39 research outputs found

    Investing in Health to Improve the Wellbeing of the Disadvantaged: Reversing the Augment of the Marmot Reports

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    The Marmot reports have argued that health inequalities are the result of social inequalities. They advocate reducing health inequalities by undertaking fundamental changes that make society fairer. We argue that the focus should be on improving the health and wellbeing of the disadvantaged, even if the policies that do this also raise the health of the better off, and worsen inequality. We also argue that the causality runs from health to social status, and that health interventions are needed to improve socioeconomic outcomes. While we disagree on goals and mechanisms we are in surprisingly close agreement with Marmot Reports on policies. In particular, we agree with the focus on in early childhood investments in health and physical and cognitive development that have long term socioeconomic payoffs. We also endorse making society fairer, though mainly as a goal in itself rather than an instrument to reduce health inequality.health inequality, early childhood investments, Marmot Reports

    Activity-based costing for HIV, primary care and nutrition services in low- and middle-income countries: A systematic literature review and synthesis

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    Background This study is a systematic literature review of HIV, nutrition, and primary care activity-based costing (ABC) studies conducted in low- and middle-income countries. ABC studies are critical for understanding the quantities and unit costs of the activities and resources for specific cost functions. The results of ABC studies enable governments, funders, and policymakers to utilize costing results to make efficient, cost-effective decisions on how to allocate scarce resources. Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology for systematic literature reviews. Key search terms included: (1) activity-based costing and time-driven activity-based costing, (2) cost of services, (3) HIV interventions OR (4) primary health care. Terms were searched within article titles and abstracts in PubMed, EconLit, and Scopus. Results 1,884 abstracts were screened and reduced to 57 articles using exclusion criteria. After a full text review, 16 articles were included in the final data synthesis. Findings were used to classify costs into relevant and common inputs for activity-based costing. All costs were converted to unit cost (cost per patient) and inflated to January 2020 USD. The largest unit cost across nutrition services was training (US194.16perpatient,34.6194.16 per patient, 34.6% of total unit cost). The largest unit cost for HIV was antiretroviral therapy (ART) (US125.41, 71.0%). The largest unit cost for primary care services was human resources (US84.78,62.584.78, 62.5%). Overall costs per patient for HIV services were US176.71, US135.67forprimarycareservices,andUS135.67 for primary care services, and US561.68 for nutrition services. The costing results presented suggest that spending on HIV exceeds the actual cost of HIV services. Conclusions This is the first systematic literature review to summarize the costs of HIV, primary care, and nutrition services across activity-based costing studies. While there was a wide variation in the study designs and economic methods, many of the input cost categories were similar. With the increasing number of costing studies in countries around the world, understanding trends in costs by function and service can lead to greater efficiency in the implementation of HIV, primary care, and nutrition programs

    The Challenge of Additionality: The Impact of Central Grants for Primary Healthcare on State-Level Spending on Primary Healthcare in India

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    Background: In planning for universal health coverage, many countries have been examining their fiscal decentralization policies with the goal of increasing efficiency and equity via “additionalities.” The concept of “additionality,” when the government of a lower administrative level increases the funding allocated to a particular issue when extra funds are present, is often used in these contexts. Although the definition of “additionality” can be used more broadly, for the purposes of this paper we focus narrowly on the additional allocation of primary healthcare expenditures. This paper explores this idea by examining the impact of central level primary healthcare expenditure, on individual state level contributions to primary healthcare expenditure within 16 Indian states between 2005 and 2013. Methods: In examining 5 main variables, we compared differences between government expenditures, contributions, and revenues for Empowered Action Group (EAG) states, and non-EAG states. EAG states are normally larger states that have weaker public health infrastructure and hence qualify for additional funding. Finally, using a model that captured the quantity of central level primary healthcare expenditure distributions to these states, we measured its impact on each state’s own contributions to primary healthcare spending.Results: Our results show that, at the state level, growth in per capita central level primary healthcare expenditure has increased by 110% from 2005-2013, while state’s own contributions to primary healthcare expenditure per capita increased by 32%. Further analyses show that a 1% change disbursement from the central level leads to a -0.132%, although not significant, change by states in their own expenditure. The effect for wealthier states is -0.151% and significant and for poorer states the effect is smaller at -0.096% and not significant. Conclusion: This analysis suggests that increases in central level primary healthcare expenditure to states have an inverse relationship with primary healthcare expenditures by the state level. Furthermore, this effect is more pronounced in wealthier Indian states. This finding has policy implications on India’s decision to increase block grants to states in place of targeted program expenditures

