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Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial.

ABSTRACT: Multidisciplinary antimicrobial utilization teams (AUTs) have been proposed as a mechanism for improving antimicrobial use, but data on their efficacy remain limited.To determine the impact of an AUT on antimicrobial use at a teaching hospital.Randomized controlled intervention trial.A 953-bed, public, university-affiliated, urban teaching hospital.Patients who were given selected antimicrobial agents (piperacillin-tazobactam, levofloxacin, or vancomycin) by internal medicine ward teams.Twelve internal medicine teams were randomly assigned monthly: 6 teams to an intervention group (academic detailing by the AUT) and 6 teams to a control group that was given indication-based guidelines for prescription of broad-spectrum antimicrobials (standard of care), during a 10-month study period.Proportion of appropriate empirical, definitive (therapeutic), and end (overall) antimicrobial usage.A total of 784 new prescriptions of piperacillin-tazobactam, levofloxacin, and vancomycin were reviewed. The proportion of antimicrobial prescriptions written by the intervention teams that was considered to be appropriate was significantly higher than the proportion of antimicrobial prescriptions written by the control teams that was considered to be appropriate: 82% versus 73% for empirical (risk ratio [RR], 1.14; 95% confidence interval [CI], 1.04-1.24), 82% versus 43% for definitive (RR, 1.89; 95% CI, 1.53-2.33), and 94% versus 70% for end antimicrobial usage (RR, 1.34; 95% CI, 1.25-1.43). In multivariate analysis, teams that received feedback from the AUT alone (adjusted RR, 1.37; 95% CI, 1.27-1.48) or from both the AUT and the infectious diseases consultation service (adjusted RR, 2.28; 95% CI, 1.64-3.19) were significantly more likely to prescribe end antimicrobial usage appropriately, compared with control teams.A multidisciplinary AUT that provides feedback to prescribing physicians was an effective method in improving antimicrobial use. Trial registration. ClinicalTrials.gov identifier: NCT00552838.

SUBMITTER: Camins BC

PROVIDER: S-EPMC2779729 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial.

Camins Bernard C BC King Mark D MD Wells Jane B JB Googe Heidi L HL Patel Manish M Kourbatova Ekaterina V EV Blumberg Henry M HM

Infection control and hospital epidemiology 20091001 10

<h4>Background</h4>Multidisciplinary antimicrobial utilization teams (AUTs) have been proposed as a mechanism for improving antimicrobial use, but data on their efficacy remain limited.<h4>Objective</h4>To determine the impact of an AUT on antimicrobial use at a teaching hospital.<h4>Design</h4>Randomized controlled intervention trial.<h4>Setting</h4>A 953-bed, public, university-affiliated, urban teaching hospital.<h4>Patients</h4>Patients who were given selected antimicrobial agents (piperacil ...[more]

PMID: 19712032

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Project description:ImportanceThe Hospital-Acquired Condition Reduction Program (HACRP) evaluates acute care hospitals on the occurrence of patient safety events and health care-associated infections. Since its implementation, several studies have raised concerns about the overpenalization of teaching and safety-net hospitals, and although several changes in the program's methodology have been applied in the last few years, whether these changes reversed the overpenalization of teaching and safety-net hospitals is unknown.ObjectiveTo determine hospital characteristics associated with HACRP penalization and penalization reversal.Design, setting, and participantsThis retrospective cross-sectional study assessed data from 3117 acute care hospitals participating in the HACRP. The HACRP penalization and hospital characteristics were obtained from Hospital Compare (2020 and 2021), the Inpatient Prospective Payment System impact file (2020), and the American Hospital Association annual survey (2018).ExposuresHospital characteristics, including safety-net status and teaching intensity (no teaching and very minor, minor, major, and very major teaching levels).Main outcomes and measuresThe primary outcome was HACRP penalization (ie, hospitals that fell within the worst quartile of the program's performance). Multivariable models initially included all covariates, and then backward stepwise variable selection was used.ResultsOf 3117 hospitals that participated in HACRP in 2020, 779 (25.0%) were safety-net hospitals and 1090 (35.0%) were teaching institutions. In total, 771 hospitals (24.7%) were penalized. The HACRP penalization was associated with safety-net status (odds ratio [OR], 1.41 [95% CI, 1.16-1.71]) and very major teaching intensity (OR, 1.94 [95% CI, 1.15-3.28]). In addition, non-federal government hospitals were more likely to be penalized than for-profit hospitals (OR, 1.62 [95% CI, 1.23-2.14]), as were level I trauma centers (OR, 2.05 [95% CI, 1.43-2.96]) and hospitals located in the New England region (OR, 1.65 [95% CI, 1.12-2.43]). Safety-net hospitals with major teaching levels were twice as likely to be penalized as non-safety-net nonteaching hospitals (OR, 2.15 [95% CI, 1.14-4.03]). Furthermore, safety-net hospitals penalized in 2020 were less likely (OR, 0.64 [95% CI, 0.43-0.96]) to revert their HACRP penalization status in 2021.Conclusions and relevanceFindings from this cross-sectional study indicated that teaching and safety-net hospital status continued to be associated with overpenalization in the HACRP despite recent changes in its methodology. Most of these hospitals were also less likely to revert their penalization status. A reevaluation of the program methodology is needed to avoid depleting resources of hospitals caring for underserved populations.

Project description:BackgroundEmergency department (ED) visits show a high volatility over time. Therefore, EDs are likely to be crowded at peak-volume moments. ED crowding is a widely reported problem with negative consequences for patients as well as staff. Previous studies on the predictive value of weather variables on ED visits show conflicting results. Also, no such studies were performed in the Netherlands. Therefore, we evaluated prediction models for the number of ED visits in our large the Netherlands teaching hospital based on calendar and weather variables as potential predictors.MethodsData on all ED visits from June 2016 until December 31, 2019, were extracted. The 2016-2018 data were used as training set, the 2019 data as test set. Weather data were extracted from three publicly available datasets from the Royal Netherlands Meteorological Institute. Weather observations in proximity of the hospital were used to predict the weather in the hospital's catchment area by applying the inverse distance weighting interpolation method. The predictability of daily ED visits was examined by creating linear prediction models using stepwise selection; the mean absolute percentage error (MAPE) was used as measurement of fit.ResultsThe number of daily ED visits shows a positive time trend and a large impact of calendar events (higher on Mondays and Fridays, lower on Saturdays and Sundays, higher at special times such as carnival, lower in holidays falling on Monday through Saturday, and summer vacation). The weather itself was a better predictor than weather volatility, but only showed a small effect; the calendar-only prediction model had very similar coefficients to the calendar+weather model for the days of the week, time trend, and special time periods (both MAPE's were 8.7%).ConclusionsBecause of this similar performance, and the inaccuracy caused by weather forecasts, we decided the calendar-only model would be most useful in our hospital; it can probably be transferred for use in EDs of the same size and in a similar region. However, the variability in ED visits is considerable. Therefore, one should always anticipate potential unforeseen spikes and dips in ED visits that are not shown by the model.

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Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial.

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Impact of an antimicrobial utilization program on antimicrobial use at a large teaching hospital: a randomized controlled trial.

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