To characterize residential social vulnerability among healthcare personnel (HCP) and evaluate its association with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection.

Case–control study.

This study analyzed data collected in May–December 2020 through sentinel and population-based surveillance in healthcare facilities in Colorado, Minnesota, New Mexico, New York, and Oregon.

Data from 2,168 HCP (1,571 cases and 597 controls from the same facilities) were analyzed.

HCP residential addresses were linked to the social vulnerability index (SVI) at the census tract level, which represents a ranking of community vulnerability to emergencies based on 15 US Census variables. The primary outcome was SARS-CoV-2 infection, confirmed by positive antigen or real-time reverse-transcriptase– polymerase chain reaction (RT-PCR) test on nasopharyngeal swab. Significant differences by SVI in participant characteristics were assessed using the Fisher exact test. Adjusted odds ratios (aOR) with 95% confidence intervals (CIs) for associations between case status and SVI, controlling for HCP role and patient care activities, were estimated using logistic regression.

Significantly higher proportions of certified nursing assistants (48.0%) and medical assistants (44.1%) resided in high SVI census tracts, compared to registered nurses (15.9%) and physicians (11.6%). HCP cases were more likely than controls to live in high SVI census tracts (aOR, 1.76; 95% CI, 1.37–2.26).

These findings suggest that residing in more socially vulnerable census tracts may be associated with SARS-CoV-2 infection risk among HCP and that residential vulnerability differs by HCP role. Efforts to safeguard the US healthcare workforce and advance health equity should address the social determinants that drive racial, ethnic, and socioeconomic health disparities.

The Society for Healthcare Epidemiology of America (SHEA) is a leading medical society for infection prevention and antibiotic stewardship. This descriptive study evaluated speaker demographics at the annual SHEA Spring conferences from 2019 to 2022.

This was a retrospective, descriptive analysis of the demographic composition of speakers at the annual SHEA Spring conferences between 2019 and 2022, excluding the cancelled 2020 conference. Self-reported demographics were available for gender, race, ethnicity, age, primary practice setting, and professional degrees in speaker and membership categories.

In total, 447 speaker slots were filled by 305 unique speakers over 3 years. Average annual membership included 55.2% female, 44.8% male, 69.3% White, 21.4% Asian, 6.0% Hispanic/Latino, 2.9% Black, and 0.4% American Indian/Alaska Native or Native Hawaiian/Pacific Islander (AIAN/NHPI); 48.9% did not report a race or ethnicity. Speakers during the same period were 63.5% female, 36.5% male, 68.2% White, 13.3% Asian, 3.8% Black, 3.4% Hispanic/Latino, 0.8% AIAN/NHPI; 13.4% did not report race or ethnicity. In 2021, pharmacists represented 11.6% of speakers (and 2.9% of members) and members with nondoctoral degrees represented 11.6% of speakers (and 21.5% of members) (P < .0001). In each year, we detected underrepresentation of community and private-practice speakers relative to membership (eg, in 2022, 4.3% of speakers vs 15.7% of members; P < .05).

The SHEA Spring conferences demonstrated an increase in pharmacist speakers over time, but speakers from community hospitals and with nondoctoral degrees remain underrepresented relative to membership. Racial and ethnic minoritized individuals remain underrepresented as members and speakers. Intentional interventions are needed to consistently achieve equitable speaker representation across multiple demographic groups.

To analyze Clostridioides difficile testing in 3 hospitals in central North Carolina to validate previous racial health-disparity findings.

We completed a retrospective analysis of inpatient C. difficile tests from 2015 to 2021 at 3 university-affiliated hospitals in North Carolina. We calculated the number of C. difficile tests per 1,000 patient days stratified by race: White, Black, and non-White, non-Black (NWNB). We defined a unique C. difficile test as one that occurred in an inpatient unit with a matching laboratory accession ID and on differing calendar days. Tests were evaluated overall, by hospital, by year, and by positivity rate.

In total, 35,160 C. difficile tests and 2,571,850 patient days across all 3 hospitals from 2015 to 2021 were analyzed. The median number of C. difficile tests per 1,000 patient days was 13.85 (interquartile range [IQR], 9.88–16.07). Among all C. difficile tests, 5,225 (15%) were positive. White patients were administered more C. difficile tests (14.46 per 1,000 patient days) than Black patients (12.96; P < .0001) or NWNB race patients (10.27; P < .0001). Black patients were administered more tests than NWNB patients (P < .0001). White patients tested positive at a similar rate to Black patients (15% vs 15%; P = .3655) and higher than NWNB individuals (12%; P = .0061), and Black patients tested positive at a higher rate than NWNB patients (P = .0024).

