Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, 160012, India.
International Decision Support Initiative, London, UK.
Appl Health Econ Health Policy. 2020 Oct;18(5):699-711. doi: 10.1007/s40258-020-00566-9.
India's flagship National Health insurance programme (AB-PMJAY) requires accurate cost information for evidence-based decision-making, strategic purchasing of health services and setting reimbursement rates. To address the challenge of limited health service cost data, this study used econometric methods to identify determinants of cost and estimate unit costs for each Indian state.
Using data from 81 facilities in six states, models were developed for inpatient and outpatient services at primary and secondary level public health facilities. A best-fit unit cost function was identified using guided stepwise regression and combined with data on health service infrastructure and utilisation to predict state-level unit costs.
Health service utilisation had the greatest influence on unit cost, while number of beds, facility level and the state were also good predictors. For district hospitals, predicted cost per inpatient admission ranged from 1028 (313-3429) Indian Rupees (INR) to 4499 (1451-14,159) INR and cost per outpatient visit ranged from 91 (44-196) INR to 657 (339-1337) INR, across the states. For community healthcare centres and primary healthcare centres, cost per admission ranged from 412 (148-1151) INR to 3677 (1359-10,055) INR and cost per outpatient visit ranged from 96 (50-187) INR to 429 (217-844) INR.
This is the first time cost estimates for inpatient admissions and outpatient visits for all states have been estimated using standardised data. The model demonstrates the usefulness of such an approach in the Indian context to help inform health technology assessment, budgeting and forecasting, as well as differential pricing, and could be applied to similar country contexts where cost data are limited.
印度的旗舰国家健康保险计划（AB-PMJAY）需要准确的成本信息，以便做出基于证据的决策、战略性购买医疗服务和设定报销费率。为了解决医疗服务成本数据有限的挑战，本研究使用计量经济学方法来确定成本的决定因素，并估计每个印度邦的单位成本。
利用来自六个邦的 81 个设施的数据，为初级和二级公立卫生设施的住院和门诊服务建立模型。使用有指导的逐步回归确定最佳拟合单位成本函数，并结合卫生服务基础设施和利用数据来预测邦级单位成本。
卫生服务利用对单位成本的影响最大，而床位数量、设施级别和邦也是很好的预测因素。对于地区医院，每例住院患者的预测费用在 1028 印度卢比（INR）至 4499 INR（1451-14159 INR）之间，每例门诊患者的费用在 91 INR（44-196 INR）至 657 INR（339-1337 INR）之间，在各州之间有所不同。对于社区保健中心和初级保健中心，每例住院患者的费用在 412 INR（148-1151 INR）至 3677 INR（1359-10055 INR）之间，每例门诊患者的费用在 96 INR（50-187 INR）至 429 INR（217-844 INR）之间。
这是第一次使用标准化数据估计所有邦的住院和门诊就诊的成本估计。该模型展示了在印度背景下使用这种方法的有用性，以帮助为卫生技术评估、预算编制和预测、以及差别定价提供信息，并且可以应用于成本数据有限的类似国家背景。
