND and AM5D. For example, population-level accessibility within 15 km of the nearest studied hospital in the Center department was estimated at 68% for ED, 50% for AM5D and 34% for ND. CONCLUSION: While the access measures were highly correlated, there were significant differences in the absolute measures. Consideration of the benefits and limitations of each geospatial measure together with the intended purpose of the estimates, such as relative proximity of patients or service coverage, are key to guiding appropriate use.

Impact of neighborhood socioeconomic status, income segregation, and greenness on blood biomarkers of inflammation.

BACKGROUND: Neighborhood deprivation is linked with inflammation, which may explain poorer health across populations. Behavioral risk factors are assumed to largely mediate these relationships, but few studies have examined this. We examined three neighborhood contextual factors that could exert direct effects on inflammation: (1) neighborhood socioeconomic status, (2) an index of concentration at extremes (that measures segregation), and (3) surrounding vegetation (greenness). METHODS: Using blood samples and addresses collected from prospective cohorts of 7,930 male (1990-1994) and 16,183 female (1986-1990) health professionals with at least one inflammatory marker, we prospectively linked neighborhood contextual factors to inflammatory biomarkers (adiponectin, C-reactive protein, interleukin-6, soluble tumor necrosis factor receptor-2). Log-transformed, z-scaled component measures were used to calculate an inflammation score. Neighborhood socioeconomic status and index of concentration of extremes were obtained from the 1990 decennial census and linked to participant addresses. Surrounding greenness was assessed from satellite data and focal statistics were applied to generate exposures within 270 m and 1230 m of the participants' address. We fit multiple linear regression models adjusting for demographic, clinical, and behavioral risk factors. RESULTS: Higher neighborhood socioeconomic status was associated with lower inflammation score in women (ß for interquartile range increase = -27.7%, 95% CI: -34.9%, -19.8%) and men (ß = -21.2%, 95% CI: -31.0%, -10.1%). Similarly, participants in neighborhoods with higher concentrations of high-income households were associated with lower inflammation score in women (ß = -27.8%, 95% CI: -35.8%, -18.7%) and men (ß = -16.4%, 95% CI: -29.7%, -0.56%). Surrounding greenness within 270 m of each participant's address was associated with lower inflammation score in women (ß = -18.9%, 95% CI: -28.9%, -7.4%) but not men. Results were robust to sensitivity analyses to assess unmeasured confounding and selection bias. DISCUSSION: Our findings support the hypothesis that adverse neighborhood environments may contribute to inflammation through pathways independent of behavioral risk factors, including psychosocial stress and toxic environments.

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.

Sustaining planetary health through systems thinking: Public health's critical role.

Understanding and responding to adverse human health impacts of global environmental change will be a major priority of 21st century public health professionals. The emerging field of planetary health aims to face this challenge by studying and promoting policies that protect the health of humans and of the Earth's natural systems that support them. Public health, drawing on its experience of guiding policies to improve population health, has contributed to planetary health's development. Yet, few public health practitioners are familiar with planetary health's systems-oriented approaches for understanding relationships between economic development, environmental degradation, and human health. In this narrative review, we present key planetary health concepts and show how systems thinking has guided its development. We discuss historical approaches to studying impacts of economic development on human health and the environment. We then review novel conceptual frameworks adopted by planetary health scientists to study and forecast impacts of policies that influence human health and Earth's natural systems at varying spatiotemporal scales. We conclude by presenting examples of how applying the "Doughnut" model (an economic framework where the needs of people are met without overshooting the world's ecological limits) could guide policies for promoting health co-benefits to humans and natural systems.

Racial differences in the treatment and outcomes for prostate cancer in Massachusetts.

