Surveillance of non–ventilator-associated hospital-acquired pneumonia (NV-HAP) is complicated by subjectivity and variability in diagnosing pneumonia. We compared a fully automatable surveillance definition using routine electronic health record data to manual determinations of NV-HAP according to surveillance criteria and clinical diagnoses.

We retrospectively applied an electronic surveillance definition for NV-HAP to all adults admitted to Veterans’ Affairs (VA) hospitals from January 1, 2015, to November 30, 2020. We randomly selected 250 hospitalizations meeting NV-HAP surveillance criteria for independent review by 2 clinicians and calculated the percent of hospitalizations with (1) clinical deterioration, (2) CDC National Healthcare Safety Network (CDC-NHSN) criteria, (3) NV-HAP according to a reviewer, (4) NV-HAP according to a treating clinician, (5) pneumonia diagnosis in discharge summary; and (6) discharge diagnosis codes for HAP. We assessed interrater reliability by calculating simple agreement and the Cohen κ (kappa).

Among 3.1 million hospitalizations, 14,023 met NV-HAP electronic surveillance criteria. Among reviewed cases, 98% had a confirmed clinical deterioration; 67% met CDC-NHSN criteria; 71% had NV-HAP according to a reviewer; 60% had NV-HAP according to a treating clinician; 49% had a discharge summary diagnosis of pneumonia; and 82% had NV-HAP according to any definition according to at least 1 reviewer. Only 8% had diagnosis codes for HAP. Interrater agreement was 75% (κ = 0.50) for CDC-NHSN criteria and 78% (κ = 0.55) for reviewer diagnosis of NV-HAP.

Electronic NV-HAP surveillance criteria correlated moderately with existing manual surveillance criteria. Reviewer variability for all manual assessments was high. Electronic surveillance using clinical data may therefore allow for more consistent and efficient surveillance with similar accuracy compared to manual assessments or diagnosis codes.

To examine the impact of commonly used case definitions for coronavirus disease 2019 (COVID-19) hospitalizations on case counts and outcomes.

Retrospective analysis of all adults hospitalized between March 1, 2020, and March 1, 2022, at 5 Massachusetts acute-care hospitals.

We applied 6 commonly used definitions of COVID-19 hospitalization: positive severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) assay within 14 days of admission, PCR plus dexamethasone administration, PCR plus remdesivir, PCR plus hypoxemia, institutional COVID-19 flag, or COVID-19 International Classification of Disease, Tenth Revision (ICD-10) codes. Outcomes included case counts and in-hospital mortality. Overall, 100 PCR-positive cases were reviewed to determine each definition’s accuracy for distinguishing primary or contributing versus incidental COVID-19 hospitalizations.

Of 306,387 hospital encounters, 15,436 (5.0%) met the PCR-based definition. COVID-19 hospitalization counts varied substantially between definitions: 4,628 (1.5% of all encounters) for PCR plus dexamethasone, 5,757 (1.9%) for PCR plus remdesivir, 11,801 (3.9%) for PCR plus hypoxemia, 15,673 (5.1%) for institutional flags, and 15,868 (5.2%) for ICD-10 codes. Definitions requiring dexamethasone, hypoxemia, or remdesivir selected sicker patients compared to PCR alone (mortality rates 12.2%, 10.7%, and 8.8% vs 8.3%, respectively). Definitions requiring PCR plus remdesivir or dexamethasone did not detect a reduction in in-hospital mortality associated with the SARS-CoV-2 Omicron variant. ICD-10 codes had the highest sensitivity (98.4%) but low specificity (39.5%) for distinguishing primary or contributing versus incidental COVID-19 hospitalizations. PCR plus dexamethasone had the highest specificity (92.1%) but low sensitivity (35.5%).

Commonly used definitions for COVID-19 hospitalizations generate variable case counts and outcomes and differentiate poorly between primary or contributing versus incidental COVID-19 hospitalizations. Surveillance definitions that better capture and delineate COVID-19–associated hospitalizations are needed.

