An econometric method for estimating population parameters from non‐random samples: An application to clinical case finding

The problem of sample selection complicates the process of drawing inference about populations. Selective sampling arises in many real world situations when agents such as doctors and customs officials search for targets with high values of a characteristic. We propose a new method for estimating population characteristics from these types of selected samples. We develop a model that captures key features of the agent’s sampling decision. We use a generalized method of moments with instrumental variables and maximum likelihood to estimate the population prevalence of the characteristic of interest and the agents’ accuracy in identifying targets. We apply this method to tuberculosis (TB), which is the leading infectious disease cause of death worldwide. We use a national database of TB test data from South Africa to examine testing for multidrug resistant TB (MDR‐TB). Approximately one quarter of MDR‐TB cases was undiagnosed between 2004 and 2010. The official estimate of 2.5% is therefore too low, and MDR‐TB prevalence is as high as 3.5%. Signal‐to‐noise ratios are estimated to be between 0.5 and 1. Our approach is widely applicable because of the availability of routinely collected data and abundance of potential instruments. Using routinely collected data to monitor population prevalence can guide evidence‐based policy making.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138309/1/hec3547.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138309/2/hec3547_am.pd

Coping with intra-household job separation in South Africa's labor market

In the context of South Africa's pervasive poverty and mass unemployment, households provide an important private safety net for the unemployed. Using new South African Labour Force Survey panel data, I investigate how households cope with job separations and the resulting loss of earned income. Unsurprisingly, I find no evidence of an added worker effect among either men or women. Neither increases in employment or labor market attachment in the year following a household job separation. Instead, households rely on remittances and, to a lesser extent, savings in the wake of a job separation. I find some evidence that households are worse off after a job separation: households reduce expenditures (even in the absence of household composition changes), hold fewer financial assets and are more likely to report frequent food insecurity. Households have viable income replacement strategies to cope with the loss of earned income in the short run, but over the long run job separations are likely to strain these strategies. Addressing structural factors in the labor market that constrain an individual's response to a household shock will enable households to respond more quickly to adverse employment events and limit the long term negative repercussions

Does directly observed therapy improve tuberculosis treatment? More evidence is needed to guide tuberculosis policy

Abstract Background Tuberculosis (TB) now ranks alongside HIV as the leading infectious disease cause of death worldwide and incurs a global economic burden of over $12 billion annually. Directly observed therapy (DOT) recommends that TB patients complete the course of treatment under direct observation of a treatment supporter who is trained and overseen by health services to ensure that patients take their drugs as scheduled. Though the current WHO End TB Strategy does not mention DOT, only “supportive treatment supervision by treatment partners”, many TB programs still use it despite the fact that the has not been demonstrated to be statistically significantly superior to self-administered treatment in ensuring treatment success or cure. Discussion DOT is designed to promote proper adherence to the full course of drug therapy in order to improve patient outcomes and prevent the development of drug resistance. Yet over 8 billion dollars is spent on TB treatment each year and thousands undergo DOT for all or part of their course of treatment, despite the absence of rigorous evidence supporting the superior effectiveness of DOT over self-administration for achieving drug susceptible TB (DS-TB) cure. Moreover, the DOT component burdens patients with financial and opportunity costs, and the potential for intensified stigma. To rigorously evaluate the effectiveness of DOT and identify the essential contributors to both successful treatment and minimized patient burden, we call for a pragmatic experimental trial conducted in real-world program settings, the gold standard for evidence-based health policy decisions. It is time to invest in the rigorous evaluation of DOT and reevaluate the DOT requirement for TB treatment worldwide. Summary Rigorously evaluating the choice of treatment supporter, the frequency of health care worker contact and the development of new educational materials in a real-world setting would build the evidence base to inform the optimal design of TB treatment protocol. Implementing a more patient-centered approach may be a wise reallocation of resources to raise TB cure rates, prevent relapse, and minimize the emergence of drug resistance. Maintaining the status quo in the absence of rigorous supportive evidence may diminish the effectiveness of TB control policies in the long run.http://deepblue.lib.umich.edu/bitstream/2027.42/134652/1/12879_2016_Article_1862.pd

Assessing healthcare quality using routine data: evaluating the performance of the national tuberculosis programme in South Africa

