Patients with COVID-19 may present with respiratory syndromes indistinguishable from those caused by common viruses. Early isolation and containment is challenging. Although screening all patients with respiratory symptoms for COVID-19 has been recommended, the practicality of such an effort has yet to be assessed.

Over a 6-week period during a SARS-CoV-2 outbreak, our institution introduced a “respiratory surveillance ward” (RSW) to segregate all patients with respiratory symptoms in designated areas, where appropriate personal protective equipment (PPE) could be utilized until SARS-CoV-2 testing was done. Patients could be transferred when SARS-CoV-2 tests were negative on 2 consecutive occasions, 24 hours apart.

Over the study period, 1,178 patients were admitted to the RSWs. The mean length-of-stay (LOS) was 1.89 days (SD, 1.23). Among confirmed cases of pneumonia admitted to the RSW, 5 of 310 patients (1.61%) tested positive for SARS-CoV-2. This finding was comparable to the pickup rate from our isolation ward. In total, 126 HCWs were potentially exposed to these cases; however, only 3 (2.38%) required quarantine because most used appropriate PPE. In addition, 13 inpatients overlapped with the index cases during their stay in the RSW; of these 13 exposed inpatients, 1 patient subsequently developed COVID-19 after exposure. No patient–HCW transmission was detected despite intensive surveillance.

Our institution successfully utilized the strategy of an RSW over a 6-week period to contain a cluster of COVID-19 cases and to prevent patient–HCW transmission. However, this method was resource-intensive in terms of testing and bed capacity.

Gastroenteritis causes significant morbidity and mortality in long-term care facility (LTCF) residents, a growing population within the United States. We set out to better understand gastroenteritis outbreaks in LTCF by identifying outbreak and facility characteristics associated with outbreak incidence as well as outbreak duration and size.

We conducted a retrospective cross-sectional study on LTCFs in Philadelphia County from 2009 to 2018. Outbreak characteristics and interventions were extracted from Philadelphia Department of Public Health (PDPH) database and quality data on all LTCFs was extracted from Centers for Medicare and Medicaid Services Nursing Home Compare database.

We identified 121 gastroenteritis outbreaks in 49 facilities. Numbers of affected patients ranged from 2 to 211 patients (median patient illness rate, 17%). Staff were reported ill in 94 outbreaks (median staff illness rate, 5%). Outbreak facilities were associated with higher occupancy rates (91% vs 88%; P = .033) and total bed numbers (176 vs 122; P = .071) compared to nonoutbreak facilities. Higher rates of staff illness were associated with prolonged outbreaks (13% vs 4%; P < .001) and higher patient illness rates (9% vs 4%; P = .012). Prolonged outbreaks were associated with lower frequency of cohorting for outbreak management (13% vs 41%; P = .046).

This study is the largest published analysis of gastroenteritis outbreaks in LTCFs. Facility characteristics and staff disease activity were associated with more severe outbreaks. Heightened surveillance for gastrointestinal symptoms among staff and increased use of cohorting might reduce the risk of prolonged gastroenteritis outbreaks in LTCF.

Presenteeism, or working while ill, by healthcare personnel (HCP) experiencing influenza-like illness (ILI) puts patients and coworkers at risk. However, hospital policies and practices may not consistently facilitate HCP staying home when ill.

We conducted a mixed-methods survey in March 2018 of Emerging Infections Network infectious diseases physicians, describing institutional experiences with and policies for HCP working with ILI.

Of 715 physicians, 367 (51%) responded. Of 367, 135 (37%) were unaware of institutional policies. Of the remaining 232 respondents, 206 (89%) reported institutional policies regarding work restrictions for HCP with influenza or ILI, but only 145 (63%) said these were communicated at least annually. More than half of respondents (124, 53%) reported that adherence to work restrictions was not monitored or enforced. Work restrictions were most often not perceived to be enforced for physicians-in-training and attending physicians. Nearly all (223, 96%) reported that their facility tracked laboratory-confirmed influenza (LCI) in patients; 85 (37%) reported tracking ILI. For employees, 109 (47%) reported tracking of LCI and 53 (23%) reported tracking ILI. For independent physicians, not employed by the facility, 30 (13%) reported tracking LCI and 11 (5%) ILI.

