Epidemiology of Clostridioides difficile infection at one hospital 10 years after an outbreak of the epidemic C. difficile strain BI/027: changing strain prevalence, antimicrobial susceptibilities, and patient antibiotic exposures.

In contrast to the epidemiology 10 years earlier at our hospital when the epidemic restriction endonuclease analysis (REA) group strain BI accounted for 72% of Clostridioides difficile isolates recovered from first-episode C. difficile infection (CDI) cases, BI represented 19% of first-episode CDI isolates in 2013-2015. Two additional REA group strains accounted for 31% of isolates (Y, 16%; DH, 12%). High-level resistance to fluoroquinolones and azithromycin was more common among BI isolates than among DH, Y, and non-BI/DH/Y isolates. Multivariable analysis revealed that BI cases were 2.47 times more likely to be associated with fluoroquinolone exposure compared to non-BI cases (95% confidence interval [CI]: 1.12-5.46). In addition, the odds of developing a CDI after third- or fourth-generation cephalosporin exposure was 2.83 times for DH cases than for non-DH cases (95% CI: 1.06-7.54). Fluoroquinolone use in the hospital decreased from 2005 to 2015 from a peak of 113 to a low of 56 antimicrobial days/1,000 patient days. In contrast, cephalosporin use increased from 42 to 81 antimicrobial days/1,000 patient days. These changes correlated with a decrease in geometric mean MIC for ciprofloxacin (61.03 to 42.65 mg/L, P = 0.02) and an increase in geometric mean MIC for ceftriaxone (40.87 to 86.14 mg/L, P < 0.01) among BI isolates. The BI strain remained resistant to fluoroquinolones, but an overall decrease in fluoroquinolone use and increase in cephalosporin use were associated with a decrease in the prevalence of BI, an increased diversity of C. difficile strain types, and the emergence of strains DH and Y.

Automating detection of diagnostic error of infectious diseases using machine learning.

Diagnostic error, a cause of substantial morbidity and mortality, is largely discovered and evaluated through self-report and manual review, which is costly and not suitable to real-time intervention. Opportunities exist to leverage electronic health record data for automated detection of potential misdiagnosis, executed at scale and generalized across diseases. We propose a novel automated approach to identifying diagnostic divergence considering both diagnosis and risk of mortality. Our objective was to identify cases of emergency department infectious disease misdiagnoses by measuring the deviation between predicted diagnosis and documented diagnosis, weighted by mortality. Two machine learning models were trained for prediction of infectious disease and mortality using the first 24h of data. Charts were manually reviewed by clinicians to determine whether there could have been a more correct or timely diagnosis. The proposed approach was validated against manual reviews and compared using the Spearman rank correlation. We analyzed 6.5 million ED visits and over 700 million associated clinical features from over one hundred emergency departments. The testing set performances of the infectious disease (Macro F1 = 86.7, AUROC 90.6 to 94.7) and mortality model (Macro F1 = 97.6, AUROC 89.1 to 89.1) were in expected ranges. Human reviews and the proposed automated metric demonstrated positive correlations ranging from 0.231 to 0.358. The proposed approach for diagnostic deviation shows promise as a potential tool for clinicians to find diagnostic errors. Given the vast number of clinical features used in this analysis, further improvements likely need to either take greater account of data structure (what occurs before when) or involve natural language processing. Further work is needed to explain the potential reasons for divergence and to refine and validate the approach for implementation in real-world settings.

Automatic Extraction of Skin and Soft Tissue Infection Status from Clinical Notes.

The reliable identification of skin and soft tissue infections (SSTIs) from electronic health records is important for a number of applications, including quality improvement, clinical guideline construction, and epidemiological analysis. However, in the United States, types of SSTIs (e.g. is the infection purulent or non-purulent?) are not captured reliably in structured clinical data. With this work, we trained and evaluated a rule-based clinical natural language processing system using 6,576 manually annotated clinical notes derived from the United States Veterans Health Administration (VA) with the goal of automatically extracting and classifying SSTI subtypes from clinical notes. The trained system achieved mention- and document-level performance metrics of the range 0.39 to 0.80 for mention level classification and 0.49 to 0.98 for document level classification.

