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Screening for asymptomatic bacteriuria (ASB) is not recommended outside of patients undergoing invasive urological procedures and during pregnancy. Despite national guidelines recommending against screening for ASB, this practice is prevalent. We present outcomes from a quality-improvement intervention targeting patients undergoing cardiac artery bypass grafting surgery (CABG) at Massachusetts General Hospital, a tertiary-care hospital in Boston, Massachusetts, where preoperative testing checklists were modified to remove routine urinalysis and urine culture. This was a before-and-after intervention study.
Prior to the intervention, screening for ASB was included in the preoperative check list for all patients undergoing CABG. We assessed the proportion of patients undergoing screening for ASB in the 6 months prior to and after the intervention. We estimated cost savings from averted laboratory analyses, and we evaluated changes in antibiotic prescriptions. We additionally examined the incidence of postoperative surgical-site infections (SSIs), central-line–associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs) and Clostridioides difficile infections (CDIs).
Comparing the pre- and postintervention periods, urinalyses decreased by 76.5% and urine cultures decreased by 87.0%, with an estimated cost savings of $8,090.38. There were 50% fewer antibiotic prescriptions for bacteriuria after the intervention.
Removal of urinalysis and urine culture from preoperative checklists for cardiac surgery led to a statistically significant decrease in testing without an increase in SSIs, CLABSIs, CAUTIs, or CDI. Challenges identified included persistence of checklists in templated order sets in the electronic health record.
The coronavirus disease 2019 (COVID-19) pandemic highlighted the lack of agreement regarding the definition of aerosol-generating procedures and potential risk to healthcare personnel. We convened a group of Massachusetts healthcare epidemiologists to develop consensus through expert opinion in an area where broader guidance was lacking at the time.
Many data-driven patient risk stratification models have not been evaluated prospectively. We performed and compared the prospective and retrospective evaluations of 2 Clostridioides difficile infection (CDI) risk-prediction models at 2 large academic health centers, and we discuss the models’ robustness to data-set shifts.
We describe an approach to the evaluation and isolation of hospitalized persons under investigation (PUIs) for coronavirus disease 2019 (COVID-19) at a large US academic medical center. Only a small proportion (2.9%) of PUIs with 1 or more repeated severe acute respiratory coronavirus virus 2 (SARS-CoV-2) nucleic acid amplification tests (NAATs) after a negative NAAT were diagnosed with COVID-19.
To describe an investigation into 5 clinical cases of carbapenem-resistant Acinetobacter baumannii (CRAB).
Epidemiological investigation supplemented by whole-genome sequencing (WGS) of clinical and environmental isolates.
A tertiary-care academic health center in Boston, Massachusetts.
Patients or participants:
Individuals identified with CRAB clinical infections.
A detailed review of patient demographic and clinical data was conducted. Clinical isolates underwent phenotypic antimicrobial susceptibility testing and WGS. Infection control practices were evaluated, and CRAB isolates obtained through environmental sampling were assessed by WGS. Genomic relatedness was measured by single-nucleotide polymorphism (SNP) analysis.
Four clinical cases spanning 4 months were linked to a single index case; isolates differed by 1–7 SNPs and belonged to a single cluster. The index patient and 3 case patients were admitted to the same room prior to their development of CRAB infection, and 2 case patients were admitted to the same room within 48 hours of admission. A fourth case patient was admitted to a different unit. Environmental sampling identified highly contaminated areas, and WGS of 5 environmental isolates revealed that they were highly related to the clinical cluster.
We report a cluster of highly resistant Acinetobacter baumannii that occurred in a burn ICU over 5 months and then spread to a separate ICU. Two case patients developed infections classified as community acquired under standard epidemiological definitions, but WGS revealed clonality, highlighting the risk of burn patients for early-onset nosocomial infections. An extensive investigation identified the role of environmental reservoirs.
To validate a system to detect ventilator associated events (VAEs) autonomously and in real time.
