Cost Effectiveness of Mobile Health for Antenatal Care and Facility Births in Nigeria

Background: The use of mobile technology in the health sector, often referred to as mHealth, is an innovation that is being used in countries to improve health outcomes and increase and improve both the demand and supply of health care services. This study assesses the actual cost-effectiveness of initiating and implementing the use of the mHealth as a supply side job aid for antenatal care. The study also estimates the cost-effectiveness ratio if mHealth was also used to encourage and track women through facility delivery. Methods: The methodology utilized a retrospective, micro-costing technique to extract costing data from health facilities and administrative offices to estimate the costs of implementing the mHealth antenatal care program and estimate the cost of facility delivery for those that used the antenatal care services in the year 2014. Five different costing tools were developed to assist in the costing analysis. Findings: The results show that the provision of tetanus toxoid vaccination and malaria prophylaxis during pregnancy and improved labor and delivery during facility delivery contributed the most to mortality reductions for women, neonates and stillbirths in mHealth facilities versus non-mHealth facilities. The cost-effectiveness ratio of this program for antenatal care and no demand-side generation for facility delivery is US$13,739 per life saved. The cost-effectiveness ratio adding in an additional demand-side generation for facility births reduces to US$9,806 per life saved. Conclusion: These results show that mHealth programs are inexpensive and save a number of lives for the dollar investment and could save additional lives and funds if women were also encouraged to seek facility delivery

Estimating the global cost of vision impairment and its major causes: protocol for a systematic review

Introduction: Vision impairment (VI) places a burden on individuals, health systems and society in general. In order to support the case for investing in eye health services, an updated cost of illness study that measures the global impact of VI is necessary. To perform such a study, a systematic review of the literature is needed. Here we outline the protocol for a systematic review to describe and summarise the costs associated with VI and its major causes. Methods and analysis: We will systematically search in Medline (Ovid) and the Centre for Reviews and Dissemination database which includes the National Health Service Economics Evaluation Database. No language or geographical restriction will be applied. Additional literature will be identified by reviewing the references in the included studies and by contacting field experts. Grey literature will be considered. The review will include any study published from 1 January 2000 to November 2019 that provides information about costs of illness, burden of disease and/or loss of well-being in participants with VI due to an unspecified cause or due to one of the seven leading causes globally. Two reviewers will independently screen studies and extract relevant data from included studies. Methodological quality of economic studies will be assessed based on the British Medical Journal checklist for economic submissions adapted to costs of illness studies. This protocol has been prepared following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocols and has been published prospectively in Open Science Framework. Ethics and dissemination Formal ethical approval is not required, as primary data will not be collected in this review. The findings of this study will be disseminated through peer-reviewed publications, stakeholder meetings and inclusion in the ongoing Lancet Global Health Commission on Global Eye Health. Registration details https://osf.io/9au3w (DOI 10.17605/OSF.IO/6F8VM)

The economics of vision impairment and its leading causes: A systematic review

Vision impairment (VI) can have wide ranging economic impact on individuals, households, and health systems. The aim of this systematic review was to describe and summarise the costs associated with VI and its major causes. We searched MEDLINE (16 November 2019), National Health Service Economic Evaluation Database, the Database of Abstracts of Reviews of Effects and the Health Technology Assessment database (12 December 2019) for partial or full economic evaluation studies, published between 1 January 2000 and the search dates, reporting cost data for participants with VI due to an unspecified cause or one of the seven leading causes globally: cataract, uncorrected refractive error, diabetic retinopathy, glaucoma, age-related macular degeneration, corneal opacity, trachoma. The search was repeated on 20 January 2022 to identify studies published since our initial search. Included studies were quality appraised using the British Medical Journal Checklist for economic submissions adapted for cost of illness studies. Results were synthesized in a structured narrative. Of the 138 included studies, 38 reported cost estimates for VI due to an unspecified cause and 100 reported costs for one of the leading causes. These 138 studies provided 155 regional cost estimates. Fourteen studies reported global data; 103/155 (66%) regional estimates were from high-income countries. Costs were most commonly reported using a societal (n = 48) or healthcare system perspective (n = 25). Most studies included only a limited number of cost components. Large variations in methodology and reporting across studies meant cost estimates varied considerably. The average quality assessment score was 78% (range 35–100%); the most common weaknesses were the lack of sensitivity analysis and insufficient disaggregation of costs. There was substantial variation across studies in average treatment costs per patient for most conditions, including refractive error correction (range $12–$201 ppp), cataract surgery (range $54–$3654 ppp), glaucoma (range $351–$1354 ppp) and AMD (range $2209–$7524 ppp). Future cost estimates of the economic burden of VI and its major causes will be improved by the development and adoption of a reference case for eye health. This could then be used in regular studies, particularly in countries with data gaps, including low- and middle-income countries in Asia, Eastern Europe, Oceania, Latin America and sub-Saharan Africa

