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规划人力资源和设施以实现可持续发展目标:一种预测印度尼西亚癌症控制需求的决策分析建模方法。

Planning human resources and facilities to achieve Sustainable Development Goals: a decision-analytical modelling approach to predict cancer control requirements in Indonesia.

机构信息

Department of Radiation Oncology, Faculty of Medicine Universitas Indonesia, Dr Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia.

Health Economics Unit, Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.

出版信息

BMJ Open. 2022 May 9;12(5):e059555. doi: 10.1136/bmjopen-2021-059555.

DOI:10.1136/bmjopen-2021-059555
PMID:35534085
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9086632/
Abstract

OBJECTIVES

Indonesia aims to achieve universal health coverage (UHC) and Sustainable Development Goals (SDGs), including SDG 3 target 4, which focuses on cancer control, by 2030. This study aimed to forecast the human resources for health (HRH) and facilities required for cancer control in Indonesia over an 11-year period to support these goals.

DESIGN

A two-stage Markov model was developed to forecast the demand side of facilities and HRH requirements for cancer control in Indonesia over an 11-year period.

SETTING

Data sources used include the Indonesia Health Profile Report (2019), the Indonesian Radiation Oncology Society Database and National Cancer Control Committee documents (2019).

METHODS

The study involved modelling the current availability of HRH and healthcare facilities in Indonesia and predicting future requirements. The gap between the current and the required HRH and facilities related to oncology, and the costs associated with meeting these requirements, were analysed.

RESULTS

Results indicate the need to increase the number of healthcare facilities and HRH to achieve SDG targets. However, UHC for cancer care still may not be achieved, as eastern Indonesia is predicted to have no tertiary hospital until 2030. The forecast shows that Indonesia had a median of only 39% of the HRH requirements in 2019. Closing the HRH gap requires around a 47.6% increase in salary expenditure.

CONCLUSION

This study demonstrates the application of decision-analytical modelling approach to planning HRH and facilities in the context of a low-to-middle-income country. Scaling up oncology services in Indonesia to attain the SDG targets will require expansion of the number and capability of healthcare facilities and HRH. This work allows an in-depth understanding of the resources needed to achieve UHC and SDGs and could be utilised in other disease areas and contexts.

摘要

目的

印度尼西亚的目标是到 2030 年实现全民健康覆盖(UHC)和可持续发展目标(SDG),包括关注癌症控制的 SDG 目标 3 第 4 项。本研究旨在预测印度尼西亚在未来 11 年内癌症控制所需的卫生人力资源(HRH)和设施,以支持这些目标。

设计

采用两阶段马尔可夫模型预测印度尼西亚在未来 11 年内癌症控制所需设施和 HRH 的需求侧。

设置

使用的数据来源包括《印度尼西亚健康状况报告》(2019 年)、印度尼西亚放射肿瘤学会数据库和国家癌症控制委员会文件(2019 年)。

方法

该研究涉及对印度尼西亚当前 HRH 和医疗设施的可用性进行建模,并预测未来的需求。分析了当前和所需的与肿瘤学相关的 HRH 和设施之间的差距,以及满足这些需求的相关成本。

结果

结果表明,需要增加医疗设施和 HRH 的数量,以实现 SDG 目标。然而,由于预计到 2030 年,印度尼西亚东部将没有三级医院,因此可能无法实现癌症护理的 UHC。预测结果显示,印度尼西亚 2019 年的 HRH 需求中位数仅为 39%。缩小 HRH 差距需要大约 47.6%的薪资支出增长。

结论

本研究展示了决策分析模型方法在中低收入国家规划 HRH 和设施方面的应用。为了实现 SDG 目标,印度尼西亚需要扩大癌症服务的规模,以扩大医疗设施和 HRH 的数量和能力。这项工作使人们深入了解实现 UHC 和 SDG 所需的资源,并可在其他疾病领域和背景下使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/24c958669f13/bmjopen-2021-059555f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/806beebccbe0/bmjopen-2021-059555f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/e52ba98056bf/bmjopen-2021-059555f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/24c958669f13/bmjopen-2021-059555f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/806beebccbe0/bmjopen-2021-059555f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/e52ba98056bf/bmjopen-2021-059555f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92d6/9086632/24c958669f13/bmjopen-2021-059555f03.jpg

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本文引用的文献

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Mapping and Visualization of Cancer Research in Indonesia: A Scientometric Analysis.印度尼西亚癌症研究的绘制与可视化:科学计量分析。
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2016-2026 年加纳公共部门医疗设施和卫生人力需求预测。
Int J Health Policy Manag. 2018 Nov 1;7(11):1040-1052. doi: 10.15171/ijhpm.2018.64.
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