Assessing the Impact of 2-Step Clostridioides difficile Testing at the Healthcare Facility Level.

BACKGROUND: Two-step testing for Clostridioides difficile infection (CDI) aims to improve diagnostic specificity but may also influence reported epidemiology and patterns of treatment. Some providers fear that 2-step testing may result in adverse outcomes if C. difficile is underdiagnosed. METHODS: Our primary objective was to assess the impact of 2-step testing on reported incidence of hospital-onset CDI (HO-CDI). As secondary objectives, we assessed the impact of 2-step testing on C. difficile-specific antibiotic use and colectomy rates as proxies for harm from underdiagnosis or delayed treatment. This longitudinal cohort study included 2 657 324 patient-days across 8 regional hospitals from July 2017 through March 2022. Impact of 2-step testing was assessed by time series analysis with generalized estimating equation regression models. RESULTS: Two-step testing was associated with a level decrease in HO-CDI incidence (incidence rate ratio, 0.53 [95% confidence interval {CI}, .48-.60]; P < .001), a similar level decrease in utilization rates for oral vancomycin and fidaxomicin (utilization rate ratio, 0.63 [95% CI, .58-.70]; P < .001), and no significant level (rate ratio, 1.16 [95% CI, .93-1.43]; P = .18) or trend (rate ratio, 0.85 [95% CI, .52-1.39]; P = .51) change in emergent colectomy rates. CONCLUSIONS: Two-step testing is associated with decreased reported incidence of HO-CDI, likely by improving diagnostic specificity. The parallel decrease in C. difficile-specific antibiotic use offers indirect reassurance against underdiagnosis of C. difficile infections still requiring treatment by clinician assessment. Similarly, the absence of any significant change in colectomy rates offers indirect reassurance against any rise in fulminant C. difficile requiring surgical management.

Severe acute respiratory syndrome coronavirus 2 environmental contamination in hospital rooms is uncommon using viral culture techniques.

We assessed environmental contamination of inpatient rooms housing coronavirus disease 2019 (COVID-19) patients in a dedicated COVID-19 unit. Contamination with severe acute respiratory syndrome coronavirus 2 was found on 5.5% (19/347) of surfaces via reverse transcriptase polymerase chain reaction and 0.3% (1/347) of surfaces via cell culture. Environmental contamination is uncommon in hospitals rooms; RNA presence is not a specific indicator of infectious virus.

Effects of Thrust Magnitude and Duration on Immediate Postspinal Manipulation Trunk Muscle Spindle Responses.

OBJECTIVE: The purpose of this study was to characterize trunk muscle spindle responses immediately after high-velocity, low-amplitude spinal manipulation (HVLA-SM) delivered at various thrust magnitudes and thrust durations. METHODS: Secondary analysis from multiple studies involving anesthetized adult cats (N = 70; 2.3-6.0 kg) receiving L6 HVLA-SM. Muscle spindle afferent recordings were obtained from L6 dorsal rootlets before, during, and immediately after HVLA-SM. L6 HVLA-SM was delivered posteriorly-to-anteriorly using a feedback motor with peak thrust magnitudes of 25%, 55%, and 85% of cat body weight (BW) and thrust durations of 25, 50, 75, 100, 150, 200, and 250 ms. Time to the first action potential and muscle spindle discharge frequency at 1 and 2 seconds post-HVLA-SM were determined. RESULTS: A significant association between HVLA-SM thrust magnitude and immediate (≤2 s) muscle spindle response was found (P < .001). For non-control thrust magnitude, pairwise comparisons (25%, 55%, 85% BW), 55% BW thrust magnitude had the most consistent effect on immediate post-HVLA-SM discharge outcomes (false discovery rate < 0.05). No significant association was found between thrust duration and immediate post-HVLA-SM muscle spindle response (P > .05). CONCLUSION: The present study found that HVLA-SM thrust magnitudes delivered at 55% BW were more likely to affect immediate (≤2 s) post-HVLA-SM muscle spindle response.

Access to routine care and risks for 30-day readmission in patients with cardiovascular disease.

