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Budgeting for Environmental Health Services in Healthcare Facilities: A Ten-Step Model for Planning and Costing

机译:医疗机构环境卫生服务预算:规划和成本核算的十步模型

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摘要

Environmental health services (EHS) in healthcare facilities (HCFs) are critical for safe care provision, yet their availability in low- and middle-income countries is low. A poor understanding of costs hinders progress towards adequate provision. Methods are inconsistent and poorly documented in costing literature, suggesting opportunities to improve evidence. The goal of this research was to develop a model to guide budgeting for EHS in HCFs. Based on 47 studies selected through a systematic review, we identified discrete budgeting steps, developed codes to define each step, and ordered steps into a model. We identified good practices based on a review of additional selected guidelines for costing EHS and HCFs. Our model comprises ten steps in three phases: planning, data collection, and synthesis. Costing-stakeholders define the costing purpose, relevant EHS, and cost scope; assess the EHS delivery context; develop a costing plan; and identify data sources (planning). Stakeholders then execute their costing plan and evaluate the data quality (data collection). Finally, stakeholders calculate costs and disseminate findings (synthesis). We present three hypothetical costing examples and discuss good practices, including using costing frameworks, selecting appropriate indicators to measure the quantity and quality of EHS, and iterating planning and data collection to select appropriate costing approaches and identify data gaps.
机译:医疗机构(HCF)中的环境卫生服务(EHS)对于提供安全的医疗服务至关重要,但是在低收入和中等收入国家的可用性却很低。对费用的了解不足,阻碍了充足准备金的取得。方法在成本核算文献中不一致且记录不充分,表明有机会改进证据。这项研究的目的是建立一个模型,指导HCF中EHS的预算编制。在通过系统审查选择的47项研究的基础上,我们确定了离散的预算步骤,制定了定义每个步骤的代码,并将步骤排序为模型。我们根据对EHS和HCF成本核算的其他选定指南的审查确定了良好做法。我们的模型包括三个阶段的十个步骤:计划,数据收集和综合。成本利益相关者确定成本目的,相关的EHS和成本范围;评估EHS交付环境;制定成本计划;并识别数据源(计划)。利益相关者然后执行其成本核算计划并评估数据质量(数据收集)。最后,利益相关者计算成本并传播发现(综合)。我们提供了三个假设的成本核算示例,并讨论了良好实践,包括使用成本核算框架,选择适当的指标来衡量EHS的数量和质量,以及反复进行计划和数据收集以选择适当的成本核算方法并找出数据缺口。

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