The compounding effect of having HIV and a disability on child mortality among mothers in South Africa.

BackgroundPrevious research on the association between maternal HIV status and child mortality in sub-Saharan Africa was published between 2005-2011. Findings from these studies showed a higher child mortality risk among children born to HIV-positive mothers. While the population of women with disabilities is growing in developing countries, we found no research that examined the association between maternal disability in HIV-positive mothers, and child mortality in sub-Saharan Africa. This study examined the potential compounding effect of maternal disability and HIV status on child mortality in South Africa.MethodsWe analyzed data for women age 15-49 years from South Africa, using the nationally representative 2016 South Africa Demographic and Health Survey. We estimated unadjusted and adjusted risk ratios of child mortality indicators by maternal disability and maternal HIV using modified Poisson regressions.ResultsChildren born to disabled mothers compared to their peers born to non-disabled mothers were at a higher risk for neonatal mortality (RR = 1.80, 95% CI:1.31-2.49), infant mortality (RR = 1.69, 95% CI:1.19-2.41), and under-five mortality (RR = 1.78, 95% CI:1.05-3.01). The joint risk of maternal disability and HIV-positive status on the selected child mortality indicators is compounded such that it is more than the sum of the risks from maternal disability or maternal HIV-positive status alone (RR = 3.97 vs. joint RR = 3.67 for neonatal mortality; RR = 3.57 vs. joint RR = 3.25 for infant mortality; RR = 6.44 vs. joint RR = 3.75 for under-five mortality).ConclusionsThe findings suggest that children born to HIV-positive women with disabilities are at an exceptionally high risk of premature mortality. Established inequalities faced by women with disabilities may account for this increased risk. Given that maternal HIV and disability amplify each other's impact on child mortality, addressing disabled women's HIV-related needs and understanding the pathways and mechanisms contributing to these disparities is crucial

Assessing the impact of the president's emergency plan for AIDS relief on all-cause mortality.

This study estimated the impacts of PEPFAR on all-cause mortality (ACM) rates (deaths per 1,000 population) across PEPFAR recipient countries from 2004-2018. As PEPFAR moves into its 3rd decade, this study supplements the existing literature on PEPFAR 's overall effectiveness in saving lives by focusing impact estimates on the important subgroups of countries that received different intensities of aid, and provides estimates of impact for different phases of this 15-year period study. The study uses a country-level panel data set of 157 low- and middle-income countries (LMICs) from 1990-2018, including 90 PEPFAR recipient countries receiving bilateral aid from the U.S. government, employing difference-in-differences (DID) econometric models with several model specifications, including models with differing baseline covariates, and models with yearly covariates including other donor spending and domestic health spending. Using five different model specifications, a 10-21% decline in ACM rates from 2004 to 2018 is attributed to PEPFAR presence in the group of 90 recipient countries. Declines are somewhat larger (15-25%) in those countries that are subject to PEPFAR's country operational planning (COP) process, and where PEPFAR per capita aid amounts are largest (17-27%). Across the 90 recipient countries we study, the average impact across models is estimated to be a 7.6% reduction in ACM in the first 5-year period (2004-2008), somewhat smaller in the second 5-year period (5.5%) and in the third 5-year period (4.7%). In COP countries the impacts show decreases in ACM of 7.4% in the first period attributed to PEPFAR, 7.7% reductions in the second, and 6.6% reductions in the third. PEPFAR presence is correlated with large declines in the ACM rate, and the overall life-saving results persisted over time. The effects of PEFAR on ACM have been large, suggesting the possibility of spillover life-saving impacts of PEPFAR programming beyond HIV disease alone