BACKGROUND: Studies have shown that access to routine medical care is associated with the prevention, diagnosis, and treatment of chronic diseases. However, studies have not examined whether patient-reported difficulties in access to care are associated with rehospitalization in patients with cardiovascular disease. METHODS: Electronic medical records and a standardized survey were used to examine cardiovascular patients admitted to a large medical center from January 1, 2015 through January 10, 2017 (n=520). All-cause readmission within 30 days of discharge was the primary outcome for analysis. Logistic regression models were used to examine the association between access to care and 30-day readmission while adjusting for patient demographics, socioeconomic status, healthcare utilization, and health status. RESULTS: Nearly 1-in-6 patients (15.7%) reported difficulty in accessing routine medical care; and those who were younger, male, non-white, uninsured, with heart failure, and had low social support were significantly more likely to report difficulty. Patients who reported difficulty in accessing care had significantly higher rates of 30-day readmission than patients who did not report difficulty (33.3% vs. 17.9%; P=.001); and the risks remained largely unchanged after accounting for nearly two dozen covariates (unadjusted odds ratio [OR]=2.29; 95% CI, 1.46-3.60 vs. adjusted OR=2.17; 95% CI, 1.29-3.66). Risks for readmission were especially high for patients who reported issues with transportation (OR=3.24; 95% CI, 1.28-8.16) and scheduling appointments (OR=3.56; 95% CI, 1.43-8.84), but not for other reasons (OR=1.47; 95% CI, 0.61-3.54). CONCLUSIONS: Cardiovascular patients who reported difficulty in accessing routine care had substantial risks of readmission within 30 days after discharge. These findings have important implications for identifying high-risk patients and developing interventions to improve access to routine medical care.

Place-Based Initiatives to Improve Health in Disadvantaged Communities: Cross-Sector Characteristics and Networks of Local Actors in North Carolina.

OBJECTIVES: To examine the leadership attributes and collaborative connections of local actors from the health sector and those outside the health sector in a major place-based health initiative. METHODS: We used survey data from 340 individuals in 4 Healthy Places North Carolina counties from 2014 to assess the leadership attributes (awareness, attitudes, and capacity) and network connections of local actors by their organizational sector. RESULTS: Respondents' leadership attributes-scored on 5-point Likert scales-were similar across Healthy Places North Carolina counties. Although local actors reported high levels of awareness and collaboration around community health improvement, we found lower levels of capacity for connecting diversity, identifying barriers, and using resources in new ways to improve community health. Actors outside the health sector had generally lower levels of capacity than actors in the health sector. Those in the health sector exhibited the majority of network ties in their community; however, they were also the most segregated from actors in other sectors. CONCLUSIONS: More capacity building around strategic action-particularly in nonhealth sectors-is needed to support efforts in making widespread changes to community health.

Identification of carbapenem-resistant organism (CRO) contamination of in-room sinks in intensive care units in a new hospital bed tower.

BACKGROUND: The origins and timing of inpatient room sink contamination with carbapenem-resistant organisms (CROs) are poorly understood. METHODS: We performed a prospective observational study to describe the timing, rate, and frequency of CRO contamination of in-room handwashing sinks in 2 intensive care units (ICU) in a newly constructed hospital bed tower. Study units, A and B, were opened to patient care in succession. The patients in unit A were moved to a new unit in the same bed tower, unit B. Each unit was similarly designed with 26 rooms and in-room sinks. Microbiological samples were taken every 4 weeks from 3 locations from each study sink: the top of the bowl, the drain cover, and the p-trap. The primary outcome was sink conversion events (SCEs), defined as CRO contamination of a sink in which CRO had not previously been detected. RESULTS: Sink samples were obtained 22 times from September 2020 to June 2022, giving 1,638 total environmental cultures. In total, 2,814 patients were admitted to study units while sink sampling occurred. We observed 35 SCEs (73%) overall; 9 sinks (41%) in unit A became contaminated with CRO by month 10, and all 26 sinks became contaminated in unit B by month 7. Overall, 299 CRO isolates were recovered; the most common species were Enterobacter cloacae and Pseudomonas aeruginosa. CONCLUSION: CRO contamination of sinks in 2 newly constructed ICUs was rapid and cumulative. Our findings support in-room sinks as reservoirs of CRO and emphasize the need for prevention strategies to mitigate contamination of hands and surfaces from CRO-colonized sinks.

Comparative analysis of sampling and detection methods for fungal contamination on common healthcare environment surface materials.

We evaluated sampling and detection methods for fungal contamination on healthcare surface materials, comparing the efficacy of foam sponges, flocked swabs, and Replicate Organism Detection And Counting (RODAC) plates alongside culture-based quantification and quantitative polymerase chain reaction (qPCR). Findings indicate that sponge sampling and qPCR detection performed best, suggesting a foundation for future studies aiming to surveillance practices for fungi.

CDC's Hospital-Onset Clostridioides difficile Prevention Framework in a Regional Hospital Network.

