12 research outputs found
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Estimating Effects of Poverty on the Survival of HIV Patients on ART and Food Supplementation in Rural Haiti: A Comparative Evaluation of Socio-Economic Indicators
Background: Because economic conditions are both a risk factor for disease and may themselves be objectives for health delivery interventions, monitoring changes in economic outcomes has become a routine priority for health and development efforts. However, the lack of formal commerce in poor agrarian communities creates challenges for measuring economic status. Data on household finances, such as income, are ideal but are time-consuming, costly, and less reliable, whereas proxy measures of wealth such as indices of durable assets are easier to measure but relatively coarse and are less sensitive to rapid changes in underlying drivers.
Methods: We used data from a cohort of 528 people living with HIV/AIDS (PLHA) enrolled in a food intervention study on household demographics, agricultural production, cash income, in-kind income, household durable assets and health status, including CD4 count. We created a household economic index using principal components analysis (PCA) and compared it with three other economic indicators generated from the data (income, expenditures, poverty score). Through multivariate logistic regression analysis we evaluated the effect of the economic metric on probability of survival within the first year of study.
Results: Socioeconomic status determined by PCA of durable assets, weighted by the square root of the household size, was the only consistently significant economic predictor of probability of death. It remained significant even after controlling for direct health indicators such as CD4 count. There was no significant correlation between CD4 count and the economic indicators, which may be attributable to uniform access to ART among study participants.
Conclusion: Among people who have HIV and are all enrolled in ART and food programs, household socioeconomic status is an important predictor of mortality rates, even after controlling for direct health measurements such as CD4 count and other health-related covariates. The SES indicator from PCA is also a simple metric to estimate. The study underscores that poverty is a social determinant of mortality even in the context of equal access to health services, and is suggestive of the importance of poverty alleviation activities as an important supplement to clinical interventions
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Activity-based costing of health-care delivery, Haiti
Abstract Objective: To evaluate the implementation of a time-driven activity-based costing analysis at five community health facilities in Haiti. Methods: Together with stakeholders, the project team decided that health-care providers should enter start and end times of the patient encounter in every fifth patient’s medical dossier. We trained one data collector per facility, who manually entered the time recordings and patient characteristics in a database and submitted the data to a cloud-based data warehouse each week. We calculated the capacity cost per minute for each resource used. An automated web-based platform multiplied reported time with capacity cost rate and provided the information to health-facilities administrators. Findings: Between March 2014 and June 2015, the project tracked the clinical services for 7162 outpatients. The cost of care for specific conditions varied widely across the five facilities, due to heterogeneity in staffing and resources. For example, the average cost of a first antenatal-care visit ranged from 6.87 United States dollars (US 25.06 at a high-level facility. Within facilities, we observed similarly variation in costs, due to factors such as patient comorbidities, patient arrival time, stocking of supplies at facilities and type of visit. Conclusion: Time-driven activity-based costing can be implemented in low-resource settings to guide resource allocation decisions. However, the extent to which this information will drive observable changes at patient, provider and institutional levels depends on several contextual factors, including budget constraints, management, policies and the political economy in which the health system is situated
Adapting Lot Quality Assurance Sampling to accommodate imperfect diagnostic tests: application to COVID-19 serosurveillance in Haiti
Abstract Background Lot Quality Assurance Sampling (LQAS), a tool used for monitoring health indicators in low resource settings resulting in “high” or “low” classifications, assumes that determination of the trait of interest is perfect. This is often not true for diagnostic tests, with imperfect sensitivity and specificity. Here, we develop Lot Quality Assurance Sampling for Imperfect Tests (LQAS-IMP) to address this issue and apply it to a COVID-19 serosurveillance study design in Haiti. Methods We first derive a modified procedure, LQAS-IMP, that accounts for the sensitivity and specificity of a diagnostic test to yield correct classification errors. We then apply the novel LQAS-IMP to design an LQAS system to classify prevalence of SARS-CoV-2 antibodies among healthcare workers at eleven Zanmia Lasante health facilities in Haiti. Finally, we show the performance of the LQAS-IMP procedure in a simulation study. Results We found that when an imperfect diagnostic test is used, the classification errors in the standard LQAS procedure are larger than specified. In the modified LQAS-IMP procedure, classification errors are consistent with the specified maximum classification error. We then utilized the LQAS-IMP procedure to define valid systems for sampling at eleven hospitals in Haiti. Conclusion The LQAS-IMP procedure accounts for imperfect sensitivity and specificity in system design; if the accuracy of a test is known, the use of LQAS-IMP extends LQAS to applications for indicators that are based on laboratory tests, such as SARS-CoV-2 antibodies
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Addressing the immediate need for emergency providers in resource-limited settings: the model of a six-month emergency medicine curriculum in Haiti
Background: In many resource-limited settings, emergency medicine (EM) is underdeveloped and formal EM training limited. Residencies and fellowships are an ideal long-term solution but cannot meet immediate needs for emergency providers, while short-term programs are often too limited in content. We describe a third method successfully implemented in Haiti: a medium-duration certificate program to meet the immediate need for emergency specialists. Methods: In conjunction with the Haitian Ministry of Health and National Medical School, we developed and implemented a novel, 6-month EM certificate program to build human resources for health and emergency care capacity. The program consisted of didactic and supervised clinical components, covering core content in EM. Didactics included lectures, simulations, hands-on skill-sessions, and journal clubs. Supervised clinical time reinforced concepts and taught an EM approach to patient care. Results: Fourteen physicians from around Haiti successfully completed the program; all improved from their pre-test to post-test. At the end of the program and 9-month post-program evaluations, participants rated the program highly, and most felt they used their new knowledge daily. Participants found clinical supervision and simulation particularly useful. Key components to our program’s success included collaboration with the Ministry of Health and National Medical School, supervised clinical time, and the continual presence of a course director. The program could be improved by a more flexible curriculum and by grouping participants by baseline knowledge levels. Conclusion: Medium-duration certificate programs offer a viable option for addressing immediate human resource gaps in emergency care, and our program offers a model for implementation in resource-limited settings. Similar options should be considered for other emerging specialties in resource-limited settings
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Rethinking the cost of healthcare in low-resource settings: the value of time-driven activity-based costing
Low-income and middle-income countries account for over 80% of the world's infectious disease burden, but <20% of global expenditures on health. In this context, judicious resource allocation can mean the difference between life and death, not just for individual patients, but entire patient populations. Understanding the cost of healthcare delivery is a prerequisite for allocating health resources, such as staff and medicines, in a way that is effective, efficient, just and fair. Nevertheless, health costs are often poorly understood, undermining effectiveness and efficiency of service delivery. We outline shortcomings, and consequences, of common approaches to estimating the cost of healthcare in low-resource settings, as well as advantages of a newly introduced approach in healthcare known as time-driven activity-based costing (TDABC). TDABC is a patient-centred approach to cost analysis, meaning that it begins by studying the flow of individual patients through the health system, and measuring the human, equipment and facility resources used to treat the patients. The benefits of this approach are numerous: fewer assumptions need to be made, heterogeneity in expenditures can be studied, service delivery can be modelled and streamlined and stronger linkages can be established between resource allocation and health outcomes. TDABC has demonstrated significant benefits for improving health service delivery in high-income countries but has yet to be adopted in resource-limited settings. We provide an illustrative case study of its application throughout a network of hospitals in Haiti, as well as a simplified framework for policymakers to apply this approach in low-resource settings around the world