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. 2025 Oct 31:16:1673019.
doi: 10.3389/fmicb.2025.1673019. eCollection 2025.

Integrating procurement, prescription, and resistance data to strengthen antimicrobial stewardship: insights from a public health institution in India

Vinay Modgil  1 , Sundeep Sahay  1   2 , Arunima Mukherjee  1   3 , Rashi Banta  1 , Neha Joshi  1 , Rashmi Surial  1 , Subhash Thakur  1 , Suvodeep Mazumdar  4 , Sneha Roychowdhury  5 , Neelam Taneja  6
Affiliations

Integrating procurement, prescription, and resistance data to strengthen antimicrobial stewardship: insights from a public health institution in India

Vinay Modgil et al. Front Microbiol. .

Abstract

Introduction: Sustained and sub-optimal antimicrobial use drives antimicrobial resistance (AMR), a major health systems challenge in low- and middle-income countries (LMICs) such as India. This study examined the relationship between institutional antimicrobial procurement and outpatient prescribing patterns, and how these influence resistance trends identified through antibiotic susceptibility testing (AST) in a public community hospital.

Methods: Data were collected from three sources: (i) procurement records (2018-2022), (ii) AST results from urine, pus, and stool samples (2023-2024), and (iii) outpatient prescriptions (2023-2024). Each dataset was analyzed individually and in an integrated framework to assess interrelationships between antimicrobial use and resistance.

Results: Amoxicillin-clavulanate, ciprofloxacin, and doxycycline were among the most procured drugs, with Escherichia coli (urine) resistance rates of 53%, 87%, and 39%, respectively. The most frequently prescribed antimicrobials were Amoxicillin-Clavulanate (24%), Cefixime (15%), and Azithromycin (11%); over 50% were broad-spectrum agents and over 90% belonged to the WHO AWaRe "Access" category. Correlation analysis revealed a weak positive association between procurement and sensitivity, indicating that higher procurement did not necessarily increase resistance.

Discussion: These findings demonstrate the feasibility of linking institutional datasets to identify inefficiencies in antimicrobial use and guide evidence-based stewardship interventions, including formulary revision, procurement alignment, and data-driven prescribing practices.

Keywords: antimicrobial resistance; antimicrobial stewardship policy; antimicrobial susceptibility testing; consumption; hospital; prescription.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Line graph showing DDD per ten thousand inhabitants per day from 2018 to 2022. Values are 160.48 in 2018, peaking at 309 in 2019, then dropping to 77.43 in 2020, 30.67 in 2021, and rising to 96.81 in 2022.
FIGURE 1
Institutional antimicrobial procurement in defined daily doses (DDD)/1,000/inhabitants/day over 5 years (2018–2022).
Line graph illustrating the procurement of antimicrobials in defined daily doses (DDD) from 2018 to 2022. Key medications include Azithromycin, Doxycycline, Ofloxacin with ornidazole, Amoxicillin with clavulanic acid, Amoxicillin, and Cefixime. Azithromycin, shown in blue, peaks in 2019. Doxycycline, in orange, also peaks in 2019. Ofloxacin with ornidazole, in gray, maintains a higher level through the years. Other medications show lower, varied amounts.
FIGURE 2
Top procured drugs over the year (2018–2022) in defined daily doses (DDD).
A grouped bar chart and heatmap compare the distribution of six bacterial isolates across urine, pus exudate, and stool. The bar chart shows counts, while the heatmap displays percentages, with E. coli most prevalent in urine and S. aureus in pus exudate. Color keys represent different isolates.
FIGURE 3
Clinical isolates from urine, exudate, and stool samples.
Three-part infographic on prescriptions and demographics. Left: Bar chart of prescribing indicators showing high adherence to using EDL and legible prescriptions. Center: Donut chart of gender distribution with 51 males (4.4%) and 49 females (4.3%). Right: Bar chart of age group distribution with most individuals aged 15-39 years (63.35%), followed by 40-65 years (21.93%). Average drugs per prescription is 2.8.
FIGURE 4
Key characteristics of antimicrobial prescriptions studied.
Bar chart showing prescription percentages of various antibiotics. Amoxicillin with Clavulanic Acid leads at 24.0%, categorized as Access. Cefixime, Azithromycin, and Ciprofloxacin follow, all marked as Watch. Nitrofurantoin, Ofloxacin-ornidazole, and Amoxicillin are also Access. Doxycycline and Metronidazole are included, with different categorizations from Broad to Narrow Spectrum.
FIGURE 5
Patterns of antimicrobial prescriptions as per their class and WHO AWaRe classification.
Two scatter plots compare prescription percentage to sensitivity. The left plot shows blue dots for 2023 with prescription percentages mostly below 24%. The right plot includes orange dots for 2024, with some values above 24%. The y-axis represents sensitivity, and both plots show varying levels of sensitivity across different prescription rates.
FIGURE 6
Scatterplot of prescription vs. sensitivity, comparing combined 2023/24 with 2023 and 2024.
Three scatter plots show the relationship between prescription percentage and antimicrobial sensitivity for different bacteria: E. coli (urine), Staphylococcus spp. (exudate samples), Pseudomonas spp. (urine), and Klebsiella (urine). Each plot uses different symbols for each bacterium. The top plot combines all bacteria, while the bottom left and right plots separately depict data from 2021 and 2022 for E. coli and Staphylococcus spp. The y-axis represents antimicrobial sensitivity, and the x-axis shows prescription percentage.
FIGURE 7
Scatterplot of prescription vs. sensitivity, grouped by microbe and clinical isolates.
See this image and copyright information in PMC

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