Covariates of Digital Technology in Providing Effective Health Care Services: A Primary Study in India

This qualitative study seeks to understand the factors influencing the adoption and effectiveness of digital health services among Indian citizens.By collecting primary data through surveys distributed to public health staff across policy, district, and peripheral levels, the study explores how digital technology can be optimized to improve health outcomes in India.Descriptive and inferential statistics, including binary logistic regression and ANOVA, were employed to analyse the data, focusing on the digital health score and its associations with various independent variables.Data analysis was conducted using STATA and MS Excel.The results show varying levels of digital technology adoption for health services across different population groups.Mobile phone use for notifying disease outbreaks and tracking beneficiaries had the highest adoption rates.Bivariate analysis revealed significant regional differences in digital health scores, with central regions performing better than others.Regression analysis indicated that district and peripheral levels had higher odds of good digital health scores compared to the policy/program level.ANOVA confirmed statistically significant differences between group means, with the Central region notably differing from the national average.The adoption of digital health technologies is influenced by regional variations, timing, and implementation levels.Mobile technologies are prevalent, particularly for outbreak notifications and beneficiary tracking, indicating their crucial role in healthcare.Regional differences and data collection timing significantly impact digital health scores, with district and peripheral levels performing better than policy levels.These findings highlight the need for targeted, region-specific strategies to ensure equitable and effective digital health technology adoption.