Objectives: Evidence-based decision-making is essential for health systems strengthening. With a network of health information systems in place, the level of data usage for programmatic decisions by sub-district level managers needs to be ascertained to feed into programmatic performance and policy decisions. This study aims to ascertain the extent of data use for decision-making by Medical Officers-In-Charge (MO-ICs) positioned at sub-district level health centers in Haryana, India. Materials and Methods: A cross-sectional study was conducted (December 2020 till May 2023) at purposively selected six districts of Haryana. Interviews capturing quantitative data were conducted with 120 MO-ICs across sub-district health units in selected districts. The main outcome measure was the Data Utilization Score (DUS), a composite score measuring the extent of data utilization based on subjective and objective assessment of MO-ICs level of data usage. Results: The average DUS was 60.1%. Almost three-fourths (72%) of MO-ICs scored more than 50%, and less than 1% scored below 25%. Subjective assessment highlighted routine data being utilized for programmatic decision-making and support, assessing objectives/targets/programs, during management meetings, and for reporting/planning/target setting. Objective assessment revealed a mismatch between self-reported (82%) and actual data usage skills (65%), limited knowledge of program indicators apart from the ones discussed during monthly meetings, and a display of the latest data in facilities. Conclusion: There was increased data usage for decision-making at the sub-district level, aligning with the availability of health information systems in India, like the Health Management Information System and Reproductive and Child Health portal. Although there was system readiness in the form of a data-informed culture with accessibility and usage of web-based information systems, yet there were limited skills for data use and a lack of knowledge about key indicators. The policy focus should be on addressing skill gaps and emphasizing key indicators.
Sahota et al. (2026) studied this question.