Importance: Despite modest reductions in the incidence of hospital-onset Clostridioides difficile infection (HO-CDI), CDI remains a leading cause of health care-associated infection. As no single intervention has proven highly effective on its own, a multifaceted approach to controlling HO-CDI is needed. Objective: To assess the effectiveness of the Centers for Disease Control and Prevention's Strategies to Prevent Clostridioides difficile Infection in Acute Care Facilities Framework (hereafter, the Framework) in reducing HO-CDI incidence. Design, Setting, and Participants: This quality improvement study was performed within the Duke Infection Control Outreach Network from July 1, 2019, through March 31, 2022. In all, 20 hospitals in the network participated in an implementation study of the Framework recommendations, and 26 hospitals did not participate and served as controls. The Framework has 39 discrete intervention categories organized into 5 focal areas for CDI prevention: (1) isolation and contact precautions, (2) CDI confirmation, (3) environmental cleaning, (4) infrastructure development, and (5) antimicrobial stewardship engagement. Exposures: Monthly teleconferences supporting Framework implementation for the participating hospitals. Main Outcomes and Measures: Primary outcomes were HO-CDI incidence trends at participating hospitals compared with controls and postintervention HO-CDI incidence at intervention sites compared with rates during the 24 months before the intervention. Results: The study sample included a total of 2184 HO-CDI cases and 7 269 429 patient-days. In the intervention cohort of 20 participating hospitals, there were 1403 HO-CDI cases and 3 513 755 patient-days, with a median (IQR) HO-CDI incidence of 2.8 (2.0-4.3) cases per 10 000 patient-days. The first analysis included an additional 3 755 674 patient-days and 781 HO-CDI cases among the 26 controls, with a median (IQR) HO-CDI incidence of 1.1 (0.7-2.7) case per 10 000 patient-days. The second analysis included an additional 2 538 874 patient-days and 1751 HO-CDI cases, with a median (IQR) HO-CDI incidence of 5.9 (2.7-8.9) cases per 10 000 patient-days, from participating hospitals 24 months before the intervention. In the first analysis, intervention sites had a steeper decline in HO-CDI incidence over time relative to controls (yearly incidence rate ratio [IRR], 0.79 [95% CI, 0.67-0.94]; P = .01), but the decline was not temporally associated with study participation. In the second analysis, HO-CDI incidence was declining in participating hospitals before the intervention, and the rate of decline did not change during the intervention. The degree to which hospitals implemented the Framework was associated with steeper declines in HO-CDI incidence (yearly IRR, 0.95 [95% CI, 0.90-0.99]; P = .03). Conclusions and Relevance: In this quality improvement study of a regional hospital network, implementation of the Framework was not temporally associated with declining HO-CDI incidence. Further study of the effectiveness of multimodal prevention measures for controlling HO-CDI is warranted.

Impact of measurement and feedback on chlorhexidine gluconate bathing among intensive care unit patients: A multicenter study.

OBJECTIVE: To assess whether measurement and feedback of chlorhexidine gluconate (CHG) skin concentrations can improve CHG bathing practice across multiple intensive care units (ICUs). DESIGN: A before-and-after quality improvement study measuring patient CHG skin concentrations during 6 point-prevalence surveys (3 surveys each during baseline and intervention periods). SETTING: The study was conducted across 7 geographically diverse ICUs with routine CHG bathing. PARTICIPANTS: Adult patients in the medical ICU. METHODS: CHG skin concentrations were measured at the neck, axilla, and inguinal region using a semiquantitative colorimetric assay. Aggregate unit-level CHG skin concentration measurements from the baseline period and each intervention period survey were reported back to ICU leadership, which then used routine education and quality improvement activities to improve CHG bathing practice. We used multilevel linear models to assess the impact of intervention on CHG skin concentrations. RESULTS: We enrolled 681 (93%) of 736 eligible patients; 92% received a CHG bath prior to survey. At baseline, CHG skin concentrations were lowest on the neck, compared to axillary or inguinal regions (P < .001). CHG was not detected on 33% of necks, 19% of axillae, and 18% of inguinal regions (P < .001 for differences in body sites). During the intervention period, ICUs that used CHG-impregnated cloths had a 3-fold increase in patient CHG skin concentrations as compared to baseline (P < .001). CONCLUSIONS: Routine CHG bathing performance in the ICU varied across multiple hospitals. Measurement and feedback of CHG skin concentrations can be an important tool to improve CHG bathing practice.

Investigating Risk Factors for Urine Culture Contamination in Outpatient Clinics: A New Avenue for Diagnostic Stewardship.

Mixed flora in urine cultures usually occur due to pre-analytic contamination. In our outpatient urology clinic, we found a high prevalence of mixed flora (46.2%), which was associated with female sex and older age. Patient education did not impact the rate of mixed flora. Future efforts should target high-risk patients.