ObjectiveTo assess the performance of healthcare facilities by means of indicators based on guidelines for clinical care of TB, which is likely a good measure of overall facility quality.MethodsWe assessed quality of care in all public health facilities in South Africa using graphical, correlation and locally weighted kernel regression analysis of routine TB test data.ResultsFacility performance falls short of national standards of care. Only 74% of patients with TB provided a second specimen for testing, 18% received follow‐up testing and 14% received drug resistance testing. Only resistance testing rates improved over time, tripling between 2004 and 2011. National awareness campaigns and changes in clinical guidelines had only a transient impact on testing rates. The poorest performing facilities remained at the bottom of the rankings over the period of study.ConclusionThe optimal policy strategy requires both broad‐based policies and targeted resources to poor performers. This approach to assessing facility quality of care can be adapted to other contexts and also provides a low‐cost method for evaluating the effectiveness of proposed interventions. Devising targeted policies based on routine data is a cost‐effective way to improve the quality of public health care provided.ObjectifEvaluer la performance des établissements de santé au moyen d’indicateurs basés sur des directives pour les soins cliniques de la tuberculose (TB), qui sont probablement une bonne mesure de la qualité globale des établissements.MéthodesNous avons évalué la qualité des soins dans tous les établissements de santé publique en Afrique du Sud à l’aide d’une analyse de régression graphique, de corrélation et localement pondérée des données de dépistage de routine de la TB.RésultatsLa performance des établissements ne respecte pas les normes nationales de soins. Seuls 74% des patients TB ont fourni un deuxième échantillon pour les tests, 18% ont reçu des tests de suivi et 14% ont reçu des tests de résistance aux médicaments. Seuls les taux de dépistage de la résistance se sont améliorés au cours du temps, en triplant entre 2004 et 2011. Les campagnes de sensibilisation nationales et les changements apportés aux directives cliniques n’ont eu qu’un impact transitoire sur les taux de dépistage. Les établissements avec la plus mauvaise performance sont restés au bas du classement au cours de la période étudiée.ConclusionLa stratégie politique optimale requiert à la fois des politiques générales et des ressources ciblées pour la mauvaise performance. Cette méthode d’évaluation de la qualité des soins peut être adaptée à d’autres contextes et procure également une méthode peu coûteuse pour évaluer l’efficacité des interventions proposées. L’élaboration de politiques ciblées basées sur des données de routine est un moyen rentable pour améliorer la qualité des soins de santé publique fournis.Mots‐clésqualité des soins, mesure de la qualité, prestation des soins de santé, politique de santé, tuberculose, résistance aux antibiotiques, Afrique du SudObjetivoEvaluar el desempeño de los centros sanitarios por medio de indicadores basados en guías para la atención clínica de la TB, lo cual podría ser una buena medida de la calidad general de las instalaciones.MétodosHemos evaluado la calidad de la atención en centros sanitarios públicos de Sudáfrica mediante análisis gráficos, correlaciones y regresiones ponderadas de Kernel utilizando datos rutinarios de TB.ResultadosEl desempeño de los centros está por debajo de los estándares nacionales de cuidado. Solo un 74% de los pacientes con TB proveyeron un segundo espécimen para pruebas, un 18% recibió pruebas de seguimiento, y un 14% pruebas de resistencia a medicamentos. Solo mejoraron a lo largo del tiempo las tasas de las pruebas de resistencia, triplicándose entre el 2004‐2011. Las campañas de concienciación nacionales y los cambios en las guías clínicas solo tenían un impacto transitorio sobre las tasas de las pruebas. Los centros con los peores resultados continuaron en lo más bajo de la clasificación a lo largo del periodo de estudio.ConclusiónLa estrategia óptima requiere tanto el uso de políticas de base amplia como de recursos dirigidos a quienes tienen un peor desempeño. Esta aproximación para evaluar la calidad de la atención de los centros puede adaptarse a otros contextos, y también provee un método de bajo coste para evaluar la efectividad de las intervenciones propuestas. La elaboración de políticas orientadas, basadas en datos rutinarios, es una forma coste‐efectiva de mejorar la calidad de la atención sanitaria pública.Palabras clavecalidad de la atención, calidad de medidas, entrega de atención sanitaria, política sanitaria, tuberculosis, resistencia a antibióticos, SudáfricaPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135966/1/tmi12819.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135966/2/tmi12819_am.pd