BACKGROUND: Massachusetts is a northeastern state with universally mandated health insurance since 2006. Although Black men have generally worse prostate cancer outcomes, emerging data suggest that they may experience equivalent outcomes within a fully insured system. In this setting, the authors analyzed treatments and outcomes of non-Hispanic White and Black men in Massachusetts. METHODS: White and Black men who were 20 years old or older and had been diagnosed with localized intermediate- or high-risk nonmetastatic prostate cancer in 2004-2015 were identified in the Massachusetts Cancer Registry. Adjusted logistic regression models were used to assess predictors of definitive therapy. Adjusted and unadjusted survival models compared cancer-specific mortality. Interaction terms were then used to assess whether the effect of race varied between counties. RESULTS: A total of 20,856 men were identified. Of these, 19,287 (92.5%) were White. There were significant county-level differences in the odds of receiving definitive therapy and survival. Survival was worse for those with high-risk cancer (adjusted hazard ratio [HR], 1.50; 95% CI, 1.4-1.60) and those with public insurance (adjusted HR for Medicaid, 1.69; 95% CI, 1.38-2.07; adjusted HR for Medicare, 1.2; 95% CI, 1.14-1.35). Black men were less likely to receive definitive therapy (adjusted odds ratio, 0.78; 95% CI, 0.74-0.83) but had a 17% lower cancer-specific mortality (adjusted HR, 0.83; 95% CI, 0.7-0.99). CONCLUSIONS: Despite lower odds of definitive treatment, Black men experience decreased cancer-specific mortality in comparison with White men in Massachusetts. These data support the growing body of research showing that Black men may achieve outcomes equivalent to or even better than those of White men within the context of a well-insured population. LAY SUMMARY: There is a growing body of evidence showing that the excess risk of death among Black men with prostate cancer may be caused by disparities in access to care, with few or no disparities seen in universally insured health systems such as the Veterans Affairs and US Military Health System. Therefore, the authors sought to assess racial disparities in prostate cancer in Massachusetts, which was the earliest US state to mandate universal insurance coverage (in 2006). Despite lower odds of definitive treatment, Black men with prostate cancer experience reduced cancer-specific mortality in comparison with White men in Massachusetts. These data support the growing body of research showing that Black men may achieve outcomes equivalent to or even better than those of White men within the context of a well-insured population.

Trends in mortality among Black and White men with prostate cancer in Massachusetts and Pennsylvania: Race and neighborhood socioeconomic position.

BACKGROUND: Reducing disparities in men with prostate cancer (PCa) that may be caused by racial and socioeconomic differences is a major public health priority. Few reports have studied whether these disparities have changed over time. METHODS: Men diagnosed with PCa from January 1, 2000 to December 31, 2015 were identified from the Massachusetts and Pennsylvania cancer registries. All-cause mortality and PCa and cardiovascular cause-specific mortality were assessed. To estimate neighborhood socioeconomic position (nSEP), a summary score was generated using census tract-level measures of income, wealth, educational attainment, and racial and income segregation. Participants were grouped by diagnosis year (2000-2003, 2004-2007, 2008-2011, or 2012-2015), and changing trends in the mortality rate ratio by race and nSEP were estimated using covariate-adjusted Cox models with follow-up for up to 10 years, until death, or until censoring on January 1, 2018. RESULTS: There were 193,883 patients with PCa and 43,661 deaths over 1,404,131 person-years of follow-up. The Black-White adjusted hazard ratio (aHR) from 2000 to 2003 through 2012 to 2015 was stable for all-cause mortality (aHR, 1.14 to 0.97; P for heterogeneity = .42), decreased for PCa-specific mortality (aHR, 1.38 to 0.93; P for heterogeneity = .005), and increased for cardiovascular mortality (aHR, 1.09 to 1.28; P for heterogeneity = .034). The aHR comparing those in the lowest versus the highest nSEP quintile increased significantly for all-cause mortality (aHR, 1.54 to 1.79; P for heterogeneity = .008), but not for PCa-specific mortality (aHR, 1.60 to 1.72; P for heterogeneity = .40) or cardiovascular mortality (aHR, 1.72 to 1.89; P for heterogeneity = .085). CONCLUSIONS: Although Black-White disparities in prostate mortality declined in Massachusetts and Pennsylvania over the study period, nSEP mortality disparity trends were stagnant or increased, warranting further attention. LAY SUMMARY: Few reports have examined whether racial and socioeconomic disparities in prostate cancer mortality have widened or narrowed in recent years. Using data from 2 state registries (Massachusetts and Pennsylvania) with differing intensities of government-mandated health insurance, trends in racial and neighborhood socioeconomic disparities were studied among Black and White men diagnosed from 2000 to 2015. Overall, trends in racial disparities were stagnant for all-cause mortality, shrank for prostate mortality, and widened for cardiovascular mortality. Disparities associated with neighborhood socioeconomic status either were stagnant or widened across all mortality end points. In general, disparities were more pronounced in Pennsylvania than in Massachusetts.