More than one-third of respondents were unaware of whether their institutions had policies to prevent HCP with ILI from working; among those with knowledge of institutional policies, dissemination, monitoring, and enforcement of these policies was highly variable. Improving communication about work-restriction policies, as well as monitoring and enforcement, may help prevent the spread of infections from HCP to patients.

To characterize nontuberculous mycobacteria (NTM) associated with case clusters at 3 medical facilities.

Retrospective cohort study using molecular typing of patient and water isolates.

Veterans Affairs Medical Centers (VAMCs).

Isolation and identification of NTM from clinical and water samples using culture, MALDI-TOF, and gene population sequencing to determine species and genetic relatedness. Clinical data were abstracted from electronic health records.

An identical strain of Mycobacterium conceptionense was isolated from 41 patients at VA Medical Centers (VAMCs A, B, and D), and from VAMC A’s ICU ice machine. Isolates were initially identified as other NTM species within the M. fortuitum clade. Sequencing analyses revealed that they were identical M. conceptionense strains. Overall, 7 patients (17%) met the criteria for pulmonary or nonpulmonary infection with NTM, and 13 of 41 (32%) were treated with effective antimicrobials regardless of infection or colonization status. Separately, a M. mucogenicum patient strain from VAMC A matched a strain isolated from a VAMC B ICU ice machine. VAMC C, in a different state, had a 4-patient cluster with Mycobacterium porcinum. Strains were identical to those isolated from sink-water samples at this facility.

NTM from hospital water systems are found in hospitalized patients, often during workup for other infections, making attribution of NTM infection problematic. Variable NTM identification methods and changing taxonomy create challenges for epidemiologic investigation and linkage to environmental sources.

The disease burden of surgical site infection (SSI) following total knee (TKA) replacement is considerable and is expected to grow with increased demand for the procedure. Diagnosing and treating SSI utilizes both inpatient and outpatient services, and the timing of diagnosis can affect health service requirements. The purpose of this study was to estimate the health system costs of infection and to compare them across time-to-diagnosis categories.

Administrative data from 2005–2016 were used to identify cases diagnosed with SSI up to 1 year following primary TKA. Uninfected controls were selected matched on age, sex and comorbidities. Costs and utilization were measured over the 2-year period following surgery using hospital and out-of-hospital data. Costs and utilization were compared for those diagnosed within 30, 90, 180, and 365 days. A subsample of cases and controls without comorbidities were also compared.

We identified 238 SSI cases over the study period. On average, SSI cases cost 8 times more than noninfected controls over the 2-year follow-up period (CaD$41,938 [US$29,965] vs CaD$5,158 [US$3,685]) for a net difference of CaD$36,780 (US$26,279). The case-to-control ratio for costs was lowest for those diagnosed within 30 days compared to those diagnosed later. When only patients without comorbidities were included, costs were >7 times higher.

Our results suggest that considerable costs result from SSI following TKA and that those costs vary depending on the time of diagnosis. A 2-year follow-up period provided a more complete estimate of cost and utilization.

Automated surveillance of healthcare-associated infections reduces workload and improves standardization, but it has not yet been adopted widely. In this study, we assessed the performance and feasibility of an easy implementable framework to develop algorithms for semiautomated surveillance of deep incisional and organ-space surgical site infections (SSIs) after orthopedic, cardiac, and colon surgeries.

Retrospective cohort study in multiple countries.

European hospitals were recruited and selected based on the availability of manual SSI surveillance data from 2012 onward (reference standard) and on the ability to extract relevant data from electronic health records. A questionnaire on local manual surveillance and clinical practices was administered to participating hospitals, and the information collected was used to pre-emptively design semiautomated surveillance algorithms standardized for multiple hospitals and for center-specific application. Algorithm sensitivity, positive predictive value, and reduction of manual charts requiring review were calculated. Reasons for misclassification were explored using discrepancy analyses.