The Impact of Infection Versus Colonization on Clostridioides difficile Environmental Contamination in Hospitalized Patients With Diarrhea.

Background: Patients with Clostridioides difficile infections (CDIs) contaminate the healthcare environment; however, the relative contribution of contamination by colonized individuals is unknown. Current guidelines do not recommend the use of contact precautions for asymptomatic C difficile carriers. We evaluated C difficile environmental contamination in rooms housing adult inpatients with diarrhea based on C difficile status. Methods: We performed a prospective cohort study of inpatient adults with diarrhea who underwent testing for CDI via polymerase chain reaction (PCR) and enzyme immunoassay (EIA). Patients were stratified into cohorts based on test result: infected (PCR+/EIA+), colonized (PCR+/EIA-), or negative/control (PCR-). Environmental microbiological samples were taken within 24 hours of C difficile testing and again for 2 successive days. Samples were obtained from the patient, bathroom, and care areas. Results: We enrolled 94 patients between November 2019 and June 2021. Clostridioides difficile was recovered in 93 (38%) patient rooms: 44 (62%) infected patient rooms, 35 (43%) colonized patient rooms (P = .08 vs infected 38 patient rooms), and 14 (15%) negative patient rooms (P < .01 vs infected; P < .01 vs colonized). Clostridioides difficile was recovered in 40 (56%), 6 (9%), and 20 (28%) of bathrooms, care areas and patient areas in 40 infected patient rooms; 34 (41%), 1 (1%), and 4 (5%) samples in colonized patient rooms; and 12 (13%), 1 (1%), and 3 (3%) of samples in negative patient rooms, respectively. Conclusions: Patients colonized with C difficile frequently contaminated the hospital environment. Our data support the use of contact precautions when entering rooms of patients colonized with C difficile, especially when entering the bathroom.

Development of a Machine Learning Model Using Electronic Health Record Data to Identify Antibiotic Use Among Hospitalized Patients.

Importance: Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve comparisons for antimicrobial stewardship assessments. Objective: To evaluate whether variables of varying complexity and feasibility of measurement, derived retrospectively from the electronic health records, accurately identify inpatient antimicrobial use. Design, Setting, and Participants: Retrospective cohort study, using a 2-stage random forests machine learning modeling analysis of electronic health record data. Data were split into training and testing sets to measure model performance using area under the curve and absolute error. All adult and pediatric inpatient encounters from October 1, 2015, to September 30, 2017, at 2 community hospitals and 1 academic medical center in the Duke University Health System were analyzed. A total of 204 candidate variables were categorized into 4 tiers based on feasibility of measurement from the electronic health records. Main Outcomes and Measures: Antimicrobial exposure was measured at the encounter level in 2 ways: binary (ever or never) and number of days of therapy. Analyses were stratified by age (pediatric or adult), unit type, and antibiotic group. Results: The data set included 170 294 encounters and 204 candidate variables from 3 hospitals during the 3-year study period. Antimicrobial exposure occurred in 80 190 encounters (47%); 64 998 (38%) received 1 to 6 days of therapy, and 15 192 (9%) received 7 or more days of therapy. Two-stage models identified antimicrobial use with high fidelity (mean area under the curve, 0.85; mean absolute error, 1.0 days of therapy). Addition of more complex variables increased accuracy, with largest improvements occurring with inclusion of diagnosis information. Accuracy varied based on location and antibiotic group. Models underestimated the number of days of therapy of encounters with long lengths of stay. Conclusions and Relevance: Models using variables derived from electronic health records identified antimicrobial exposure accurately. Future risk-adjustment strategies incorporating encounter-level information may make comparisons of antimicrobial use more meaningful for hospital antimicrobial stewardship assessments.

Impact of preoperative chlorhexidine gluconate (CHG) application methods on preoperative CHG skin concentration.

Elective surgical patients routinely bathe with chlorhexidine gluconate (CHG) at home days prior to their procedures. However, the impact of home CHG bathing on surgical site CHG concentration is unclear. We examined 3 different methods of applying CHG and hypothesized that different application methods would impact resulting CHG skin concentration.

Socioeconomic, Psychosocial and Behavioral Characteristics of Patients Hospitalized With Cardiovascular Disease.