To determine change in rates of postoperative pneumonia and ventilator-associated pneumonia among patients hospitalized in the United States during 2009–2019.

Retrospective cohort study.

Patients hospitalized for major surgical procedures, acute myocardial infarction, heart failure, and pneumonia.

We conducted a retrospective review of data from the Medicare Patient Safety Monitoring System, a chart-abstraction–derived database including 21 adverse-event measures among patients hospitalized in the United States. Changes in observed and risk-adjusted rates of postoperative pneumonia and ventilator-associated pneumonia were derived.

Among 58,618 patients undergoing major surgical procedures between 2009 and 2019, the observed rate of postoperative pneumonia from 2009–2011 was 1.9% and decreased to 1.3% during 2017–2019. The adjusted annual risk each year, compared to the prior year, was 0.94 (95% CI, 0.92–0.96). Among 4,007 patients hospitalized for any of these 4 conditions at risk for ventilator-associated pneumonia during 2009–2019, we did not detect a significant change in observed or adjusted rates. Observed rates clustered around 10%, and adjusted annual risk compared to the prior year was 0.99 (95% CI, 0.95–1.02).

During 2009–2019, the rate of postoperative pneumonia decreased statistically and clinically significantly in among patients hospitalized for major surgical procedures in the United States, but rates of ventilator-associated pneumonia among patients hospitalized for major surgical procedures, acute myocardial infarction, heart failure, and pneumonia did not change.

To assess coronavirus disease 2019 (COVID-19) infection policies at leading US medical centers in the context of the initial wave of the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) omicron variant.

Electronic survey study eliciting hospital policies on masking, personal protective equipment, cohorting, airborne-infection isolation rooms (AIIRs), portable HEPA filters, and patient and employee testing.

“Hospital epidemiologists from U.S. News top 20 hospitals and 10 hospitals in the CDC Prevention Epicenters program.”  As it is currently written, it implies all 30 hospitals are from the CDC Prevention Epicenters program, but that only applies to 10 hospitals.  Alternatively, we could just say “Hospital epidemiologists from 30 leading US hospitals.”

Survey results were reported using descriptive statistics.

Of 30 hospital epidemiologists surveyed, 23 (77%) completed the survey between February 15 and March 3, 2022. Among the responding hospitals, 18 (78%) used medical masks for universal masking and 5 (22%) used N95 respirators. 16 hospitals (70%) required universal eye protection. 22 hospitals (96%) used N95s for routine COVID-19 care and 1 (4%) reserved N95s for aerosol-generating procedures. 2 responding hospitals (9%) utilized dedicated COVID-19 wards; 8 (35%) used mixed COVID-19 and non–COVID-19 units; and 13 (57%) used both dedicated and mixed units. 4 hospitals (17%) used AIIRs for all COVID-19 patients, 10 (43%) prioritized AIIRs for aerosol-generating procedures, 3 (13%) used alternate risk-stratification criteria (not based on aerosol-generating procedures), and 6 (26%) did not routinely use AIIRs. 9 hospitals (39%) did not use portable HEPA filters, but 14 (61%) used them for various indications, most commonly as substitutes for AIIRs when unavailable or for specific high-risk areas or situations. 21 hospitals (91%) tested asymptomatic patients on admission, but postadmission testing strategies and preferred specimen sites varied substantially. 5 hospitals (22%) required regular testing of unvaccinated employees and 1 hospital (4%) reported mandatory weekly testing even for vaccinated employees during the SARS-CoV-2 omicron surge.

COVID-19 infection control practices in leading hospitals vary substantially. Clearer public health guidance and transparency around hospital policies may facilitate more consistent national standards.

To investigate the effectiveness of a daily attestation system used by employees of a multi-institutional academic medical center, which comprised of symptom-screening, self-referrals to the Occupational Health Services team, and/or a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) test.

We conducted a retrospective cohort study of all employee attestations and SARS-CoV-2 tests performed between March and June 2020.

A large multi-institutional academic medical center, including both inpatient and ambulatory settings.

