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2.
BMC Health Serv Res ; 24(1): 127, 2024 Jan 23.
Artigo em Inglês | MEDLINE | ID: mdl-38263128

RESUMO

BACKGROUND: Globally, non-communicable diseases (NCDs) are the leading cause of mortality and morbidity placing a huge burden on individuals, families and health systems, especially in low- and middle-income countries (LMICs). This rising disease burden calls for policy responses that engage the entire health care system. This study aims to synthesize evidence on how people with NCDs choose their healthcare providers in LMICs, and the outcomes of these choices, with a focus on private sector delivery. METHODS: A systematic search for literature following PRISMA guidelines was conducted. We extracted and synthesised data on the determinants and outcomes of private health care utilisation for NCDs in LMICs. A quality and risk of bias assessment was performed using the Mixed Methods Appraisal Tool (MMAT). RESULTS: We identified 115 studies for inclusion. Findings on determinants and outcomes were heterogenous, often based on a particular country context, disease, and provider. The most reported determinants of seeking private NCD care were patients having a higher socioeconomic status; greater availability of services, staff and medicines; convenience including proximity and opening hours; shorter waiting times and perceived quality. Transitioning between public and private facilities is common. Costs to patients were usually far higher in the private sector for both inpatient and outpatient settings. The quality of NCD care seems mixed depending on the disease, facility size and location, as well as the aspect of quality assessed. CONCLUSION: Given the limited, mixed and context specific evidence currently available, adapting health service delivery models to respond to NCDs remains a challenge in LMICs. More robust research on health seeking behaviours and outcomes, especially through large multi-country surveys, is needed to inform the effective design of mixed health care systems that effectively engage both public and private providers. TRIAL REGISTRATION: PROSPERO registration number CRD42022340059 .


Assuntos
Doenças não Transmissíveis , Humanos , Países em Desenvolvimento , Setor Privado , Comportamentos Relacionados com a Saúde , Aceitação pelo Paciente de Cuidados de Saúde
3.
BMJ Open ; 13(8): e066213, 2023 08 24.
Artigo em Inglês | MEDLINE | ID: mdl-37620272

RESUMO

INTRODUCTION: The burden of non-communicable diseases (NCDs) has increased substantially in low- and middle-income countries (LMICs), and adapting health service delivery models to address this remains a challenge. Many patients with NCD seek private care at different points in their encounters with the health system, but the determinants and outcomes of these choices are insufficiently understood. The proposed systematic review will help inform the governance of mixed health systems towards achieving the goal of universal health coverage. This protocol details our intended methodological and analytical approaches, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). METHODS AND ANALYSIS: Following the PRISMA approach, this systematic review will develop a descriptive synthesis of the determinants and outcomes of private healthcare utilisation for NCDs in LMICs. The databases Embase, Medline, Web of Science Core Collection, EconLit, Global Index Medicus and Google Scholar will be searched for relevant studies published in English between period 1 January 2010 and 30 June 2022 with additional searching of reference lists. The study selection process will involve a title-abstract and full-text review, guided by clearly defined inclusion and exclusion criteria. A quality and risk of bias assessment will be done for each study using the Mixed Methods Appraisal Tool. ETHICS AND DISSEMINATION: Ethical approval is not required because this review is based on data collected from publicly available materials. The results will be published in a peer-reviewed journal and presented at related scientific events. PROSPERO REGISTRATION NUMBER: CRD42022340059.


