Coding and blinding in technical sample evaluation: a procurement-based approach to transparency and cost efficiency in the Indian health sector-a first-of-its-kind initiative

Background: Public procurement plays a critical role in service delivery while remaining susceptible to evaluator bias, particularly during the technical evaluation of goods even within the structured regulatory systems like India’s General Financial Rules 2017 and Central Vigilance Commission guidelines. Our study assesses whether introducing coding and blinding techniques in sample evaluation lowers evaluation bias, improves transparency, fairness and cost-efficiency in public procurement. Methods: A pre and post interventional study design (non-randomized) was conducted retrieving procurement data of two financial years, 2021-22 (pre-intervention) and 2023-24 (post-intervention) from the institutional digital procurement library and store records. The intervention consisted of assigning alphanumeric codes to items and its vendor samples with all brand markings concealed on submitted samples of goods for technical evaluation. These coded and blinded samples were evaluated by the Technical Specification Evaluation Committee (TSEC). STATA 15.0 was used to examine data. Descriptive statistics were applied and Mann-Whitney test was used to draw comparisons. Results: Fifty-six procurement events were analysed under different categories-Crystalloid (16%), General (30%), Linen (14%), Stationary (5%) and Surgical (35%). Post-intervention the number of technically shortlisted bidders increased significantly (p<0.001) whereas procurement prices decreased across all categories with significant cost reductions in Crystalloid and General categories (p<0.001). Conclusions: Using coding and blinding methods in technical sample evaluation significantly improved transparency, reduced bias leading to competitive pricing. The intervention offers a scalable approach for improving transparency and responsibility in public sector procurement systems and fits well with GFR 2017 and CVC regulations.