All employees who worked at the study site.

Data were combined from the attestation system (COVIDPass), the employee database, and the electronic health records and were analyzed using descriptive statistics including χ2, Wilcoxon, and Kruskal-Wallis tests. We investigated whether an association existed between symptomatic attestations by the employees and the employee testing positive for SARS-CoV-2.

After data linkage and cleaning, there were 2,117,298 attestations submitted by 65,422 employees between March and June 2020. Most attestations were asymptomatic (99.9%). The most commonly reported symptoms were sore throat (n = 910), runny nose (n = 637), and cough (n = 570). Among the 2,026 employees who ever attested that they were symptomatic, 905 employees were tested within 14 days of a symptomatic attestation, and 114 (13%) of these tests were positive. The most common symptoms associated with a positive SARS-CoV-2 test were anosmia (23% vs 4%) and fever (46% vs 19%).

Daily symptom attestations among healthcare workers identified a handful of employees with COVID-19. Although the number of positive tests was low, attestations may help keep unwell employees off campus to prevent transmissions.

Early administration of antibiotics in sepsis is associated with improved patient outcomes, but safe and generalizable approaches to de-escalate or discontinue antibiotics after suspected sepsis events are unknown.

We used a modified Delphi approach to identify safety criteria for an opt-out protocol to guide de-escalation or discontinuation of antibiotic therapy after 72 hours in non-ICU patients with suspected sepsis. An expert panel with expertise in antimicrobial stewardship and hospital epidemiology rated 48 unique criteria across 3 electronic survey rating tools. Criteria were rated primarily based on their impact on patient safety and feasibility for extraction from electronic health record review. The 48 unique criteria were rated by anonymous electronic survey tools, and the results were fed back to the expert panel participants. Consensus was achieved to either retain or remove each criterion.

After 3 rounds, 22 unique criteria remained as part of the opt-out safety checklist. These criteria included high-risk comorbidities, signs of severe illness, lack of cultures during sepsis work-up or antibiotic use prior to blood cultures, or ongoing signs and symptoms of infection.

The modified Delphi approach is a useful method to achieve expert-level consensus in the absence of evidence suifficient to provide validated guidance. The Delphi approach allowed for flexibility in development of an opt-out trial protocol for sepsis antibiotic de-escalation. The utility of this protocol should be evaluated in a randomized controlled trial.

Evidence from pandemics suggests that influenza is often associated with bacterial coinfection. Among patients hospitalized for influenza pneumonia, we report the rate of coinfection and distribution of pathogens, and we compare outcomes of patients with and without bacterial coinfection.

We included adults admitted with community-acquired pneumonia (CAP) and tested for influenza from 2010 to 2015 at 179 US hospitals participating in the Premier database. Pneumonia was identified using an International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) algorithm. We used multiple logistic and gamma-generalized linear mixed models to assess the relationships between coinfection and inpatient mortality, intensive care unit (ICU) admission, length of stay, and cost.

Among 38,665 patients hospitalized with CAP and tested for influenza, 4,313 (11.2%) were positive. In the first 3 hospital days, patients with influenza were less likely than those without to have a positive culture (10.3% vs 16.2%; P < .001), and cultures were more likely to contain Staphylococcus aureus (34.2% vs 28.2%; P = .007) and less likely to contain Streptococcus pneumoniae (24.9% vs 31.0%; P = .008). Of S. aureus isolates, 42.8% were methicillin resistant among influenza patients versus 53.2% among those without influenza (P = .01). After hospital day 3, pathogens for both groups were similar. Bacterial coinfection was associated with increased odds of in-hospital mortality (aOR, 3.00; 95% CI, 2.17–4.16), late ICU transfer (aOR, 2.83; 95% CI, 1.98–4.04), and higher cost (risk-adjusted mean multiplier, 1.77; 95% CI, 1.59–1.96).

In a large US inpatient sample hospitalized with influenza and CAP, S. aureus was the most frequent cause of bacterial coinfection. Coinfection was associated with worse outcomes and higher costs.