White patients received more C. difficile tests than Black and NWNB patient groups when controlling for race patient days. Future studies should control for comorbidities and investigate community onset of C. difficile by race and ethnicity.

To assess association of pharmacist gender with acceptance of antibiotic stewardship recommendations.

A retrospective evaluation of the Reducing Overuse of Antibiotics at Discharge (ROAD) Home intervention.

The study was conducted from May to October 2019 in a single academic medical center.

The study included patients receiving antibiotics on a hospitalist service who were nearing discharge.

During the intervention, clinical pharmacists (none who had specialist postgraduate infectious disease residency training) reviewed patients on antibiotics and led an antibiotic timeout (ie, structured conversation) prior to discharge to improve discharge antibiotic prescribing. We assessed the association of pharmacist gender with acceptance of timeout recommendations by hospitalists using logistic regression controlling for patient characteristics.

Over 6 months, pharmacists conducted 295 timeouts: 158 timeouts (53.6%) were conducted by 12 women, 137 (46.4%) were conducted by 8 men. Pharmacists recommended an antibiotic change in 82 timeouts (27.8%), of which 51 (62.2%) were accepted. Compared to male pharmacists, female pharmacists were less likely to recommend a discharge antibiotic change: 30 (19.0%) of 158 versus 52 (38.0%) of 137 (P < .001). Female pharmacists were also less likely to have a recommendation accepted: 10 (33.3%) of 30 versus 41 (8.8%) of 52 (P < .001). Thus, timeouts conducted by female versus male pharmacists were less likely to result in an antibiotic change: 10 (6.3%) of 158 versus 41 (29.9%) of 137 (P < .001). After adjustments, pharmacist gender remained significantly associated with whether recommended changes were accepted (adjusted odds ratio [aOR], 0.10; 95%confidence interval [CI], 0.03–0.36 for female versus male pharmacists).

Antibiotic stewardship recommendations made by female clinical pharmacists were less likely to be accepted by hospitalists. Gender bias may play a role in the acceptance of clinical pharmacist recommendations, which could affect patient care and outcomes.

To investigate associations between healthcare-associated Clostridioides difficile infection and patient demographics at an urban safety-net hospital and compare findings with national surveillance statistics.

Study participants were selected using a case-control design using medical records collected between August 2014 and May 2018 at Hahnemann University Hospital in Philadelphia. Controls were frequency matched to cases by age and length of stay. Final sample included 170 cases and 324 controls. Neighborhood-level factors were measured using American Community Survey data. Multilevel models were used to examine infection by census tract, deprivation index, race/ethnicity, insurance type, referral location, antibiotic use, and proton-pump inhibitor use.

Patients on Medicare compared to private insurance had 2.04 times (95% CI, 1.31–3.20) the odds of infection after adjusting for all covariables. Prior antibiotic use (2.70; 95% CI, 1.64–4.46) was also associated with infection, but race or ethnicity and referral location were not. A smaller proportion of hospital cases occurred among white patients (25% vs 44%) and patients over the age of 65 (39% vs 56%) than expected based on national surveillance statistics.

Medicare and antibiotics were associated with Clostridioides difficile infection, but evidence did not indicate association with race or ethnicity. This finding diverges from national data in that infection is higher among white people compared to nonwhite people. Furthermore, a greater proportion of hospital cases were aged <65 years than expected based on national data. National surveillance statistics on CDI may not be transportable to safety-net hospitals, which often disproportionately serve low-income, nonwhite patients.

To evaluate trends in racial and ethnic disparities in weekly cumulative rates of coronavirus disease 2019 (COVID-19) cases and deaths in Connecticut nursing homes.

Longitudinal analysis of nursing-home COVID-19 reports and other databases. Multivariable negative binomial models were used to estimate disparities in COVID-19 incidence and fatality rates across nursing-home groups with varying proportions of racial and ethnic minority residents, defined as low-, medium-, medium-high-, and high-proportion groups. Trends in such disparities were estimated from week 1 (April 13) to week 10 (ending on June 19, 2020).

