A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Adaptation and validation of an antibiotic prescribing, peer comparison metric for respiratory tract diagnoses in walk-in clinics: a mixed-methods analysis. | LitMetric

AI Article Synopsis

  • - The study examines antibiotic overuse in walk-in clinics, focusing on the effectiveness of a specific metric that tracks antibiotic prescribing for respiratory tract diagnoses (RTDs) while excluding complicating factors.
  • - Data from 331,496 clinic visits between 2018-2022 revealed that 36.5% met RTD criteria, with 36.7% of those receiving antibiotics; factors like patient age and comorbidities influenced prescribing rates.
  • - Provider interviews indicated that the RTD metric is acceptable for assessing antibiotic prescribing practices, suggesting it has validity, but further research is needed to evaluate its effectiveness as a feedback tool.

Article Abstract

Objective: Antibiotic overuse is common across walk-in clinics, but it is unclear which stewardship metrics are most effective for audit and feedback. In this study, we assessed the validity of a metric that captures antibiotic prescribing for respiratory tract diagnoses (RTDs).

Design: We performed a mixed-methods study to evaluate an RTD metric, which quantified the frequency at which a provider prescribed antibiotics for RTD visits after excluding visits with complicating factors.

Setting: Seven walk-in clinics across an integrated healthcare system.

Participants: We included clinic visits during 2018-2022. We also conducted 17 semi-structured interviews with 10 unique providers to assess metric acceptability.

Results: There were 331,496 visits; 120,937 (36.5%) met RTD criteria and 44,382 (36.7%) of these received an antibiotic. Factors associated with an increased odds of antibiotic use for RTDs included patient age ≥ 65 (OR = 1.40; 95% CI 1.30-1.51), age 0-17 (1.55, 95% CI 1.50-1.60), and ≥1 comorbidity (OR = 1.22; 95% CI = 1.15-1.29). After stratifying providers by their antibiotic-prescribing frequency for RTDs, patient case-mix was similar across tertiles. However, the highest tertile of prescribers more frequently coded suppurative otitis media and more frequently prescribed antibiotics for antibiotic-nonresponsive conditions (eg, viral infections). There was no correlation between antibiotic prescribing for RTDs and the frequency of return visits (r = 0.01, = 0.96). Interviews with providers demonstrated the acceptability of the metric as an assessment tool.

Conclusion: A provider-level metric that quantifies the frequency of antibiotic prescribing for all RTDs has both construct and face validity. Future studies should assess whether this type of metric is an effective feedback tool.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11500272PMC
http://dx.doi.org/10.1017/ash.2024.436DOI Listing

Publication Analysis

Top Keywords

antibiotic prescribing
16
walk-in clinics
12
respiratory tract
8
tract diagnoses
8
prescribed antibiotics
8
prescribing rtds
8
antibiotic
7
metric
7
visits
5
adaptation validation
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!