AI Insight
This study analyzed prescription and diagnostic data from 25.7 million medicines and 156,000 microbiology samples from Tata 1mg's digital healthcare platform in India between 2023-2025. The research found that 10.8% of prescribed medicines were antibiotics, with "Watch" category antibiotics (those with higher resistance potential) exceeding "Access" antibiotics (first-line treatments) in all qualifying states. In urinary tract infections caused by E. coli, resistance to Watch antibiotics like ceftriaxone and ciprofloxacin exceeded 50%, while resistance to Access antibiotics remained below 5%, and time-series analysis suggested resistance to Watch antibiotics preceded resistance changes in Access antibiotics by 3-6 months.
Why it matters
This study demonstrates that routine digital healthcare data can effectively monitor antibiotic resistance patterns in community settings, addressing a critical gap in India's surveillance systems that traditionally focus on hospitals. The findings reveal concerning overuse of broad-spectrum antibiotics and high resistance rates that could inform prescribing guidelines and public health interventions.
Understand the Science
⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Hospital-based surveillance captures important components of antimicrobial resistance in India, but community-facing data linking prescribing and resistance remain limited. To address this, we analysed routinely generated prescription and diagnostic data from Tata 1mg from 2023 to 2025. Among 25.7 million medicines prescribed, 10.8% were antibiotics, with Watch antibiotics exceeding Access antibiotics in every state meeting the inclusion criteria. Among 156,000 diagnostic microbiology samples, urine cultures predominated, with Escherichia coli accounting for 60.6% of culture-positive isolates. In urinary E. coli, resistance was low to the Access antibiotics nitrofurantoin and amikacin (4.9% each), but high to the Watch antibiotics ceftriaxone (53.6%) and ciprofloxacin (57.0%). Exploratory cross-correlation analyses identified lead-lag relationships in which resistance to selected Watch antibiotics preceded changes in resistance to Access antibiotics by approximately 3-6 months. Routine digital healthcare data can therefore support community-facing AMR surveillance by jointly characterising platform-recorded prescribing and susceptibility within the observed care pathway.
Source: Antibiotic prescribing and resistance beyond hospital surveillance networks in India