Retrospective review of ventilated patients using a secure informatics platform to identify VAEs (ie, automated surveillance) compared to surveillance by infection control (IC) staff (ie, manual surveillance), including development and validation cohorts.
The Massachusetts General Hospital, a tertiary-care academic health center, during January–March 2015 (development cohort) and January–March 2016 (validation cohort).
Ventilated patients in 4 intensive care units.
The automated process included (1) analysis of physiologic data to detect increases in positive end-expiratory pressure (PEEP) and fraction of inspired oxygen (FiO2); (2) querying the electronic health record (EHR) for leukopenia or leukocytosis and antibiotic initiation data; and (3) retrieval and interpretation of microbiology reports. The cohorts were evaluated as follows: (1) manual surveillance by IC staff with independent chart review; (2) automated surveillance detection of ventilator-associated condition (VAC), infection-related ventilator-associated complication (IVAC), and possible VAP (PVAP); (3) senior IC staff adjudicated manual surveillance–automated surveillance discordance. Outcomes included sensitivity, specificity, positive predictive value (PPV), and manual surveillance detection errors. Errors detected during the development cohort resulted in algorithm updates applied to the validation cohort.
In the development cohort, there were 1,325 admissions, 479 ventilated patients, 2,539 ventilator days, and 47 VAEs. In the validation cohort, there were 1,234 admissions, 431 ventilated patients, 2,604 ventilator days, and 56 VAEs. With manual surveillance, in the development cohort, sensitivity was 40%, specificity was 98%, and PPV was 70%. In the validation cohort, sensitivity was 71%, specificity was 98%, and PPV was 87%. With automated surveillance, in the development cohort, sensitivity was 100%, specificity was 100%, and PPV was 100%. In the validation cohort, sensitivity was 85%, specificity was 99%, and PPV was 100%. Manual surveillance detection errors included missed detections, misclassifications, and false detections.
Manual surveillance is vulnerable to human error. Automated surveillance is more accurate and more efficient for VAE surveillance.
An estimated 293,300 healthcare-associated cases of Clostridium difficile infection (CDI) occur annually in the United States. To date, research has focused on developing risk prediction models for CDI that work well across institutions. However, this one-size-fits-all approach ignores important hospital-specific factors. We focus on a generalizable method for building facility-specific models. We demonstrate the applicability of the approach using electronic health records (EHR) from the University of Michigan Hospitals (UM) and the Massachusetts General Hospital (MGH).
We utilized EHR data from 191,014 adult admissions to UM and 65,718 adult admissions to MGH. We extracted patient demographics, admission details, patient history, and daily hospitalization details, resulting in 4,836 features from patients at UM and 1,837 from patients at MGH. We used L2 regularized logistic regression to learn the models, and we measured the discriminative performance of the models on held-out data from each hospital.
Using the UM and MGH test data, the models achieved area under the receiver operating characteristic curve (AUROC) values of 0.82 (95% confidence interval [CI], 0.80–0.84) and 0.75 ( 95% CI, 0.73–0.78), respectively. Some predictive factors were shared between the 2 models, but many of the top predictive factors differed between facilities.
A data-driven approach to building models for estimating daily patient risk for CDI was used to build institution-specific models at 2 large hospitals with different patient populations and EHR systems. In contrast to traditional approaches that focus on developing models that apply across hospitals, our generalizable approach yields risk-stratification models tailored to an institution. These hospital-specific models allow for earlier and more accurate identification of high-risk patients and better targeting of infection prevention strategies.
To determine the impact of methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus (MRSA/VRE) designations, or flags, on selected hospital operational outcomes.
Retrospective cohort study of inpatients admitted to the Massachusetts General Hospital during 2010–2011.
Operational outcomes were time to bed arrival, acuity-unrelated within-hospital transfers, and length of stay. Covariates considered included demographic and clinical characteristics: age, gender, severity of illness on admission, admit day of week, residence prior to admission, hospitalization within the prior 30 days, clinical service, and discharge destination.