The study was conducted across 211 nursing homes.

The average number of cases ranged from 6.1 cases per facility for the low-proportion group to 11.7 cases per facility for the high-proportion group in week 1, and from 26.7 to 58.5 cases per facility in week 10. Compared to the low-proportion group, the adjusted incidence rate ratios (IRRs) for the high-proportion group were 1.18 (95% confidence interval [CI], 0.77–1.80; P > .10) in week 1 and 1.54 (95% CI, 1.05–2.25; P < .05) in week 10, showing a 30% (95% CI, 5%–62%) relative increase (P < .05). The average weekly number of COVID-19–related deaths ranged from 0 to 0.3 deaths per facility for different groups in week 1, and from 7.6 to 13.3 deaths per facility in week 10. Adjusted disparities in fatalities similarly increased over time.

Connecticut nursing homes caring for predominately racial and ethnic minority residents tended to have higher COVID-19 incidence and fatality rates. These across-facility disparities increased during the early periods of the pandemic.

Residents of long-term care facilities face significantly greater risk of contracting or dying from coronavirus disease 2019 (COVID-19). However, little is known about COVID-19 in assisted living communities (ALCs) and the potential determinants of its spread. We examined the association between COVID-19 cases in ALCs and the proportion of Medicare-Medicaid (dual) eligible minority residents, neighborhood area deprivation, and state COVID-19 policy stringency.

We conducted longitudinal analyses employing data on confirmed COVID-19 cases in ALCs in 5 states. We sought to determine the weekly cumulative number of COVID-19 cases in ALCs. Covariates were ALC characteristics, area deprivation index, and state COVID-19 policy stringency. Multivariate 2-part models were used to determine the associations between independent variables and the likelihood of an outbreak and the overall count of cases.

In our study sample, 201 ALCs (7.04%) reported 1 or more COVID-19 cases as of August 17, 2020. A higher percentage of minority residents was associated with an increased likelihood of an ALC reporting at least 1 COVID-19 case (odds ratio [OR], 1.06; P = .032). Conditional on having at least 1 case, ALCs in states with stricter social distancing policies had lower case counts (incidence rate ratio [IRR], 0.98; P < .001). Greater neighborhood deprivation was associated with higher case count (IRR, 1.36; P = .049).

ALCs with higher proportions of dual-eligible minority residents were more likely to have COVID-19 outbreaks within their communities. ALCs located in more socioeconomically deprived neighborhoods, and in states with less stringent state social distancing policies, tended to have more COVID-19 cases.

To examine associations between socioeconomic factors and (1) adherence to methicillin-resistant Staphylococcus aureus (MRSA) posttreatment follow-up swab sampling after 1 and 6 months and (2) successful decolonization treatment.

Cohort study with 2 years of follow-up. Data on patients diagnosed with MRSA were extracted from a regional MRSA database and national registries. We used a cluster-based logistic regression model to estimate the adjusted odds ratios (aOR) and 95% confidence interval (CI) for associations between socioeconomic factors and decolonization treatment.

Danish primary health care.

The rate of adherence to posttreatment follow-up swab sampling among 2,536 cases 1 month after decolonization treatment was 66% (95% CI, 64%–68%), and it decreased to 30% (95% CI, 28%–32%) after 6 months. Living in intermediate municipalities (76–159 inhabitants/km2) or having retired were associated with completed posttreatment follow-up swabs 1 month after decolonization treatment: aOR, 1.40 (95% CI, 1.2–1.74) and aOR, 2.67 (95% CI, 1.16–6.13), respectively. The rate of successful decolonization treatment 2 years after initiating treatment was 36% (95% CI, 34%–38%). Factors associated with successful decolonization treatment included individuals with higher education (aOR, 1.62; 95% CI, 1.22–2.15), early retirees (aOR, 1.63; 95% CI, 1.12–2.38), those living in intermediate municipalities (ie, 160–900+ inhabitants/km2; aOR, 1.35; 95% CI, 1.08–1.68), and those living in predominantly urban municipalities (ie, 160–900+ inhabitants/km2; aOR, 2.04; 95% CI, 1.5–2.76).

Disparities in the effect of decolonization treatment and adherence to MRSA follow-up sampling among MRSA-positive individuals appear to be largely explained by the level of education, area of residence, and employment status.