Assuntos
Doenças não Transmissíveis , Humanos , Doenças não Transmissíveis/terapia , Países em Desenvolvimento , Setor Privado , Comportamentos Relacionados com a Saúde , Aceitação pelo Paciente de Cuidados de Saúde , Revisões Sistemáticas como Assunto
4.
Health Econ ; 32(11): 2427-2445, 2023 11.
Artigo em Inglês | MEDLINE | ID: mdl-37424194

RESUMO

Long waiting times have been a persistent policy issue in the United Kingdom that the COVID-19 pandemic has exacerbated. This study analyses the causal effect of hospital spending on waiting times in England using a first-differences panel approach and an instrumental variable strategy to deal with residual concerns for endogeneity. We use data from 2014 to 2019 on waiting times from general practitioner referral to treatment (RTT) measured at the level of local purchasers (known as Clinical Commissioning Groups). We find that increases in hospital spending by local purchasers of 1% reduce median RTT waiting time for patients whose pathway ends with a hospital admission (admitted pathway) by 0.6 days but the effect is not statistically significant at 5% level (only at the 10% level). We also find that higher hospital spending does not affect the RTT waiting time for patients whose pathway ends with a specialist consultation (non-admitted pathway). Nor does higher spending have a statistically significant effect on the volume of elective activity for either pathway. Our findings suggest that higher spending is no guarantee of higher volumes and lower waiting times, and that additional mechanisms need to be put in place to ensure that increased spending benefits elective patients.


Assuntos
COVID-19 , Listas de Espera , Humanos , Pandemias , Hospitalização , Hospitais
5.
BMC Public Health ; 23(1): 689, 2023 04 12.
Artigo em Inglês | MEDLINE | ID: mdl-37046247

RESUMO

BACKGROUND: Primary prevention of cardiovascular diseases (CVD) increasingly relies on monitoring global CVD risk scores. Lack of evidence on socioeconomic inequality in these scores and the contributions that specific risk factors make to this inequality impedes effective targeting of CVD prevention. We aimed to address this evidence gap by measuring and decomposing socioeconomic inequality in CVD risk in the Philippines. METHODS: We used data on 8462 individuals aged 40-74 years from the Philippines National Nutrition Survey and the laboratory-based Globorisk equation to predict 10-year risk of a CVD event from sex, age, systolic blood pressure, total cholesterol, high blood glucose, and smoking. We used a household wealth index to proxy socioeconomic status and measured socioeconomic inequality with a concentration index that we decomposed into contributions of the risk factors used to predict CVD risk. We measured socioeconomic inequalities in these risk factors and decomposed them into contributions of more distal risk factors: body mass index, fat share of energy intake, low physical activity, and drinking alcohol. We stratified by sex. RESULTS: Wealthier individuals, particularly males, had greater exposure to all risk factors, with the exception of smoking, and had higher CVD risks. Total cholesterol and high blood glucose accounted for 58% and 34%, respectively, of the socioeconomic inequality in CVD risk among males. For females, the respective estimates were 63% and 69%. Systolic blood pressure accounted for 26% of the higher CVD risk of wealthier males but did not contribute to inequality among females. If smoking prevalence had not been higher among poorer individuals, then the inequality in CVD risk would have been 35% higher for males and 75% higher for females. Among distal risk factors, body mass index and fat intake contributed most to inequalities in total cholesterol, high blood sugar, and, for males, systolic blood pressure. CONCLUSIONS: Wealthier Filipinos have higher predicted CVD risks and greater exposure to all risk factors, except smoking. There is need for a nuanced approach to CVD prevention that targets anti-smoking programmes on the poorer population while targeting diet and exercise interventions on the wealthier.


Assuntos
Doenças Cardiovasculares , Masculino , Feminino , Humanos , Fatores de Risco , Doenças Cardiovasculares/epidemiologia , Estudos Transversais , Glicemia , Filipinas/epidemiologia , Fatores Socioeconômicos , Fatores de Risco de Doenças Cardíacas , Colesterol
6.
Lancet Glob Health ; 7(11): e1500-e1510, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31564629