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.

Cost-effectiveness of a mentorship and quality improvement intervention to enhance the quality of antenatal care at rural health centers in Rwanda.

OBJECTIVE: To estimate cost-effectiveness of Mentorship, Enhanced Supervision for Healthcare and Quality Improvement (MESH-QI) intervention to strengthen the quality of antenatal care at rural health centers in rural Rwanda. DESIGN: Cost-effectiveness analysis of the MESH-QI intervention using the provider perspective. SETTING: Kirehe and Rwinkwavu District Hospital catchment areas, Rwanda. INTERVENTION: MESH-QI. MAIN OUTCOME MEASURES: Incremental cost per antenatal care visit with complete danger sign and vital sign assessments. RESULTS: The total annual costs of standard antenatal care supervision was 10 777.21 USD at the baseline, whereas the total costs of MESH-QI intervention was 19 656.53 USD. Human resources (salary and benefits) and transport drove the majority of program expenses, (44.8% and 40%, respectively). Other costs included training of mentors (12.9%), data management (6.5%) and equipment (6.5%). The incremental cost per antenatal care visit attributable to MESH-QI with all assessment items completed was 0.70 USD for danger signs and 1.10 USD for vital signs. CONCLUSIONS: MESH-QI could be an affordable and effective intervention to improve the quality of antenatal care at health centers in low-resource settings. Cost savings would increase if MESH-QI mentors were integrated into the existing healthcare systems and deployed to sites with higher volume of antenatal care visits.

A Comparison of Health Achievements in Rwanda and Burundi.

Strong primary health care systems are essential for implementing universal health coverage and fulfilling health rights entitlements, but disagreement exists over how best to create them. Comparing countries with similar histories, lifestyle practices, and geography but divergent health outcomes can yield insights into possible mechanisms for improvement. Rwanda and Burundi are two such countries. Both faced protracted periods of violence in the 1990s, leading to significant societal upheaval. In subsequent years, Rwanda's improvement in health has been far greater than Burundi's. To understand how this divergence occurred, we studied trends in life expectancy following the periods of instability in both countries, as well as the health policies implemented after these conflicts. We used the World Bank's World Development Indicators to assess trends in life expectancy in the two countries and then evaluated health policy reforms using Walt and Gilson's framework. Following both countries' implementation of health sector policies in 2005, we found a statistically significant increase in life expectancy in Rwanda after adjusting for GDP per capita (14.7 years, 95% CI: 11.4-18.0), relative to Burundi (4.6 years, 95% CI: 1.8-7.5). Strong public sector leadership, investments in health information systems, equity-driven policies, and the use of foreign aid to invest in local capacity helped Rwanda achieve greater health gains compared to Burundi.

Economic evaluation of a mentorship and enhanced supervision program to improve quality of integrated management of childhood illness care in rural Rwanda.