Overall, 81,288 admissions were included. After adjusting for covariates, patients with a MRSA/VRE flag at the time of admission experienced a mean delay in time to bed arrival of 1.03 hours (9.63 hours [95% CI, 9.39–9.88] vs 8.60 hours [95% CI, 8.47–8.73]). These patients had 1.19 times the odds of experiencing an acuity-unrelated within-hospital transfer [95% CI, 1.13–1.26] and a mean length of stay 1.76 days longer (7.03 days [95% CI, 6.82–7.24] vs 5.27 days [95% CI, 5.15–5.38]) than patients with no MRSA/VRE flag.
MRSA/VRE designation was associated with delays in time to bed arrival, increased likelihood of acuity-unrelated within-hospital transfers and extended length of stay. Efforts to identify patients who have cleared MRSA/VRE colonization are critically important to mitigate inefficient use of resources and to improve inpatient flow.
Despite published catheter-associated urinary tract infection prevention guidelines, inappropriate catheter use is common. We surveyed housestaff about their knowledge of catheter-associated urinary tract infections at a teaching hospital and found most are aware of prevention guidelines; however, their application to clinical scenarios and catheter practices fall short of national goals.
Infect. Control Hosp. Epidemiol. 2015;36(11):1355–1357
To evaluate the use of inpatient pharmacy and administrative data to detect surgical site infections (SSIs) following hysterectomy and colorectal and vascular surgery.
Retrospective cohort study.
Five hospitals affiliated with academic medical centers.
Adults who underwent abdominal or vaginal hysterectomy, colorectal surgery, or vascular surgery procedures between July 1, 2003, and June 30, 2005.
We reviewed the medical records of weighted, random samples drawn from 3,079 abdominal and vaginal hysterectomy, 4,748 colorectal surgery, and 3,332 vascular surgery procedures. We compared routine surveillance with screening of inpatient pharmacy data and diagnosis codes and then performed medical record review to confirm SSI status.
Medical records from 823 hysterectomy, 736 colorectal surgery, and 680 vascular surgery procedures were reviewed. SSI rates determined by antimicrobial- and/or diagnosis code-based screening followed by medical record review (enhanced surveillance) were substantially higher than rates determined by routine surveillance (4.3% [95% confidence interval, 3.6%—5.1%] vs 2.7% for hysterectomies, 7.1% [95% confidence interval, 6.7%–8.2%] vs 2.0% for colorectal procedures, and 2.3% [95% confidence interval, 1.9%–2.9%] vs 1.4% for vascular procedures). Enhanced surveillance had substantially higher sensitivity than did routine surveillance to detect SSI (92% vs 59% for hysterectomies, 88% vs 22% for colorectal procedures, and 72% vs 43% for vascular procedures). A review of medical records confirmed SSI for 31% of hysterectomies, 20% of colorectal procedures, and 31% of vascular procedures that met the enhanced screening criteria.
Antimicrobial- and diagnosis code-based screening may be a useful method for enhancing and streamlining SSI surveillance for a variety of surgical procedures, including those procedures targeted by the Centers for Medicare and Medicaid Services.
We surveyed patient access managers on the impact of contact precautions (CP) for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococcus (VRE) on time to bed assignment, and we investigated the factors influencing infection control policies allowing for discontinuation of CP. The majority of respondents reported an increase in time to bed assignment for patients with a history of MRSA and/or VRE infection or colonization.
To evaluate the use of routinely collected electronic health data in Medicare claims to identify surgical site infections (SSIs) following hip arthroplasty, knee arthroplasty, and vascular surgery.
Retrospective cohort study.
Four academic hospitals that perform prospective SSI surveillance.
