Understanding the heterogeneity in healthcare expenditure in India.

Health expenditure is indicative of the financial burden of health care and serves as a yardstick of health system performance. However, health expenditure may be shaped by multiple factors such as prevalence of morbidity, income inequality and above all, unobserved heterogeneity such as disease severity. This study uses finite mixture models (FMM) to analyze health expenditure distribution based on a National Sample Survey (NSS) which is a nationally representative dataset. This exercise identifies three different class of health care users, acknowledging the heterogeneity within the expenditure distribution. The classes demonstrate variations in spending behavior and associated characteristics. It is observed that health spending is influenced by disease severity, age, gender, education, social group, and economic status. Notably, health expenditure for similar diseases varies significantly across three classes, with the highest expenditure observed in the third latent class. It also reaffirms the gender disparities in health spending irrespective of the class. Additionally, socio-economic status consistently affects health expenditure across classes. These findings underscore the importance of recognizing unobserved heterogeneity in health expenditure for the design of effective healthcare policies. In conclusion, there is a need to recognize the unobserved heterogeneity in health expenditure data and such a recognition that distinct classes within may have greater significance in designing better health care policies. Beyond health expenditure, this analytical framework can be adopted to other medical and public health research to identify the latent classes, thus offering a broader methodological value.