RESUMO

BACKGROUND: Primary health care (PHC) is a driving force for advancing towards universal health coverage (UHC). PHC-oriented health systems bring enormous benefits but require substantial financial investments. Here, we aim to present measures for PHC investments and project the associated resource needs. METHODS: This modelling study analysed data from 67 low-income and middle-income countries (LMICs). Recognising the variation in PHC services among countries, we propose three measures for PHC, with different scope for included interventions and system strengthening. Measure 1 is centred on public health interventions and outpatient care; measure 2 adds general inpatient care; and measure 3 further adds cross-sectoral activities. Cost components included in each measure were based on the Declaration of Astana, informed by work delineating PHC within health accounts, and finalised through an expert and country validation meeting. We extracted the subset of PHC costs for each measure from WHO's Sustainable Development Goal (SDG) price tag for the 67 LMICs, and projected the associated health impact. Estimates of financial resource need, health workforce, and outpatient visits are presented as PHC investment guide posts for LMICs. FINDINGS: An estimated additional US$200-328 billion per year is required for the various measures of PHC from 2020 to 2030. For measure 1, an additional $32 is needed per capita across the countries. Needs are greatest in low-income countries where PHC spending per capita needs to increase from $25 to $65. Overall health workforces would need to increase from 5·6 workers per 1000 population to 6·7 per 1000 population, delivering an average of 5·9 outpatient visits per capita per year. Increasing coverage of PHC interventions would avert an estimated 60·1 million deaths and increase average life expectancy by 3·7 years. By 2030, these incremental PHC costs would be about 3·3% of projected gross domestic product (GDP; median 1·7%, range 0·1-20·2). In a business-as-usual financing scenario, 25 of 67 countries will have funding gaps in 2030. If funding for PHC was increased by 1-2% of GDP across all countries, as few as 16 countries would see a funding gap by 2030. INTERPRETATION: The resources required to strengthen PHC vary across countries, depending on demographic trends, disease burden, and health system capacity. The proposed PHC investment guide posts advance discussions around the budgetary implications of strengthening PHC, including relevant system investment needs and achievable health outcomes. Preliminary findings suggest that low-income and lower-middle-income countries would need to at least double current spending on PHC to strengthen their systems and universally provide essential PHC services. Investing in PHC will bring substantial health benefits and build human capital. At country level, PHC interventions need to be explicitly identified, and plans should be made for how to most appropriately reorient the health system towards PHC as a key lever towards achieving UHC and the health-related SDGs. FUNDING: The Bill & Melinda Gates Foundation.


Assuntos
Países em Desenvolvimento/estatística & dados numéricos , Custos de Cuidados de Saúde/tendências , Gastos em Saúde/tendências , Cobertura Universal do Seguro de Saúde/tendências , Saúde Global/tendências , Produto Interno Bruto/tendências , Financiamento da Assistência à Saúde , Humanos , Atenção Primária à Saúde/tendências , Cobertura Universal do Seguro de Saúde/economia
7.
Cost Eff Resour Alloc ; 16: 10, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29541000

RESUMO

BACKGROUND: Human resources are consistently cited as a leading contributor to health care costs; however the availability of internationally comparable data on health worker earnings for all countries is a challenge for estimating the costs of health care services. This paper describes an econometric model using cross sectional earnings data from the International Labour Organization (ILO) that the World Health Organizations (WHO)-Choosing Interventions that are Cost-effective programme (CHOICE) has used to prepare estimates of health worker earnings (in 2010 USD) for all WHO member states. METHODS: The ILO data contained 324 observations of earnings data across 4 skill levels for 193 countries. Using this data, along with the assumption that data were missing not at random, we used a Heckman two stage selection model to estimate earning data for each of the 4 skill levels for all WHO member states. RESULTS: It was possible to develop a prediction model for health worker earnings for all countries for which GDP data was available. Health worker earnings vary both within country due to skill level, as well as across countries. As a multiple of GDP per capita, earnings show a negative correlation with GDP-that is lower income countries pay their health workers relatively more than higher income countries. CONCLUSIONS: Limited data on health worker earnings is a limiting factor in estimating the costs of global health programmes. It is hoped that these estimates will support robust health care intervention costings and projections of resources needs over the Sustainable Development Goal period.