BACKGROUND: Integrated management of childhood illness (IMCI) can reduce under-5 morbidity and mortality in low-income settings. A program to strengthen IMCI practices through Mentorship and Enhanced Supervision at Health centers (MESH) was implemented in two rural districts in eastern Rwanda in 2010. METHODS: We estimated cost per improvement in quality of care as measured by the difference in correct diagnosis and correct treatment at baseline and 12 months of MESH. Costs of developing and implementing MESH were estimated in 2011 United States Dollars (USD) from the provider perspective using both top-down and bottom-up approaches, from programmatic financial records and site-level data. Improvement in quality of care attributed to MESH was measured through case management observations (n = 292 cases at baseline, 413 cases at 12 months), with outcomes from the intervention already published. Sensitivity analyses were conducted to assess uncertainty under different assumptions of quality of care and patient volume. RESULTS: The total annual cost of MESH was US$ 27,955.74 and the average cost added by MESH per IMCI patient was US$1.06. Salary and benefits accounted for the majority of total annual costs (US$22,400 /year). Improvements in quality of care after 12 months of MESH implementation cost US$2.95 per additional child correctly diagnosed and $5.30 per additional child correctly treated. CONCLUSIONS: The incremental costs per additional child correctly diagnosed and child correctly treated suggest that MESH could be an affordable method for improving IMCI quality of care elsewhere in Rwanda and similar settings. Integrating MESH into existing supervision systems would further reduce costs, increasing potential for spread.

Improving district facility readiness: a 12-month evaluation of a data-driven health systems strengthening intervention in rural Rwanda.

BACKGROUND: While health systems strengthening (HSS) interventions are recommended by global health policy experts to improve population health in resource-limited settings, few examples exist of evaluations of HSS interventions conducted at the district level. In 2009, a partnership between Partners In Health (PIH), a non-governmental organization, and the Rwandan Ministry of Health (RMOH) was provided funds to implement and evaluate a district-level HSS intervention in two rural districts of Rwanda. DESIGN: The partnership provided limited funds to 14 health centers for targeted systems support in 2010; six others received support prior to the intervention (reference). RMOH health systems norms were mapped across the WHO HSS framework, scored from 0 to 10 and incorporated into a rapid survey assessing 11 domains of facility readiness. Stakeholder meetings allowed partnership leaders to review results, set priorities, and allocate resources. Investments included salary support, infrastructure improvements, medical equipment, and social support for patients. We compared facility domain scores from the start of the intervention to 12 months and tested for correlation between change in score and change in funding allocation to assess equity in our approach. RESULTS: We found significant improvements among intervention facilities from baseline to 12 months across several domains [infrastructure (+4, p=0.0001), clinical services (+1.2, p=0.03), infection and sanitation control (+0.6, p=0.03), medical equipment (+1.0, p=0.02), information use (+2, p=0.002)]. Composite score across domains improved from 6.2 at baseline to 7.4 at 12 months (p=0.002). Across facilities, 50% had composite scores greater than the average score among reference facilities (7.4) at 12 months compared to none at baseline. CONCLUSIONS: Rapid facility surveys, stakeholder engagement, and information feedback can be used for gap analysis and resource allocation. This approach can achieve effective use of limited resources, improve facility readiness, and ensure consistency of facility capacity to provide quality care at the district level.

Toward utilization of data for program management and evaluation: quality assessment of five years of health management information system data in Rwanda.

BACKGROUND: Health data can be useful for effective service delivery, decision making, and evaluating existing programs in order to maintain high quality of healthcare. Studies have shown variability in data quality from national health management information systems (HMISs) in sub-Saharan Africa which threatens utility of these data as a tool to improve health systems. The purpose of this study is to assess the quality of Rwanda's HMIS data over a 5-year period. METHODS: The World Health Organization (WHO) data quality report card framework was used to assess the quality of HMIS data captured from 2008 to 2012 and is a census of all 495 publicly funded health facilities in Rwanda. Factors assessed included completeness and internal consistency of 10 indicators selected based on WHO recommendations and priority areas for the Rwanda national health sector. Completeness was measured as percentage of non-missing reports. Consistency was measured as the absence of extreme outliers, internal consistency between related indicators, and consistency of indicators over time. These assessments were done at the district and national level. RESULTS: Nationally, the average monthly district reporting completeness rate was 98% across 10 key indicators from 2008 to 2012. Completeness of indicator data increased over time: 2008, 88%; 2009, 91%; 2010, 89%; 2011, 90%; and 2012, 95% (p<0.0001). Comparing 2011 and 2012 health events to the mean of the three preceding years, service output increased from 3% (2011) to 9% (2012). Eighty-three percent of districts reported ratios between related indicators (ANC/DTP1, DTP1/DTP3) consistent with HMIS national ratios. Conclusion and policy implications: Our findings suggest that HMIS data quality in Rwanda has been improving over time. We recommend maintaining these assessments to identify remaining gaps in data quality and that results are shared publicly to support increased use of HMIS data.