Analysis of maternal and child health spillover effects in PEPFAR countries

Objectives This study examined whether the US President’s Emergency Plan for AIDS Relief (PEPFAR) funding had effects beyond HIV, specifically on several measures of maternal and child health in low-income and middle-income countries (LMICs). The results of previous research on the question of PEPFAR health spillovers have been inconsistent. This study, using a large, multicountry panel data set of 157 LMICs including 90 recipient countries, adds to the literature.Design Seven indicators including child and maternal mortality, several child vaccination rates and anaemia among childbearing-age women are important population health indicators. Panel data and difference-in-differences estimators (DID) were used to estimate the impact of the PEPFAR programme from inception in 2004 to 2018 using a comparison group of 67 LMICs. Several different models of baseline (2004) covariates were used to help balance the comparison and treatment groups. Staggered DID was used to estimate impacts since all countries did not start receiving aid at PEPFAR’s inception.Setting All 157 LMICs from 1990 to 2018.Participants 90 LMICs receiving PEPFAR aid and cohorts of those countries, including those required to submit annual country operational plans (COP), other recipient countries (non-COP), and three groupings of countries based on cumulative amount of per capita aid received (high, medium, low).Interventions PEPFAR aid to combat the HIV epidemic.Primary outcome measures Maternal mortality and child mortality rates, vaccination rates to protect children for diphtheria, whooping cough and tetanus, measles, HepB3, and tetanus, and prevalence of anaemia in women of childbearing age.Results Across PEPFAR recipient countries, large, favourable PEPFAR health effects were found for rates of childhood immunisation, child mortality and maternal mortality. These beneficial health effects were large and significant in all segments of PEPFAR recipient countries studied. We also found significant and favourable programme effects on the prevalence of anaemia in women of childbearing age in PEPFAR recipient countries receiving the most intensive financial support from the PEPFAR programme. Other recipient countries did not demonstrate significant effects on anaemia.Conclusions This study demonstrated that important health indicators, beyond HIV, have been consistently and favourably influenced by PEPFAR presence. Child and maternal mortality have been substantially reduced, and childhood immunisation rates increased. We also found no evidence of ‘crowding out’ or negative spillovers in these resource-poor countries. These findings add to the body of evidence that PEPFAR has had favourable health effects beyond HIV. The implications of these findings are that foreign aid for health in one area may have favourable health effects in other areas in recipient countries. More research is needed on the influence of the mechanisms at work that create these spillover health effects of PEPFAR

Estimates of PEPFAR impact on all-cause mortality (deaths per 1,000), cumulative 5-year estimates.

Estimates of PEPFAR impact on all-cause mortality (deaths per 1,000), cumulative 5-year estimates.</p

Regression results–Tables A—O.

Table A in S1 Table. Summary of PEPFAR impact by country cohort from estimation of five logged models. Table B in S1 Table. Summary of adjusted R-squares of five logged and unlogged models (level) on PEPFAR impact by country cohort. Table C in S1 Table. Summary of PEPFAR impact over three periods from estimation of five logged models. Table D in S1 Table. Full model results for "All PEPFAR" group vs control: unlogged models. Table E in S1 Table. Full model results for "All PEPFAR" group vs control: logged models. Table F in S1 Table. Full model results for "COP-PEPFAR" group vs control: unlogged models. Table G in S1 Table. Full model results for "COP-PEPFAR" group vs control: logged models. Table H in S1 Table. Full model results for "Other PEPFAR" group vs control: unlogged models. Table I in S1 Table. Full model results for "Other PEPFAR" group vs control: logged models. Table J in S1 Table. Full model results for "High intensity PEPFAR" group vs control: unlogged models. Table K in S1 Table. Full model results for "High intensity PEPFAR" group vs control: logged models. Table L in S1 Table. Full model results for "Medium intensity PEPFAR" group vs control: unlogged models. Table M in S1 Table. Full model results for "Medium intensity PEPFAR" group vs control: logged models. Table N in S1 Table. Full model results for "Low intensity PEPFAR" group vs control: unlogged models. Table O in S1 Table. Full model results for “Low intensity PEPFAR” group vs control: logged models. (DOCX)</p

