Dataset Information

Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program.

ABSTRACT:

Background

Prospective audit with feedback (PAF) is an impactful strategy for antimicrobial stewardship program (ASP) activities. However, because PAF requires reviewing large numbers of antimicrobial orders on a case-by-case basis, PAF programs are highly resource intensive. The current study aimed to identify predictors of ASP intervention (ie, feedback) and to build models to identify orders that can be safely bypassed from review, to make PAF programs more efficient.

Methods

We performed a retrospective cross-sectional study of inpatient antimicrobial orders reviewed by the University of Maryland Medical Center's PAF program between 2017 and 2019. We evaluated the relationship between antimicrobial and patient characteristics with ASP intervention using multivariable logistic regression models. Separately, we built prediction models for ASP intervention using statistical and machine learning approaches and evaluated performance on held-out data.

Results

Across 17 503 PAF reviews, 4219 (24%) resulted in intervention. In adjusted analyses, a clinical pharmacist on the ordering unit or receipt of an infectious disease consult were associated with 17% and 56% lower intervention odds, respectively (adjusted odds ratios [aORs], 0.83 and 0.44; P ≤ .001 for both). Fluoroquinolones had the highest adjusted intervention odds (aOR, 3.22 [95% confidence interval, 2.63-3.96]). A machine learning classifier (C-statistic 0.76) reduced reviews by 49% while achieving 78% sensitivity. A "workflow simplified" regression model that restricted to antimicrobial class and clinical indication variables, 2 strong machine learning-identified predictors, reduced reviews by one-third while achieving 81% sensitivity.

Conclusions

Prediction models substantially reduced PAF review caseloads while maintaining high sensitivities. Our results and approach may offer a blueprint for other ASPs.

SUBMITTER: Goodman KE

PROVIDER: S-EPMC9297307 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program.

Goodman Katherine E KE Heil Emily L EL Claeys Kimberly C KC Banoub Mary M Bork Jacqueline T JT

Open forum infectious diseases 20220610 7

<h4>Background</h4>Prospective audit with feedback (PAF) is an impactful strategy for antimicrobial stewardship program (ASP) activities. However, because PAF requires reviewing large numbers of antimicrobial orders on a case-by-case basis, PAF programs are highly resource intensive. The current study aimed to identify predictors of ASP intervention (ie, feedback) and to build models to identify orders that can be safely bypassed from review, to make PAF programs more efficient.<h4>Methods</h4>W ...[more]

PMID: 35873287

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Project description:IntroductionInappropriate use of antimicrobials in hospitals contributes to antimicrobial resistance. Antimicrobial stewardship (AMS) interventions aim to improve antimicrobial prescribing, but they are often resource and personnel intensive. Computerised decision supportsystems (CDSSs) seem a promising tool to improve antimicrobial prescribing but have been insufficiently studied in clinical trials.Methods and analysisThe COMPuterized Antibiotic Stewardship Study trial, is a publicly funded, open-label, cluster randomised, controlled superiority trial which aims to determine whether a multimodal CDSS intervention integrated in the electronic health record (EHR) reduces overall antibiotic exposure in adult patients hospitalised in wards of two secondary and one tertiary care centre in Switzerland compared with 'standard-of-care' AMS. Twenty-four hospital wards will be randomised 1:1 to either intervention or control, using a 'pair-matching' approach based on baseline antibiotic use, specialty and centre. The intervention will consist of (1) decision support for the choice of antimicrobial treatment and duration of treatment for selected indications (based on indication entry), (2) accountable justification for deviation from the local guidelines (with regard to the choice of molecules and duration), (3) alerts for self-guided re-evaluation of treatment on calendar day 4 of antimicrobial therapy and (4) monthly ward-level feedback of antimicrobial prescribing indicators. The primary outcome will be the difference in overall systemic antibiotic use measured in days of therapy per admission based on administration data recorded in the EHR over the whole intervention period (12 months), taking into account clustering. Secondary outcomes include qualitative and quantitative antimicrobial use indicators, economic outcomes and clinical, microbiological and patient safety indicators.Ethics and disseminationEthics approval was obtained for all participating sites (Comission Cantonale d'Éthique de la Recherche (CCER)2017-00454). The results of the trial will be submitted for publication in a peer-reviewed journal. Further dissemination activities will be presentations/posters at national and international conferences.Trial registration numberNCT03120975; Pre-results.

