Data quality of out-of-pocket payment on institutional delivery in India

Estimates of out-of-pocket (OOP) payments on health care are increasingly being used in research and policy. In India, these estimates are typically derived from health surveys by the National Sample Survey (NSS). The questions on OOP payment on delivery care have recently been integrated into the last two rounds of India’s National Family and Health Surveys. These surveys differs on content of questions, reporting, and recording of responses that may have a bearing on the reliability of OOP payment estimates. This paper examines issues related to the data quality of OOP payments using recent rounds of two large-scale population-based surveys: the NFHS, 2019–21 and the 2018 National Sample Survey (NSS). Our analysis includes 155,624 births delivered in healthcare facilities from NFHS-5 and 27,664 cases of hospital-based delivery care recorded in the 75th round of the NSS health survey, 2018. We have used descriptive statistics and a two-part regression model to examine variations of OOP payment across surveys. OOP payments showed variations across socioeconomic and demographic groups in both surveys, with some notable correspondence alongside significant differences. Variations are similar for those availing services from private health centres. After controlling for socio-economic and demographic factors, OOP payments in the NFHS were lower among the poorest and higher among the wealthiest compared to the NSS. State-level variations in OOP payments were also more pronounced between the two surveys. The variations in OOP payment across surveys were possibly due to the structure of questions, recall bias, and variations in the price level. We recommend standardizing survey questions to improve the reliability of OOP payment estimates across surveys.

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Journal
SSM - Health Systems
Published
2025-04-06
DOI
https://doi.org/10.1016/j.ssmhs.2025.100071
Primary Topic
Healthcare Systems and Reforms
Type
article
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article

Data quality of out-of-pocket payment on institutional delivery in India

Sanjay K. Mohanty, Sowmya Ramesh, Santosh Kumar Sharma, Suraj Maiti et al.
SSM - Health Systems
Healthcare Systems and Reforms
article

Data quality of out-of-pocket payment on institutional delivery in India

Sanjay K. Mohanty, Sowmya Ramesh, Santosh Kumar Sharma, Suraj Maiti, Laxmi Kant Dwivedi, Saritha Nair, Priyanka Gautam, Sudhir Singh
article en

Abstract

Estimates of out-of-pocket (OOP) payments on health care are increasingly being used in research and policy. In India, these estimates are typically derived from health surveys by the National Sample Survey (NSS). The questions on OOP payment on delivery care have recently been integrated into the last two rounds of India’s National Family and Health Surveys. These surveys differs on content of questions, reporting, and recording of responses that may have a bearing on the reliability of OOP payment estimates. This paper examines issues related to the data quality of OOP payments using recent rounds of two large-scale population-based surveys: the NFHS, 2019–21 and the 2018 National Sample Survey (NSS). Our analysis includes 155,624 births delivered in healthcare facilities from NFHS-5 and 27,664 cases of hospital-based delivery care recorded in the 75th round of the NSS health survey, 2018. We have used descriptive statistics and a two-part regression model to examine variations of OOP payment across surveys. OOP payments showed variations across socioeconomic and demographic groups in both surveys, with some notable correspondence alongside significant differences. Variations are similar for those availing services from private health centres. After controlling for socio-economic and demographic factors, OOP payments in the NFHS were lower among the poorest and higher among the wealthiest compared to the NSS. State-level variations in OOP payments were also more pronounced between the two surveys. The variations in OOP payment across surveys were possibly due to the structure of questions, recall bias, and variations in the price level. We recommend standardizing survey questions to improve the reliability of OOP payment estimates across surveys.

SSM - Health SystemsVol. 4
International Institute for Population Sciences (IN), Indian Council of Medical Research (IN), Population Council Institute (IN), Virginia Tech (US), Academy of Scientific and Innovative Research (IN)
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Healthcare Systems and Reforms
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