Missingness.

This study estimated the impacts of PEPFAR on all-cause mortality (ACM) rates (deaths per 1,000 population) across PEPFAR recipient countries from 2004–2018. As PEPFAR moves into its 3rd decade, this study supplements the existing literature on PEPFAR ‘s overall effectiveness in saving lives by focusing impact estimates on the important subgroups of countries that received different intensities of aid, and provides estimates of impact for different phases of this 15-year period study. The study uses a country-level panel data set of 157 low- and middle-income countries (LMICs) from 1990–2018, including 90 PEPFAR recipient countries receiving bilateral aid from the U.S. government, employing difference-in-differences (DID) econometric models with several model specifications, including models with differing baseline covariates, and models with yearly covariates including other donor spending and domestic health spending. Using five different model specifications, a 10–21% decline in ACM rates from 2004 to 2018 is attributed to PEPFAR presence in the group of 90 recipient countries. Declines are somewhat larger (15–25%) in those countries that are subject to PEPFAR’s country operational planning (COP) process, and where PEPFAR per capita aid amounts are largest (17–27%). Across the 90 recipient countries we study, the average impact across models is estimated to be a 7.6% reduction in ACM in the first 5-year period (2004–2008), somewhat smaller in the second 5-year period (5.5%) and in the third 5-year period (4.7%). In COP countries the impacts show decreases in ACM of 7.4% in the first period attributed to PEPFAR, 7.7% reductions in the second, and 6.6% reductions in the third. PEPFAR presence is correlated with large declines in the ACM rate, and the overall life-saving results persisted over time. The effects of PEFAR on ACM have been large, suggesting the possibility of spillover life-saving impacts of PEPFAR programming beyond HIV disease alone.</div

Country list by groups.

This study estimated the impacts of PEPFAR on all-cause mortality (ACM) rates (deaths per 1,000 population) across PEPFAR recipient countries from 2004–2018. As PEPFAR moves into its 3rd decade, this study supplements the existing literature on PEPFAR ‘s overall effectiveness in saving lives by focusing impact estimates on the important subgroups of countries that received different intensities of aid, and provides estimates of impact for different phases of this 15-year period study. The study uses a country-level panel data set of 157 low- and middle-income countries (LMICs) from 1990–2018, including 90 PEPFAR recipient countries receiving bilateral aid from the U.S. government, employing difference-in-differences (DID) econometric models with several model specifications, including models with differing baseline covariates, and models with yearly covariates including other donor spending and domestic health spending. Using five different model specifications, a 10–21% decline in ACM rates from 2004 to 2018 is attributed to PEPFAR presence in the group of 90 recipient countries. Declines are somewhat larger (15–25%) in those countries that are subject to PEPFAR’s country operational planning (COP) process, and where PEPFAR per capita aid amounts are largest (17–27%). Across the 90 recipient countries we study, the average impact across models is estimated to be a 7.6% reduction in ACM in the first 5-year period (2004–2008), somewhat smaller in the second 5-year period (5.5%) and in the third 5-year period (4.7%). In COP countries the impacts show decreases in ACM of 7.4% in the first period attributed to PEPFAR, 7.7% reductions in the second, and 6.6% reductions in the third. PEPFAR presence is correlated with large declines in the ACM rate, and the overall life-saving results persisted over time. The effects of PEFAR on ACM have been large, suggesting the possibility of spillover life-saving impacts of PEPFAR programming beyond HIV disease alone.</div