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Background: Early identification of patients colonized with MDROs can help healthcare facilities improve infection control and treatment. We evaluated whether a model previously validated to predict carbapenem-resistant Enterobacterales (CRE) carriage on hospital admission (area under the curve [AUC]=0.86, Lin et al. OFID 2019) would generalize to predict a patient’s likelihood of CRE and non-CRE MDRO colonization at the time of medical intensive care unit (MICU) admission. Methods: We analyzed data collected previously in a retrospective observational cohort study of patients admitted to Rush University Medical Center’s MICU from 1/2017-1/2018 and screened within the first two days for rectal MDRO colonization. Organisms of interest included CRE, carbapenem-resistant Pseudomonas aeruginosa (CRPA), vancomycin-resistant enterococci (VRE), and third-generation cephalosporin-resistant Enterobacterales (3GCR-E). Methicillin-resistant Staphylococcus aureus (MRSA) nasal colonization at admission was determined by routine clinical screening. Each patient’s first MICU admission during the study period was linked to Illinois’ hospital discharge database and assigned a CRE colonization risk probability using the existing model. Model covariates were age, and during the prior 365 days, number of short-term acute care hospitalizations (STACH) and mean STACH length of stay, number of long-term acute care hospitalizations (LTACH) and mean LTACH length of stay, prior hospital admission with an ICD-10 diagnosis code indicating bacterial infection, and current admission to LTACH. Predictive value of the model was evaluated by receiver operating characteristic (ROC) curves. Results: We analyzed 1237 MICU admissions. MDRO admission prevalence is shown in the Table. The model performed well to predict carriage of healthcare-associated MDROs, including CRE, CRPA, composite CR-MDROs (CRE & CRPA), and VRE. However, the model performed poorly for MDROs with known community reservoirs, including 3GCR-E and MRSA (Table). In general, MDRO admission prevalence increased in parallel with predicted CRE colonization risk (Figure). The number needed to screen (NNS) to detect one healthcare-associated MDRO carrier was inversely related to the CRE colonization risk score. For example, NNS in the total cohort compared to those with CRE risk score of >0.5% was: CRE 111 vs 32 patients, CRPA 333 vs 42 patients, composite CR-MDRO 83 vs 18 patients, and VRE 12 vs 4 patients. However, higher CRE risk score cutoff was inversely related to screening sensitivity. Conclusion: A prediction model using prior healthcare exposure information successfully discriminated patients likely to harbor healthcare-associated MDROs upon MICU admission. Prediction scores generated by a public-health accessible database could be used to target screening/isolation or enact protective measures for high-risk patients.
Background: Indiscriminate urine culturing of patients with indwelling urinary catheters may lead to overdiagnosis of urinary tract infections, resulting in unnecessary antibiotic treatment and inaccurate reporting of catheter-associated urinary tract infections (CAUTIs) as a hospital quality metric. We evaluated the impact of a computerized diagnostic stewardship intervention to improve urine culture testing among patients with indwelling urinary catheters. Methods: We performed a single-center retrospective observational study at Rush University Medical Center from April 2018 – July 2023. In February 2021, we implemented a computerized clinical decision support tool to promote adherence to our internal urine culture guidelines for patients with indwelling urinary catheters. Providers were required to select one guideline criteria: 1) neutropenia, 2) kidney transplant, 3) recent urologic procedure, 4) urinary tract obstruction; or if none of the criteria were met, then an infectious diseases consultation was required for approval. We compared facility-wide CAUTI rate per 10,000 catheter days and standardized infection ratio (SIR) during baseline and intervention periods using ecologic models, controlling for time and for monthly Covid-19 hospitalizations. In the intervention period, we evaluated how providers responded to the intervention. Potential harm was defined as collection of a urine culture within 7 days of the intervention that resulted in a change in clinical management. Results: In unadjusted models, CAUTI rate decreased from 12.5 to 7.6 per 10,000 catheter days (p=0.04) and SIR decreased from 0.77 to 0.49 (p=0.09) during baseline vs intervention periods. In adjusted models, the CAUTI rate decreased from 6.9 to 5.5 per 10,000 catheter days (p=0.60) (Figure 1) and SIR decreased from 0.41 to 0.35 (p=0.65) during baseline vs intervention periods. Urine catheter standard utilization ratio (SUR) did not change (p=0.36). There were 598 patient encounters with ≥1 intervention. Selecting the first intervention for each encounter, 284 (47.5%) urine cultures met our guidelines for testing and 314 (52.5%) were averted (Figure 2). Of these, only 3 ( < 1 %) had a urine culture collected in the subsequent 7 days that resulted in change in clinical management. Conclusion: We observed a trend of decreased CAUTIs over time, but effect of our diagnostic stewardship intervention was difficult to assess due to healthcare disruption caused by Covid-19. Adverse outcomes were rare among patients who had a urine culture averted. A computerized clinical decision support tool may be safe and effective as part of a multimodal program to reduce unnecessary urine cultures in patients with indwelling urinary catheters.