9.
Cost Eff Resour Alloc ; 15: 21, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-29089861

RESUMO

BACKGROUND: Estimating health care costs, either in the context of understanding resource utilization in the implementation of a health plan, or in the context of economic evaluation, has become a common activity of health planners, health technology assessment agencies and academic groups. However, data sources for costs outside of direct service delivery are often scarce. WHO-CHOICE produces global price databases and guidance on quantity assumptions to support country level costing exercises. This paper presents updates to the WHO-CHOICE methodology and price databases for programme costs. METHODS: We collated publicly available databases for 14 non-traded cost variables, as well as a set of traded items used within health systems (traded goods are those which can be purchased from anywhere in the world, whereas non-traded goods are those which must be produced locally, such as human resources). Within each of the variables, missing data was present for some proportion of the WHO member states. For each variables statistical or econometric models were used to model prices for each of the 194 WHO member states in 2010 International Dollars. Literature reviews were used to update quantity assumptions associated with each variable to contribute to the support costs of disease control programmes. RESULTS: A full database of prices for disease control programme support costs is available for country-specific costing purposes. Human resources are the largest driver of disease control programme support costs, followed by supervision costs. CONCLUSIONS: Despite major advances in the availability of data since the previous version of this work, there are still some limitations in data availability to respond to the needs of those wishing to develop cost and cost-effectiveness estimates. Greater attention to programme support costs in cost data collection activities would contribute to an understanding of how these costs contribute to quality of health service delivery and should be encouraged.

10.
Lancet Glob Health ; 5(9): e875-e887, 2017 09.
Artigo em Inglês | MEDLINE | ID: mdl-28728918

RESUMO

BACKGROUND: The ambitious development agenda of the Sustainable Development Goals (SDGs) requires substantial investments across several sectors, including for SDG 3 (healthy lives and wellbeing). No estimates of the additional resources needed to strengthen comprehensive health service delivery towards the attainment of SDG 3 and universal health coverage in low-income and middle-income countries have been published. METHODS: We developed a framework for health systems strengthening, within which population-level and individual-level health service coverage is gradually scaled up over time. We developed projections for 67 low-income and middle-income countries from 2016 to 2030, representing 95% of the total population in low-income and middle-income countries. We considered four service delivery platforms, and modelled two scenarios with differing levels of ambition: a progress scenario, in which countries' advancement towards global targets is constrained by their health system's assumed absorptive capacity, and an ambitious scenario, in which most countries attain the global targets. We estimated the associated costs and health effects, including reduced prevalence of illness, lives saved, and increases in life expectancy. We projected available funding by country and year, taking into account economic growth and anticipated allocation towards the health sector, to allow for an analysis of affordability and financial sustainability. FINDINGS: We estimate that an additional $274 billion spending on health is needed per year by 2030 to make progress towards the SDG 3 targets (progress scenario), whereas US$371 billion would be needed to reach health system targets in the ambitious scenario-the equivalent of an additional $41 (range 15-102) or $58 (22-167) per person, respectively, by the final years of scale-up. In the ambitious scenario, total health-care spending would increase to a population-weighted mean of $271 per person (range 74-984) across country contexts, and the share of gross domestic product spent on health would increase to a mean of 7·5% (2·1-20·5). Around 75% of costs are for health systems, with health workforce and infrastructure (including medical equipment) as the main cost drivers. Despite projected increases in health spending, a financing gap of $20-54 billion per year is projected. Should funds be made available and used as planned, the ambitious scenario would save 97 million lives and significantly increase life expectancy by 3·1-8·4 years, depending on the country profile. INTERPRETATION: All countries will need to strengthen investments in health systems to expand service provision in order to reach SDG 3 health targets, but even the poorest can reach some level of universality. In view of anticipated resource constraints, each country will need to prioritise equitably, plan strategically, and cost realistically its own path towards SDG 3 and universal health coverage. FUNDING: WHO.


Assuntos
Atenção à Saúde/economia , Atenção à Saúde/organização & administração , Países em Desenvolvimento , Conservação dos Recursos Naturais , Custos e Análise de Custo , Objetivos , Recursos em Saúde , Necessidades e Demandas de Serviços de Saúde , Humanos , Modelos Teóricos , Cobertura Universal do Seguro de Saúde
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