arXiv · 2609.28946
Digital Medicines Information at National Scale: Search Behaviour and System Performance of MediVerify Across 1.5 Million Queries
Abstract
National-scale digital health platforms generate usage data that reveal population healthcare needs. MediVerify, Sri Lanka's online medicines information platform providing access to National Medicines Regulatory Authority (NMRA)-approved medicines, recorded over 1.49 million queries in its first year. Large-scale medicine search behaviour in low- and middle-income countries (LMICs) remains poorly characterised. Objectives: To characterise medicine information-seeking behaviour, identify mismatches between public demand and essential medicines policy, and evaluate technical performance. Methods: We retrospectively analysed 1,497,304 anonymised queries submitted between July 2024-2025. Queries were normalised and mapped to 11,933 approved medicines using fuzzy matching based on Levenshtein distance (threshold <=5). Therapeutic categories were assigned using an Anatomical Therapeutic Chemical (ATC)-aligned classification. Query patterns and system performance were analysed, and energy consumption was estimated from processing times. Results: Vitamins/minerals (11.74%), antibiotics (10.57%), anti-diabetes (7.02%), and antihypertensives (6.84%) dominated searches. The top 20 accounted for 37.3% of queries, while approximately 40%-50% of registered medicines were never queried. Zero-result queries (~ 1%) indicated unmet information needs. Frequently searched medicines diverged from essential medicines lists. Median latency was 8ms, with >99% query resolution. Estimated energy consumption was approximately 0.12 kWh per million queries. Conclusions: Large-scale medicine search data provide insights into healthcare information demand and policy alignment. MediVerify demonstrates that a national digital health platform can achieve high utilisation at low computational and environmental cost. Usage analytics could strengthen pharmaceutical policy and digital health infrastructure in LMICs.
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Praveen Charuka Athauda-Arachchi, Pandula Mahesh Athauda-Arachchi, Rohini Fernandopulle. 2026-09-24. Digital Medicines Information at National Scale: Search Behaviour and System Performance of MediVerify Across 1.5 Million Queries. https://doi.org/10.3389/fdgth.2026.1855835
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