We developed lists of International Classification of Diseases, Ninth Revision, and Current Procedural Terminology diagnosis and procedure codes to identify potential SSIs. We then screened for these codes in Medicare claims submitted by each hospital on patients older than 65 years of age who had undergone 1 of the study procedures during 2007. Each site reviewed medical records of patients identified by either claims codes or traditional infection control surveillance to confirm SSI using Centers for Disease Control and Prevention/ National Healthcare Safety Network criteria. We assessed the performance of both methods against all chart-confirmed SSIs identified by either method.
Claims-based surveillance detected 1.8–4.7-fold more SSIs than traditional surveillance, including detection of all previously identified cases. For hip and vascular surgery, there was a 5-fold and 1.6-fold increase in detection of deep and organ/space infections, respectively, with no increased detection of deep and organ/space infections following knee surgery. Use of claims to trigger chart review led to confirmation of SSI in 1 out of 3 charts for hip arthroplasty, 1 out of 5 charts for knee arthroplasty, and 1 out of 2 charts for vascular surgery.
Claims-based SSI surveillance markedly increased the number of SSIs detected following hip arthroplasty, knee arthroplasty, and vascular surgery. It deserves consideration as a more effective approach to target chart reviews for identifying SSIs.
Review of health plan administrative data has been shown to be more sensitive than other methods for identifying postdischarge surgical-site infections (SSIs), but there has not been a direct comparison between this method and hospital-based surveillance for all infections, including those diagnosed before discharge. We compared these two methods for identifying SSIs following coronary artery bypass graft (CABG) procedures:.
We studied 1,352 CABG procedures performed among members of one health plan from March 1993 through June 1997. Health plan administrative records were reviewed based on claims containing diagnoses or procedures suggestive of infection or outpatient dispensing of antibiotics appropriate for SSI. Hospital-based surveillance information was also reviewed. SSI rates were calculated based on the total events identified by either mechanism.
Postdischarge information was reviewed for 328 (85%) of 388 procedures. SSIs were confirmed in 167 patients (13% overall risk of confirmed SSI; range, 3% to 14% in the 5 hospitals). The overall sensitivity of hospital-based surveillance was 49.7% (83 of 167), and that of health plan data was 71.8% (120 of 167). There was no significant difference among hospitals in the sensitivity of either surveillance mechanism.
Surveillance based on health plan data identified more postoperative infections, including those occurring before discharge, than did hospital-based surveillance. Screening administrative data and pharmacy activity may be an important adjunct to SSI surveillance, allowing efficient comparison of hospital-specific rates. Interpretation of differences among hospitals' infection rates requires case mix adjustment and understanding of variations in hospitals' discharge diagnosis coding practices
To measure directly the rate of contamination, during routine patient examination, of gowns, gloves, and stethoscopes with vancomycin-resistant enterococci (VRE).
A large, academic, tertiary-care hospital.
Between January 1997 and December 1998, 49 patients colonized or infected with VRE were entered in the study.
After routine examination, the examiner's glove fingertips, gown (the umbilical region and the cuffs), and stethoscope diaphragm were pressed onto Columbia colistin-nalidixic acid (CNA) agar plates with 5% sheep blood plus vancomycin 6 ug/mL. The stethoscope diaphragm was sampled again after cleaning with a 70% isopropanol wipe.
VRE were isolated from at least 1 examiner site (gloves, gowns, or stethoscope) in 33 (67%) of 49 cases. Gloves were contaminated in 63%, gowns in 37%, and stethoscopes in 31%. All three items were positive for VRE in 24%. One case each had stethoscope and gown contamination without glove contamination. Only 1 (2%) of 49 stethoscopes was positive after wiping with an alcohol swab. Contamination at any site was more likely when the patient had a colostomy or ileostomy. Patients identified by rectal-swab culture alone were as likely to contaminate their examiners as were those identified by clinical specimens.
Our study revealed a high rate of examiner contamination with VRE. The similar risk of contamination identified by surveillance and clinical cases reinforces concerns that patients not known to be colonized with VRE could serve as sources for dissemination. Wiping with alcohol is effective in decontaminating stethoscopes.
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