Introduction: priority setting in global health

Bloom, David E.; Cadarette, Daniel; Dayalu, Rashmi; Sullivan, Jessica R.

doi:10.1186/s12962-018-0115-x

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…The cascade of care is intended to provide an evidence base for important and complex discussions about resource allocation, including context-specific questions about the trade-offs between diagnostic and treatment activities and the use of finite resources for diabetes services, as compared to services for other important chronic diseases, including conditions such as HIV that have historically had greater visibility and more external funding. Both cost-effectiveness analyses and multi-criteria decision analysis are superior tools for priority-setting and decisions about resource allocation within health systems [35,36].…”

Section: Discussionmentioning

confidence: 99%

Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys

et al. 2019

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Background The prevalence of diabetes is increasing rapidly in low- and middle-income countries (LMICs), urgently requiring detailed evidence to guide the response of health systems to this epidemic. In an effort to understand at what step in the diabetes care continuum individuals are lost to care, and how this varies between countries and population groups, this study examined health system performance for diabetes among adults in 28 LMICs using a cascade of care approach. Methods and findings We pooled individual participant data from nationally representative surveys done between 2008 and 2016 in 28 LMICs. Diabetes was defined as fasting plasma glucose ≥ 7.0 mmol/l (126 mg/dl), random plasma glucose ≥ 11.1 mmol/l (200 mg/dl), HbA1c ≥ 6.5%, or reporting to be taking medication for diabetes. Stages of the care cascade were as follows: tested, diagnosed, lifestyle advice and/or medication given (“treated”), and controlled (HbA1c < 8.0% or equivalent). We stratified cascades of care by country, geographic region, World Bank income group, and individual-level characteristics (age, sex, educational attainment, household wealth quintile, and body mass index [BMI]). We then used logistic regression models with country-level fixed effects to evaluate predictors of (1) testing, (2) treatment, and (3) control. The final sample included 847,413 adults in 28 LMICs (8 low income, 9 lower-middle income, 11 upper-middle income). Survey sample size ranged from 824 in Guyana to 750,451 in India. The prevalence of diabetes was 8.8% (95% CI: 8.2%–9.5%), and the prevalence of undiagnosed diabetes was 4.8% (95% CI: 4.5%–5.2%). Health system performance for management of diabetes showed large losses to care at the stage of being tested, and low rates of diabetes control. Total unmet need for diabetes care (defined as the sum of those not tested, tested but undiagnosed, diagnosed but untreated, and treated but with diabetes not controlled) was 77.0% (95% CI: 74.9%–78.9%). Performance along the care cascade was significantly better in upper-middle income countries, but across all World Bank income groups, only half of participants with diabetes who were tested achieved diabetes control. Greater age, educational attainment, and BMI were associated with higher odds of being tested, being treated, and achieving control. The limitations of this study included the use of a single glucose measurement to assess diabetes, differences in the approach to wealth measurement across surveys, and variation in the date of the surveys. Conclusions The study uncovered poor management of diabetes along the care cascade, indicating large unmet need for diabetes care across 28 LMICs. Performance across the care cascade varied by World Bank income group and individual-level characteristics, particularly age, educational attainment, and BMI. This policy-relevant analysis can inform country-specific interventions and offers a baseline by which future progress can be measured.

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Section: Discussionmentioning

confidence: 99%

Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys

et al. 2019

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“…Further follow-up of these indicators in combination with cost-effectiveness analyses ( 63 ) and multicriteria decision analysis ( 64 ) is needed in order to plan targeted interventions and policies and allocate resources within health systems. The economic evaluation of health care policy in LMICs is of great importance, considering the resource limitations in these countries.…”

Section: Health Care Models’ Performancementioning

confidence: 99%

The Challenges in the Development of Diabetes Prevention and Care Models in Low-Income Settings

2020

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In low-and middle-income countries (LMICs), the burden of non-communicable diseases such as diabetes is rapidly rising, overpassing the existing burden of communicable diseases. Patients with diabetes living in low-income communities face unique challenges related to lack of awareness, difficulty in accessing health care systems and medications, and consequently failure in achieving optimal diabetes management and preventing complications. Effective diabetes prevention and care models could help reduce the rising burden by standardizing guidelines for prevention and management, improving access to care, engaging community and peers, improving the training of professionals and patients and using the newest technology in the management of the disease. In this article, we review the latest research and evidence on effective models of diabetes prevention and diabetes care delivery in low-income settings. We also provide existing evidence relating to the effectiveness of these models in low-resource contexts, with the aim to highlight characteristics and strengths that make their implementation successful and long-lasting.

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“…One way to structure such evidence and judgments in the short run is to use multicriteria decision analysis (46). This involves defining criteria important to a decision, assigning weights to each criterion, scoring candidate technologies according to each criterion, and prioritizing technologies according to their overall weighted scores across criteria.…”

Section: Roadmapmentioning

confidence: 99%

Toward economic evaluation of the value of vaccines and other health technologies in addressing AMR

Sevilla

Bloom

Cadarette

et al. 2018

Proc. Natl. Acad. Sci. U.S.A.

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110

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We discuss the need to make economic evaluations of vaccines antimicrobial resistance (AMR)-sensitive and ways to do so. Such AMR-sensitive evaluations can play a role in value-for-money comparisons of different vaccines within a national immunization program, or in comparisons of vaccine-centric and non-vaccine-centric technologies within an anti-AMR program. In general terms, incremental cost-effectiveness ratios and rates of return and their associated decision rules are unaltered by consideration of AMR-related value. The decision metrics need to have their various health, cost, and socioeconomic terms disaggregated into resistance-related subcategories, which in turn have to be measured carefully before they are reaggregated. The fundamental scientific challenges lie primarily in quantifying the causal impact of health technologies on resistance-related health outcomes, and secondarily in ascertaining the economic value of those outcomes. We emphasize the importance of evaluating vaccines in the context of other potentially complementary and substitutable nonvaccine technologies. Complementarity implies that optimal spending on each set of interventions is positive, and substitutability implies that the ratio of spending will depend on relative value for money. We exemplify this general point through a qualitative discussion of the complementarities and (especially the) substitutability between pneumococcal conjugate vaccines and antimicrobial stewardship and between research and development (R&D) of a gonorrhea vaccine versus R&D of a gonorrhea antibiotic. We propose a roadmap for future work, which includes quantifying the causal effects of vaccination and other health technologies on short-term and long-term resistance-related outcomes, measuring the health-sector costs and broader socioeconomic consequences of resistance-related mortality and morbidity, and evaluating vaccines in the context of nonvaccine complements and substitutes.

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Introduction: priority setting in global health

Cited by 6 publications

References 28 publications

Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys

Health system performance for people with diabetes in 28 low- and middle-income countries: A cross-sectional study of nationally representative surveys

The Challenges in the Development of Diabetes Prevention and Care Models in Low-Income Settings

Toward economic evaluation of the value of vaccines and other health technologies in addressing AMR

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