The study included 3 hospitals, in the Netherlands, France, and Spain. Classification algorithms were developed to indicate procedures with a high probability of SSI. Components concerned microbiology, prolonged length of stay or readmission, and reinterventions. Antibiotics and radiology ordering were optional. In total, 4,770 orthopedic procedures, 5,047 cardiac procedures, and 3,906 colon procedures were analyzed. Across hospitals, standardized algorithm sensitivity ranged between 82% and 100% for orthopedic surgery, between 67% and 100% for cardiac surgery, and between 84% and 100% for colon surgery, with 72%–98% workload reduction. Center-specific algorithms had lower sensitivity.

Using this framework, algorithms for semiautomated surveillance of SSI can be successfully developed. The high performance of standardized algorithms holds promise for large-scale standardization.

Despite evidence to the contrary, many practitioners continue to inappropriately screen for and treat bacteria in the urine of clinically asymptomatic patients. The purpose of this study was to evaluate the impact of a new order set on the number of urine culture performed, antibiotic days of therapy (DOT), catheter-associated urinary tract infections (CAUTI), and associated financial impact.

A quasi-experimental before-and-after intervention.

We conducted this study at 5 Catholic Health Initiative (CHI) hospitals in Texas that use the same electronic health record (EHR) system.

The study populations included adult patients who had urine culture performed from June 2017 to June 2019.

The intervention (implemented June 25, 2018) was the addition of a new order set in the electronic health record that required practitioners to choose an indication for the type of urine study. The primary outcome was number of urine cultures performed adjusted for the number of total patient days.

Following implementation of the new order set, the number of urine cultures performed among the 5 sites decreased from 1,175.8 tests per 10,000 patient days before the intervention to 701.4 after the intervention (40.4% reduction; P < .01). Antibiotic DOT for patients with a urinary tract infection indication decreased from 102.5 to 86.9 per 1,000 patient days (15.2% reduction; P < .01). The CAUTI standardized infection ratio was 1.0 before the intervention and 0.8 after the intervention (P = .23). The estimated yearly savings following the intervention was US$535,181.

The addition of a new order set resulted in decreases in the number of urine cultures performed and the antibiotic DOT, as well as substantial financial savings.

Methods that include the time-varying nature of healthcare-associated infections (HAIs) avoid biases when estimating increased risk of death and excess length of stay. We determined the excess mortality risk and length of stay associated with HAIs among inpatients in Singapore using a multistate model that accommodates the timing of key events.

Analysis of existing prospective cohort study data.

Seven public acute-care hospitals in Singapore.

Inpatients reviewed in a HAI point-prevalence survey (PPS) conducted between June 2015 and February 2016.

We modeled each patient’s admission over time using 4 states: susceptible with no HAI, infected, died, and discharged alive. We estimated the excess mortality risk and length of stay associated with HAIs, with adjustment for the baseline characteristics between the groups for mortality risk.

We included 4,428 patients, of whom 469 had ≥1 HAI. Using a multistate model, the expected excess length of stay due to any HAI was 1.68 days (95% confidence interval [CI], 1.15–2.21 days). Surgical site infections were associated with the longest excess length of stay of 4.68 days (95% CI, 2.60–6.76 days). After adjusting for baseline differences, HAIs were associated with increased hazards of in-hospital mortality (adjusted hazard ratio [aHR], 1.32; 95% CI, 1.09–1.65) and decreased hazards in being discharged (aHR, 0.75; 95% CI, 0.67–0.84).

HAIs are associated with increased length of hospital stay and mortality in hospitalized patients. Avoiding nosocomial infections can improve patient outcomes and free valuable bed days.

To identify patient and provider characteristics associated with high-volume antibiotic prescribing for children in Tennessee, a state with high antibiotic utilization.

Cross-sectional, retrospective analysis of pediatric (aged <20 years) outpatient antibiotic prescriptions in Tennessee using the 2016 IQVIA Xponent (formerly QuintilesIMS) database.

Patient and provider characteristics, including county of prescription fill, rural versus urban county classification, patient age group, provider type (nurse practitioner, physician assistant, physician, or dentist), physician specialty, and physician years of practice were analyzed.

