OBJECTIVES

Cost-utility analysis is the most preferred form of economic evaluation by HTA agencies worldwide such as NICE and PBAC. This systematic literature review analysed the cost-utility studies conducted from an Indian perspective.

METHODS

Comprehensive search was conducted in PubMed, National Health Service Economic Evaluation Database (NHSEED) and Cochrane library to identify relevant literature published between November 2009 to November 2019. In addition, hand searching was also conducted. Two researchers independently reviewed and assessed the study quality using Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Discrepancies between the two reviewers were resolved by discussion with the third reviewer.

RESULTS

Thirty-five studies were included in the final review. Thirteen studies used Markov model, five studies used decision tree model, four studies used a combination of decision tree and Markov model and one each used microsimulation and dynamic compartmental model. Of the rest, nine were trial based evaluations and two were observational studies. Therapeutic areas modeled were infectious diseases (n=12), ophthalmology (n=5), endocrine disorders (n=4), oncology (n=3) and others (n=11). Eighteen studies did not report the state where the research was conducted. Five studies were carried out in Tamil Nadu, four in Goa, three in Punjab, two each in Delhi, Maharashtra and Uttar Pradesh and one each in West Bengal and Karnataka. Twenty-nine studies performed sensitivity analysis. Twenty-eight studies were published after 2015.Twenty-three, eight and four studies were found to be of excellent, very good and good quality, respectively. The average quality score of the studies was 19.21 out of 24.

CONCLUSIONS

Maximum studies used Markov modelling method for the analyses and the lead therapeutic area was infectious disease. While most of the studies were of excellent quality, the overall quality of the remaining papers could be improved by addressing parameters such as sub-group analyses, study perspective, discount rate and use of sensitivity analysis.