2015-19 年期间马拉维公共部门医疗保健系统资源使用估算及加强医疗保健服务的效果:一项模拟研究(Thanzi La Onse)。

IF 19.9 1区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Timothy B Hallett, Tara D Mangal, Asif U Tamuri, Nimalan Arinaminpathy, Valentina Cambiano, Martin Chalkley, Joseph H Collins, Jonathan Cooper, Matthew S Gillman, Mosè Giordano, Matthew M Graham, William Graham, Iwona Hawryluk, Eva Janoušková, Britta L Jewell, Ines Li Lin, Robert Manning Smith, Gerald Manthalu, Emmanuel Mnjowe, Sakshi Mohan, Margherita Molaro, Wingston Ng'ambi, Dominic Nkhoma, Stefan Piatek, Paul Revill, Alison Rodger, Dimitra Salmanidou, Bingling She, Mikaela Smit, Pakwanja D Twea, Tim Colbourn, Joseph Mfutso-Bengo, Andrew N Phillips
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引用次数: 0

摘要

背景:在所有医疗保健系统中,都需要就可用资源的分配做出决定。这些决策需要证据,尤其是在低收入国家。我们旨在估算马拉维在 2015-19 年间如何使用公共部门提供的医疗资源,并估算加强医疗服务的效果:在这项建模研究中,我们使用了基于个人的模拟模型 Thanzi La Onse。该模型的范围是 2015-19 年间马拉维公共部门提供的医疗保健服务。医疗保健服务是在医疗保健系统互动(HSI)事件中提供的,我们将这些事件描述为发生在特定设施层面并需要特定预约次数的事件。根据全球疾病负担(GBD)的估算,2015-19 年间马拉维约有 81% 的死亡和 72% 的残疾调整寿命年数(DALYs)是由这些死亡和残疾原因造成的。疾病模型可以相互影响,也可以与每个人的基本属性相互影响。Thanzi La Onse 模型中的每个人都有特定的属性(如性别、居住地区、财富百分位数、吸烟状况和体重指数等),我们利用人口和健康调查数据测量了这些属性的分布和随时间的变化情况。我们还估算了不同类型的医疗保健系统改进的效果:我们估计,在 2015-19 年期间,马拉维公共部门的医疗保健系统避免了 4,120 万个残疾调整寿命年(95% UI 38-6-43-8),约占本应避免的 8,430 万个残疾调整寿命年(81-5-86-9)的一半。由于提供的服务避免了急性下呼吸道感染、艾滋病毒或艾滋病、疟疾或新生儿疾病造成的残疾调整寿命年数,0-4 岁儿童避免的残疾调整寿命年数偏高。成人中避免的残疾调整寿命年数主要归因于艾滋病毒或艾滋病和结核病。如果每次预约的时间都符合预期,且医护人员的工作时间不超过合同规定的时间,那么在 2015-19 年期间,马拉维的医疗保健系统仅能避免 1900 万残疾调整寿命年(95% UI 为 17-1-22-4),这表明约 2100-300 万残疾调整寿命年(20-0-23-6)的总效应是通过医护人员的过度工作产生的。如果生病的人能够立即得到治疗,所有转诊都能顺利完成,医护人员的诊断准确率尽可能高,而且耗材(即药品)总是能买到,那么可以避免的残疾调整寿命年数将增加 28-2%(95% UI 25-7-30-9)(即 1220 万残疾调整寿命年数 [95% UI 10-9-13-8]):马拉维的医疗保健系统以稀缺的资源提供了巨大的健康收益。加强干预措施有可能增加这些收益,因此应优先进行调查和投资。基于个体的医疗保健服务提供模拟模型对于医疗保健系统的规划和加强很有价值:资金来源:惠康基金会、英国研究与创新组织、英国医学研究委员会和社区贾米尔。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimates of resource use in the public-sector health-care system and the effect of strengthening health-care services in Malawi during 2015-19: a modelling study (Thanzi La Onse).

Background: In all health-care systems, decisions need to be made regarding allocation of available resources. Evidence is needed for these decisions, especially in low-income countries. We aimed to estimate how health-care resources provided by the public sector were used in Malawi during 2015-19 and to estimate the effects of strengthening health-care services.

Methods: For this modelling study, we used the Thanzi La Onse model, an individual-based simulation model. The scope of the model was health care provided by the public sector in Malawi during 2015-19. Health-care services were delivered during health-care system interaction (HSI) events, which we characterised as occurring at a particular facility level and requiring a particular number of appointments. We developed mechanistic models for the causes of death and disability that were estimated to account for approximately 81% of deaths and approximately 72% of disability-adjusted life-years (DALYs) in Malawi during 2015-19, according to the Global Burden of Disease (GBD) estimates; we computed DALYs incurred in the population as the sum of years of life lost and years lived with disability. The disease models could interact with one another and with the underlying properties of each person. Each person in the Thanzi La Onse model had specific properties (eg, sex, district of residence, wealth percentile, smoking status, and BMI, among others), for which we measured distribution and evolution over time using demographic and health survey data. We also estimated the effect of different types of health-care system improvement.

Findings: We estimated that the public-sector health-care system in Malawi averted 41·2 million DALYs (95% UI 38·6-43·8) during 2015-19, approximately half of the 84·3 million DALYs (81·5-86·9) that the population would otherwise have incurred. DALYs averted were heavily skewed to children aged 0-4 years due to services averting DALYs that would be caused by acute lower respiratory tract infection, HIV or AIDS, malaria, or neonatal disorders. DALYs averted among adults were mostly attributed to HIV or AIDS and tuberculosis. Under a scenario whereby each appointment took the time expected and health-care workers did not work for longer than contracted, the health-care system in Malawi during 2015-19 would have averted only 19·1 million DALYs (95% UI 17·1-22·4), suggesting that approximately 21·3 million DALYS (20·0-23·6) of total effect were derived through overwork of health-care workers. If people becoming ill immediately accessed care, all referrals were successfully completed, diagnostic accuracy of health-care workers was as good as possible, and consumables (ie, medicines) were always available, 28·2% (95% UI 25·7-30·9) more DALYS (ie, 12·2 million DALYs [95% UI 10·9-13·8]) could be averted.

Interpretation: The health-care system in Malawi provides substantial health gains with scarce resources. Strengthening interventions could potentially increase these gains, so should be a priority for investigation and investment. An individual-based simulation model of health-care service delivery is valuable for health-care system planning and strengthening.

Funding: The Wellcome Trust, UK Research and Innovation, the UK Medical Research Council, and Community Jameel.

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来源期刊
Lancet Global Health
Lancet Global Health PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
44.10
自引率
1.20%
发文量
763
审稿时长
10 weeks
期刊介绍: The Lancet Global Health is an online publication that releases monthly open access (subscription-free) issues.Each issue includes original research, commentary, and correspondence.In addition to this, the publication also provides regular blog posts. The main focus of The Lancet Global Health is on disadvantaged populations, which can include both entire economic regions and marginalized groups within prosperous nations.The publication prefers to cover topics related to reproductive, maternal, neonatal, child, and adolescent health; infectious diseases (including neglected tropical diseases); non-communicable diseases; mental health; the global health workforce; health systems; surgery; and health policy.
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