Resource Utilization and Costs of Care prior to ART Initiation for Pediatric Patients in Zambia.

Objective. We estimated time to initiation, outpatient resource use, and costs of outpatient care during the 6 months prior to ART initiation for HIV-infected pediatric patients in Zambia. Methods. We enrolled 1,102 children who initiated ART at <15 years of age between 2006 and 2011 at 5 study sites. Of these, 832 initiated ART ≤6 months after first presenting to care at the study sites. Data on time in care and resources utilized during the 6 months prior to ART initiation were extracted from patient medical records. Costs were estimated from the provider's perspective and are reported in 2011 USD. Results. For the patients who initiated ART ≤6 months after presenting to care, median age at presentation to care was 3.9 years; median CD4 percentage was 13%. Median time to ART initiation was 26 days. Patients made, on average, 2.38 clinic visits prior to ART initiation and received 0.81 CD4 tests, 0.74 full blood count tests, and 0.49 blood chemistry tests. The mean cost of pre-ART care was $20 per patient. Conclusions. Zambian pediatric patients initiating ART ≤6 months after presenting to care do so quickly, utilize fewer resources than mandated by national guidelines, and accrue low costs.

Retention in care, resource utilization, and costs for adults receiving antiretroviral therapy in Zambia: a retrospective cohort study.

BACKGROUND: Of the estimated 800,000 adults living with HIV in Zambia in 2011, roughly half were receiving antiretroviral therapy (ART). As treatment scale up continues, information on the care provided to patients after initiating ART can help guide decision-making. We estimated retention in care, the quantity of resources utilized, and costs for a retrospective cohort of adults initiating ART under routine clinical conditions in Zambia. METHODS: Data on resource utilization (antiretroviral [ARV] and non-ARV drugs, laboratory tests, outpatient clinic visits, and fixed resources) and retention in care were extracted from medical records for 846 patients who initiated ART at ≥15 years of age at six treatment sites between July 2007 and October 2008. Unit costs were estimated from the provider's perspective using site- and country-level data and are reported in 2011 USD. RESULTS: Patients initiated ART at a median CD4 cell count of 145 cells/µL. Fifty-nine percent of patients initiated on a tenofovir-containing regimen, ranging from 15% to 86% depending on site. One year after ART initiation, 75% of patients were retained in care. The average cost per patient retained in care one year after ART initiation was $243 (95% CI, $194-$293), ranging from $184 (95% CI, $172-$195) to $304 (95% CI, $290-$319) depending on site. Patients retained in care one year after ART initiation received, on average, 11.4 months' worth of ARV drugs, 1.5 CD4 tests, 1.3 blood chemistry tests, 1.4 full blood count tests, and 6.5 clinic visits with a doctor or clinical officer. At all sites, ARV drugs were the largest cost component, ranging from 38% to 84% of total costs, depending on site. CONCLUSIONS: Patients initiate ART late in the course of disease progression and a large proportion drop out of care after initiation. The quantity of resources utilized and costs vary widely by site, and patients utilize a different mix of resources under routine clinical conditions than if they were receiving fully guideline-concordant care. Improving retention in care and guideline concordance, including increasing the use of tenofovir in first-line ART regimens, may lead to increases in overall treatment costs.