Project description:BackgroundThe success of antimicrobial stewardship is dependent on how often it is completed and which antimicrobials are targeted. We evaluated the impact of an antimicrobial stewardship program (ASP) in three non-ICU settings where all systemic antibiotics, regardless of spectrum, were targeted on the first weekday after initiation.MethodsProspective audit and feedback (PAAF) was initiated on the surgical, respiratory, and medical wards of a community hospital on July 1, 2010, October 1, 2010, and April 1, 2012, respectively. We evaluated rates of total antibiotic use, measured in days on therapy (DOTs), among all patients admitted to the wards before and after PAAF initiation using an interrupted time series analysis. Changes in antibiotic costs, rates of C. difficile infection (CDI), mortality, readmission, and length of stay were evaluated using univariate analyses.ResultsTime series modelling demonstrated that total antibiotic use decreased (± standard error) by 100 ± 51 DOTs/1,000 patient-days on the surgical wards (p = 0.049), 100 ± 46 DOTs/1,000 patient-days on the respiratory ward (p = 0.029), and 91 ± 33 DOTs/1,000 patient-days on the medical wards (p = 0.006) immediately following PAAF initiation. Reductions in antibiotic use were sustained up to 50 months after intervention initiation, and were accompanied by decreases in antibiotic costs. There were no significant changes to patient outcomes on the surgical and respiratory wards following intervention initiation. On the medical wards, however, readmission increased from 4.6 to 5.6 per 1,000 patient-days (p = 0.043), while mortality decreased from 7.4 to 5.0 per 1,000 patient-days (p = 0.001). CDI rates showed a non-significant declining trend after PAAF initiation.ConclusionsASPs can lead to cost-effective, sustained reductions in total antibiotic use when interventions are conducted early in the course of therapy and target all antibiotics. Shifting to such a model may help strengthen the effectiveness of ASPs in non-ICU settings.

Project description:ImportanceAntibiotics are commonly prescribed in primary care, increasing the risk of antimicrobial resistance in the population.ObjectiveTo investigate the effect of quarterly audit and feedback on antibiotic prescribing among primary care physicians in Switzerland with medium to high antibiotic prescription rates.Design, setting, and participantsThis pragmatic randomized clinical trial was conducted from January 1, 2018, to December 31, 2019, among 3426 registered primary care physicians and pediatricians in single or small practices in Switzerland who were among the top 75% prescribers of antibiotics. Intention-to-treat analysis was performed using analysis of covariance models and conducted from September 1, 2021, to January 31, 2022.InterventionsPrimary care physicians were randomized in a 1:1 fashion to undergo quarterly antibiotic prescribing audit and feedback with peer benchmarking vs no intervention for 2 years, with 2017 used as the baseline year. Anonymized patient-level claims data from 3 health insurers serving roughly 50% of insurees in Switzerland were used for audit and feedback. The intervention group also received evidence-based guidelines for respiratory tract and urinary tract infection management and community antibiotic resistance information. Physicians in the intervention group were blinded regarding the nature of the trial, and physicians in the control group were not informed of the trial.Main outcomes and measuresThe claims data used for audit and feedback were analyzed to assess outcomes. Primary outcome was the antibiotic prescribing rate per 100 consultations during the second year of the intervention. Secondary end points included overall antibiotic use in the first year and over 2 years, use of quinolones and oral cephalosporins, all-cause hospitalizations, and antibiotic use in 3 age groups.ResultsA total of 3426 physicians were randomized to the intervention (n = 1713) and control groups (n = 1713) serving 629 825 and 622 344 patients, respectively, with a total of 4 790 525 consultations in the baseline year of 2017. In the entire cohort, a 4.2% (95% CI, 3.9%-4.6%) relative increase in the antibiotic prescribing rate was noted during the second year of the intervention compared with 2017. In the intervention group, the median annual antibiotic prescribing rate per 100 consultations was 8.2 (IQR, 6.1-11.4) in the second year of the intervention and was 8.4 (IQR, 6.0-11.8) in the control group. Relative to the overall increase, a -0.1% (95% CI, -1.2% to 1.0%) lower antibiotic prescribing rate per 100 consultations was found in the intervention group compared with the control group. No relevant reductions in specific antibiotic prescribing rates were noted between groups except for quinolones in the second year of the intervention (-0.9% [95% CI, -1.5% to -0.4%]).Conclusions and relevanceThis randomized clinical trial found that quarterly personalized antibiotic prescribing audit and feedback with peer benchmarking did not reduce antibiotic prescribing among primary care physicians in Switzerland with medium to high antibiotic prescription rates.Trial registrationClinicalTrials.gov Identifier: NCT03379194.

Dataset Information

Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program.

Background

Methods

Results

Conclusions

Publications

Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention "Hotspots" in an Antibiotic Audit and Feedback Program.

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