Distance decay and persistent health care disparities in South Africa

Abstract Background Access to health care is a particular concern given the important role of poor access in perpetuating poverty and inequality. South Africa’s apartheid history leaves large racial disparities in access despite post-apartheid health policy to increase the number of health facilities, even in remote rural areas. However, even when health services are provided free of charge, monetary and time costs of travel to a local clinic may pose a significant barrier for vulnerable segments of the population, leading to overall poorer health. Methods Using newly available health care utilization data from the first nationally representative panel survey in South Africa, together with administrative geographic data from the Department of Health, we use graphical and multivariate regression analysis to investigate the role of distance to the nearest facility on the likelihood of having a health consultation or an attended birth. Results Ninety percent of South Africans live within 7 km of the nearest public clinic, and two-thirds live less than 2 km away. However, 14% of Black African adults live more than 5 km from the nearest facility, compared to only 4% of Whites, and they are 16 percentage points less likely to report a recent health consultation (p < 0.01) and 47 percentage points less likely to use private facilities (p < 0.01). Respondents in the poorest income quintiles live 0.5 to 0.75 km further from the nearest health facility (p < 0.01). Racial differentials in the likelihood of having a health consultation or an attended birth persist even after controlling for confounders. Conclusions Our results have two policy implications: minimizing the distance that poor South Africans must travel to obtain health care and improving the quality of care provided in poorer areas will reduce inequality. Much has been done to redress disparities in South Africa since the end of apartheid but progress is still needed to achieve equity in health care access.http://deepblue.lib.umich.edu/bitstream/2027.42/109482/1/12913_2014_Article_541.pd

Understanding the relationship between access to care and facility‐based delivery through analysis of the 2008 Ghana Demographic Health Survey

ObjectiveTo determine the types of access to care most strongly associated with facility‐based delivery among women in Ghana.MethodsData relating to the “5 As of Access” framework were extracted from the 2008 Ghana Demographic Health Survey and analyzed using multivariate logistic regression.ResultsIn all, 55.5% of a weighted sample of 1102 women delivered in a healthcare facility, whereas 45.5% delivered at home. Affordability was the strongest access factor associated with delivery location, with health insurance coverage tripling the odds of facility delivery. Availability, accessibility (except urban residence), acceptability, and social access variables were not significant factors in the final models. Social access variables, including needing permission to seek healthcare and not being involved in decisions regarding healthcare, were associated with a reduced likelihood of facility‐based delivery when examined individually. Multivariate analysis suggested that these variables reflected maternal literacy, health insurance coverage, and household wealth, all of which attenuated the effects of social access.ConclusionAffordability was an important determinant of facility delivery in Ghana—even among women with health insurance—but social access variables had a mediating role.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135213/1/ijgo224.pd

A Data-Driven Evaluation of the Stop TB Global Partnership Strategy of Targeting Key Populations at Greater Risk for Tuberculosis.

OBJECTIVE:Identifying those infected with tuberculosis (TB) is an important component of any strategy for reducing TB transmission and population prevalence. The Stop TB Global Partnership recently launched an initiative with a focus on key populations at greater risk for TB infection or poor clinical outcomes, due to housing and working conditions, incarceration, low household income, malnutrition, co-morbidities, exposure to tobacco and silica dust, or barriers to accessing medical care. To achieve operational targets, the global health community needs effective, low cost, and large-scale strategies for identifying key populations. Using South Africa as a test case, we assess the feasibility and effectiveness of targeting active case finding to populations with TB risk factors identified from regularly collected sources of data. Our approach is applicable to all countries with TB testing and census data. It allows countries to tailor their outreach activities to the particular risk factors of greatest significance in their national context. METHODS:We use a national database of TB test results to estimate municipality-level TB infection prevalence, and link it to Census data to measure population risk factors for TB including rates of urban households, informal settlements, household income, unemployment, and mobile phone ownership. To examine the relationship between TB prevalence and risk factors, we perform linear regression analysis and plot the set of population characteristics against TB prevalence and TB testing rate by municipality. We overlay lines of best fit and smoothed curves of best fit from locally weighted scatter plot smoothing. FINDINGS:Higher TB prevalence is statistically significantly associated with more urban municipalities (slope coefficient β1 = 0.129, p < 0.0001, R2 = 0.133), lower mobile phone access (β1 = -0.053, p < 0.001, R2 = 0.089), lower unemployment rates (β1 = -0.020, p = 0.003, R2 = 0.048), and a lower proportion of low-income households (β1 = -0.048, p < 0.0001, R2 = 0.084). Municipalities with more low-income households also have marginally higher TB testing rates, however, this association is not statistically significant (β1 = -0.025, p = 0.676, R2 = 0.001). There is no relationship between TB prevalence and the proportion of informal settlement households (β1 = 0.021, p = 0.136, R2 = 0.014). CONCLUSIONS:These analyses reveal that the set of characteristics identified by the Global Plan as defining key populations do not adequately predict populations with high TB burden. For example, we find that higher TB prevalence is correlated with more urbanized municipalities but not with informal settlements. We highlight several factors that are counter-intuitively those most associated with high TB burdens and which should therefore play a large role in any effective targeting strategy. Targeting active case finding to key populations at higher risk of infection or poor clinical outcomes may prove more cost effective than broad efforts. However, these results should increase caution in current targeting of active case finding interventions