Tennessee providers wrote 1,940,011 pediatric outpatient antibiotic prescriptions yielding an antibiotic prescribing rate of 1,165 per 1,000 population, 50% higher than the national pediatric antibiotic prescribing rate. Mean antibiotic prescribing rates varied greatly by county (range, 39–2,482 prescriptions per 1,000 population). Physicians wrote the greatest number of antibiotic prescriptions (1,043,030 prescriptions, 54%) of which 56% were written by general pediatricians. Pediatricians graduating from medical school prior to 2000 were significantly more likely than those graduating after 2000 to be high antibiotic prescribers. Overall, 360 providers (1.7% of the 21,798 total providers in this dataset) were responsible for nearly 25% of both overall and broad-spectrum antibiotic prescriptions; 20% of these providers practiced in a single county.

Fewer than 2% of providers account for 25% of pediatric antibiotic prescriptions. High antibiotic prescribing for children in Tennessee is associated with specific patient and provider characteristics that can be used to design stewardship interventions targeted to the highest prescribing providers in specific counties and specialties.

Guidelines recommend empowering patients and families to remind healthcare workers (HCWs) to perform hand hygiene (HH). The effectiveness of empowerment tools for patients and their families in Southeast Asia is unknown.

We performed a prospective study in a pediatric intensive care unit (PICU) of a Vietnamese pediatric referral hospital. With family and HCW input, we developed a visual tool for families to prompt HCW HH. We used direct observation to collect baseline HH data. We then enrolled families to receive the visual tool and education on its use while continuing prospective collection of HH data. Multivariable logistic regression was used to identify independent predictors of HH in baseline and implementation periods.

In total, 2,014 baseline and 2,498 implementation-period HH opportunities were observed. During the implementation period, 73 families were enrolled. Overall, HCW HH was 46% preimplementation, which increased to 73% in the implementation period (P < .001). The lowest HH adherence in both periods occurred after HCW contact with patient surroundings: 16% at baseline increased to 24% after implementation. In multivariable analyses, the odds of HCW HH during the implementation period were significantly higher than baseline (adjusted odds ratio [aOR], 2.94; 95% confidence interval [CI], 2.54–3.41; P < .001) after adjusting for observation room, HCW type, time of observation (weekday business hours vs evening or weekend), and HH moment.

The introduction of a visual empowerment tool was associated with significant improvement in HH adherence among HCWs in a Vietnamese PICU. Future research should explore acceptability and barriers to use of similar tools in low- and middle-income settings.

To develop a risk score for deep sternal wound infection (DSWI) after isolated coronary artery bypass grafting (CABG).

Multicenter, prospective study.

Tertiary-care referral hospitals.

The study included 7,352 patients from the European multicenter coronary artery bypass grafting (E-CABG) registry.

Isolated CABG.

An additive risk score (the E-CABG DSWI score) was estimated from the derivation data set (66.7% of patients), and its performance was assessed in the validation data set (33.3% of patients).

DSWI occurred in 181 (2.5%) patients and increased 1-year mortality (adjusted hazard ratio, 4.275; 95% confidence interval [CI], 2.804–6.517). Female gender (odds ratio [OR], 1.804; 95% CI, 1.161–2.802), body mass index ≥30 kg/m2 (OR, 1.729; 95% CI, 1.166–2.562), glomerular filtration rate <45 mL/min/1.73 m2 (OR, 2.410; 95% CI, 1.413–4.111), diabetes (OR, 1.741; 95% CI, 1.178–2.573), pulmonary disease (OR, 1.935; 95% CI, 1.178–3.180), atrial fibrillation (OR, 1.854; 95% CI, 1.096–3.138), critical preoperative state (OR, 2.196; 95% CI, 1.209–3.891), and bilateral internal mammary artery grafting (OR, 2.088; 95% CI, 1.422–3.066) were predictors of DSWI (derivation data set). An additive risk score was calculated by assigning 1 point to each of these independent risk factors for DSWI. In the validation data set, the rate of DSWI increased along with the E-CABG DSWI scores (score of 0, 1.0%; score of 1, 1.8%; score of 2, 2.2%; score of 3, 6.9%; score ≥4: 12.1%; P < .0001). Net reclassification improvement, integrated discrimination improvement, and decision curve analysis showed that the E-CABG DSWI score performed better than other risk scores.

DSWI is associated with poor outcome after CABG, and its risk can be stratified using the E-CABG DSWI score.

clinicaltrials.gov identifier: NCT02319083