Developing a Pharmacist-Centered Novel Antimicrobial Stewardship (AMS) Approach for Healthcare in Pakistan: A Grounded Theory Study
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance (AMR) is one of the most significant global health threats of the 21st century, endangering healthcare systems worldwide as a silent pandemic. Despite the globally recognized role of pharmacists as antimicrobial stewards, their involvement remains limited in antimicrobial stewardship (AMS) endeavors in Pakistan. METHODS: By utilizing the Straussian grounded theory methodology, this study aimed to develop a pharmacist-centered novel AMS approach for healthcare in Pakistan in order to enhance the engagement of pharmacists in AMS and reduce the burden of AMR in Pakistan. Through 13 semi-structured in-depth interviews with pharmacists and AMS experts, this study explored the facilitators and obstacles faced by pharmacists in Pakistan pertaining to their participation in AMS. RESULTS: The findings highlighted the underutilization of pharmacists in AMS owing to persistent policy, institutional, and resource-level barriers. Several facilitators were also identified, including institutional ownership and pharmacist-prescriber-patient (3P) communication. The evidence generated informed the development of the pharmacist-centered novel AMS approach, which recommends extending AMS policy support to pharmacists, improving One Health interdisciplinary collaborations, promoting pharmacist-led behavior change campaigns, granting prescribing rights to pharmacists for minor ailments, and advancing AMS trainings and education. CONCLUSIONS: Formally integrating pharmacists into AMS efforts is the need of the hour to contain the consequences of AMR in Pakistan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".