BACKGROUND: Recent studies have drawn attention to nonclinical factors to better understand disparities in the development, treatment and prognosis of patients with cardiovascular disease. However, there has been limited research describing the nonclinical characteristics of patients hospitalized for cardiovascular care. METHODS: Data for this study come from 520 patients admitted to the Duke Heart Center from January 1, 2015 through January 10, 2017. Electronic medical records and a standardized survey administered before discharge were used to ascertain detailed information on patients' demographic (age, sex, race, marital status and living arrangement), socioeconomic (education, employment and health insurance), psychosocial (health literacy, health self-efficacy, social support, stress and depressive symptoms) and behavioral (smoking, drinking and medication adherence) attributes. RESULTS: Study participants were of a median age of 65 years, predominantly male (61.4%), non-Hispanic white (67.1%), hospitalized for 5.11 days and comparable to all patients admitted during this period. Results from the survey showed significant heterogeneity among patients in their demographic, socioeconomic and behavioral characteristics. We also found that the patients' levels of psychosocial risks and resources were significantly associated with many of these nonclinical characteristics. Patients who were older, women, nonwhite and unmarried had generally lower levels of health literacy, self-efficacy and social support, and higher levels of stress and depressive symptoms than their counterparts. CONCLUSIONS: Patients hospitalized with cardiovascular disease have diverse nonclinical profiles that have important implications for targeting interventions. A better understanding of these characteristics will enhance the personalized delivery of care and improve outcomes in vulnerable patient groups.

Identifying Nonclinical Factors Associated With 30-Day Readmission in Patients with Cardiovascular Disease: Protocol for an Observational Study.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of hospitalization in older adults and high readmission rates have attracted considerable attention as actionable targets to promote efficiency in care and to reduce costs. Despite a plethora of research over the past decade, current strategies to predict readmissions have been largely ineffective and efforts to identify novel clinical predictors have been largely unsuccessful. OBJECTIVE: The objective of this study is to examine a wide array of socioeconomic, psychosocial, behavioral, and clinical factors to predict risks of 30-day hospital readmission in cardiovascular patients. METHODS: The study includes patients (aged 18 years and older) admitted for the treatment of cardiovascular-related illnesses at the Duke Heart Center, which is among the nation's largest and top-ranked cardiovascular care hospitals. The study uses a novel standardized survey to ascertain data on a comprehensive array of patient characteristics that will be linked to their electronic medical records. A series of univariate and multivariate models will be used to estimate the associations between the patient-level factors and 30-day readmissions. The performance of the risk models will be examined based on 2 components of accuracy-model calibration and discrimination-to determine how closely the predicted outcome agrees with the observed (actual) outcome and how well the model distinguishes patients who were readmitted and those who were not. The purpose of this paper is to present the protocol for the implementation of this study. RESULTS: The study was launched in February 2014 and is actively recruiting patients from the Heart Center. Approximately 550 patients have been enrolled to date and the study is expected to continue recruitment until February 2018. Preliminary results show that participants in the study were aged 63.6 years on average (SD 14.0), predominately male (61.2%), and primarily non-Hispanic white (64.6%) or non-Hispanic black (31.7%). The demographic characteristics of study participants were not significantly different from all patients admitted to the Heart Center during this period with an average age of 65.0 years (SD 15.3) and predominately male (58.6%), non-Hispanic white (62.9%) or non-Hispanic black (31.8%) The integration of the interview data with clinical data from the patient electronic medical records is currently underway. The study has received funding and ethical approval. CONCLUSIONS: Many US hospitals continue to struggle with high readmission rates in patients with cardiovascular disease. The primary objective of this study is to collect and integrate a comprehensive array of patient attributes to develop a powerful yet parsimonious model to stratify risks of rehospitalization in cardiovascular patients. The results of this research also have the potential to identify actionable targets for tailored interventions to improve patient outcomes.

Marital history and survival after a heart attack.

Heart disease is the leading cause of death in the United States and nearly one million Americans will have a heart attack this year. Although the risks associated with a heart attack are well established, we know surprisingly little about how marital factors contribute to survival in adults afflicted with heart disease. This study uses a life course perspective and longitudinal data from the Health and Retirement Study to examine how various dimensions of marital life influence survival in U.S. older adults who suffered a heart attack (n = 2197). We found that adults who were never married (odds ratio [OR] = 1.73), currently divorced (OR = 1.70), or widowed (OR = 1.34) were at significantly greater risk of dying after a heart attack than adults who were continuously married; and the risks were not uniform over time. We also found that the risk of dying increased by 12% for every additional marital loss and decreased by 7% for every one-tenth increase in the proportion of years married. After accounting for more than a dozen socioeconomic, psychosocial, behavioral, and physiological factors, we found that current marital status remained the most robust indicator of survival following a heart attack. The implications of the findings are discussed in the context of life course inequalities in chronic disease and directions for future research.