Process evaluation of health system costing - Experience from CHSI study in India
Process evaluation of health system costing - Experience from CHSI study in India
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DOI：
10.1371/journal.pone.0232873
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发表时间：
2020-05-13
期刊：
影响因子：
3.7
通讯作者：
Guinness, Lorna
中科院分区：
文献类型：
--
作者：
Prinja, Shankar;Brar, Sehr;Guinness, Lorna
背景 印度正在进行一项名为“印度医疗保健服务成本核算”(CHSI) 的国家研究，旨在为卫生技术评估和定价生成可靠的医疗保健成本估算。 CHSI 对 13 个州的 52 家公立医院和 40 家私立医院进行了抽样调查，并采用了混合微观成本计算方法。本文旨在概述成本数据收集的过程、挑战和重要教训，以改进数据收集的方法和质量。方法在 CHSI 数据收集团队中进行了一项探索性调查，包括在线半结构化问卷、小组讨论和监测数据审查三个组成部分。有定性和定量的成分。获取个人数据的难度按照李克特量表进行评级。结果在一个科室/专科完成成本数据收集所需的平均时间为 7.86 (+/- 0.51) 个月，其中大部分花在数据输入和数据问题解决上。数据收集最困难的是确定设备使用情况（平均难度分数 6.59 +/- 0.52）、消耗品价格（6.09 +/- 0.58）、设备价格（6.05 +/- 0.72）和家具价格（5.64 +/- 0.68）。人力资源、药品和消耗品占总成本的 78% 和数据收集时间的 31%。然而，家具、管理费用和设备消耗了 51% 的时间，仅占总成本的 9%。寻求多个权限、缺乏电子记录、多个数据源是导致延误的关键挑战。结论微观成本计算是时间和资源密集型的。在数据收集之前解决关键问题将简化数据收集过程，提高估计质量并帮助确定优先级。电子健康记录和国家成本数据库的可用性将有助于进行成本计算研究。
BackgroundA national study, 'Costing of healthcare services in India' (CHSI) aimed at generating reliable healthcare cost estimates for health technology assessment and price-setting is being undertaken in India. CHSI sampled 52 public and 40 private hospitals in 13 states and used a mixed micro-costing approach. This paper aims to outline the process, challenges and critical lessons of cost data collection to feed methodological and quality improvement of data collection.MethodsAn exploratory survey with 3 components-an online semi-structured questionnaire, group discussion and review of monitoring data, was conducted amongst CHSI data collection teams. There were qualitative and quantitative components. Difficulty in obtaining individual data was rated on a Likert scale.ResultsMean time taken to complete cost data collection in one department/speciality was 7.86 (+/- 0.51) months, majority of which was spent on data entry and data issues resolution. Data collection was most difficult for determination of equipment usage (mean difficulty score 6.59 +/- 0.52), consumables prices (6.09 +/- 0.58), equipment price(6.05 +/- 0.72), and furniture price(5.64 +/- 0.68). Human resources, drugs & consumables contributed to 78% of total cost and 31% of data collection time. However, furniture, overheads and equipment consumed 51% of time contributing only 9% of total cost. Seeking multiple permissions, absence of electronic records, multiple sources of data were key challenges causing delays.ConclusionsMicro-costing is time and resource intensive. Addressing key issues prior to data collection would ease the process of data collection, improve quality of estimates and aid priority setting. Electronic health records and availability of national cost data base would facilitate conducting costing studies.