    A Model for Rigorously Applying the Exploration, Preparation, Implementation, Sustainment (EPIS) Framework in the Design and Measurement of a Large Scale Collaborative Multi-Site Study

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    Background This paper describes the means by which a United States National Institute on Drug Abuse (NIDA)-funded cooperative, Juvenile Justice-Translational Research on Interventions for Adolescents in the Legal System (JJ-TRIALS), utilized an established implementation science framework in conducting a multi-site, multi-research center implementation intervention initiative. The initiative aimed to bolster the ability of juvenile justice agencies to address unmet client needs related to substance use while enhancing inter-organizational relationships between juvenile justice and local behavioral health partners. Methods The EPIS (Exploration, Preparation, Implementation, Sustainment) framework was selected and utilized as the guiding model from inception through project completion; including the mapping of implementation strategies to EPIS stages, articulation of research questions, and selection, content, and timing of measurement protocols. Among other key developments, the project led to a reconceptualization of its governing implementation science framework into cyclical form as the EPIS Wheel. The EPIS Wheel is more consistent with rapid-cycle testing principles and permits researchers to track both progressive and recursive movement through EPIS. Moreover, because this randomized controlled trial was predicated on a bundled strategy method, JJ-TRIALS was designed to rigorously test progress through the EPIS stages as promoted by facilitation of data-driven decision making principles. The project extended EPIS by (1) elucidating the role and nature of recursive activity in promoting change (yielding the circular EPIS Wheel), (2) by expanding the applicability of the EPIS framework beyond a single evidence-based practice (EBP) to address varying process improvement efforts (representing varying EBPs), and (3) by disentangling outcome measures of progression through EPIS stages from the a priori established study timeline. Discussion The utilization of EPIS in JJ-TRIALS provides a model for practical and applied use of implementation frameworks in real-world settings that span outer service system and inner organizational contexts in improving care for vulnerable populations. Trial registration NCT02672150. Retrospectively registered on 22 January 2016

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

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    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 US13,739perlifesaved.ThecosteffectivenessratioaddinginanadditionaldemandsidegenerationforfacilitybirthsreducestoUS13,739 per life saved. The cost-effectiveness ratio adding in an additional demand-side generation for facility births reduces to US9,806 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

    Investing in health to improve the wellbeing of the disadvantaged: Reversing the argument of Fair Society, Healthy Lives (The Marmot Review)

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    Health gradient Social inequality Social determinants of health Fair Society, Healthy Lives (The Marmot Review)

    Guatemala: The economic burden of illness and health system implications

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    Objectives To assess the economic burden of ill health in Guatemala, the characteristics of Guatemala's health system that potentially explain this burden, and to identify policies to help ameliorate it.Methods Data from the 2000 and 2006 Living Standard Measurement Surveys are used to assess levels of financial burden from ill health, along with information on health system characteristics of Guatemala and recent reform experiences of several middle- and low-income countries.Results Despite some gains over the period from 2000 to 2006, there continues to be both a high level and inequitable distribution of financial burden associated with ill health in Guatemala. Low levels of insurance coverage, a heavy concentration of the uninsured among the less well off and rural populations, as well as their low levels of access to public services are important drivers of out of pocket spending on health. Households with older members also appear to be at increased risk for out of pocket payments.Conclusions High levels of catastrophic health spending and poverty co-exist with significant economic inequality and poverty in Guatemala. With health system features and a large informal sector similar to many other developing countries, recent international experience can provide useful lessons to help Guatemala devise innovative financing and payment mechanisms to address these concerns.Health expenditures Poverty Health systems Guatemala
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