Veterans and Nonveterans Coping With Stress During 4 Months of COVID-19.

PURPOSE: Identifying how people have been coping with stress during the COVID-19 pandemic allows us to anticipate how the population may react to similar stressors over time. In this study, we assessed patterns of coping styles among veterans and nonveterans, and stability and change in these strategies at 3 time points during the pandemic. METHODS: Using an online survey platform, we circulated a questionnaire at 3 time points during the period when COVID-19 vaccines became widely available (December 2-27, 2020; January 21-February 6, 2021; and March 8-23, 2021). The questionnaire asked participants about their extent of use of 11 coping strategies, and symptoms of anxiety and depression. RESULTS: A total of 2,085 participants (50.8% veterans) completed the questionnaire at 1 or more time points and 930 participants (62.8% veterans) completed it at all 3 time points. Cluster analysis identified 3 distinct coping styles: adaptive, distressed, and disengaged. Compared with nonveterans, veterans more commonly had adaptive and disengaged coping styles, and less commonly had a distressed coping style. The majority of the cohort (71.3%) changed coping style at least once during the study period. Participants who used the same coping style across all 3 time points reported lower levels of anxiety and depression. CONCLUSIONS: Our data demonstrate a need to better understand the dynamic nature of coping with pandemic-level stressors across time. We did not find patterns of change in coping styles, but our findings point to potential advantages of stability in coping style. It is possible that less adaptive styles that are more stable may be advantageous for mental health. This research has implications for supporting patients dealing with stress in family medicine.

Telehealth Use During the COVID-19 Pandemic Among Veterans and Nonveterans: Web-Based Survey Study.

BACKGROUND: In the first year of the COVID-19 pandemic, studies reported delays in health care usage due to safety concerns. Delays in care may result in increased morbidity and mortality from otherwise treatable conditions. Telehealth provides a safe alternative for patients to receive care when other circumstances make in-person care unavailable or unsafe, but information on patient experiences is limited. Understanding which people are more or less likely to use telehealth and their experiences can help tailor outreach efforts to maximize the impact of telehealth. OBJECTIVE: This study aims to examine the characteristics of telehealth users and nonusers and their reported experiences among veteran and nonveteran respondents. METHODS: A nationwide web-based survey of current behaviors and health care experiences was conducted in December 2020-March 2021. The survey consisted of 3 waves, and the first wave is assessed here. Respondents included US adults participating in Qualtrics web-based panels. Primary outcomes were self-reported telehealth use and number of telehealth visits. The analysis used a 2-part regression model examining the association between telehealth use and the number of visits with respondent characteristics. RESULTS: There were 2085 participants in the first wave, and 898 (43.1%) reported using telehealth since the pandemic began. Most veterans who used telehealth reported much or somewhat preferring an in-person visit (336/474, 70.9%), while slightly less than half of nonveterans (189/424, 44.6%) reported this preference. While there was no significant difference between veteran and nonveteran likelihood of using telehealth (odds ratio [OR] 1.33, 95% CI 0.97-1.82), veterans were likely to have more visits when they did use it (incidence rate ratio [IRR] 1.49, 95% CI 1.07-2.07). Individuals were less likely to use telehealth and reported fewer visits if they were 55 years and older (OR 0.39, 95% CI 0.25-0.62 for ages 55-64 years; IRR 0.43, 95% CI 0.28-0.66) or lived in a small city (OR 0.63, 95% CI 0.43-0.92; IRR 0.71, 95% CI 0.51-0.99). Receiving health care partly or primarily at the Veterans Health Administration (VA) was associated with telehealth use (primarily VA: OR 3.25, 95% CI 2.20-4.81; equal mix: OR 2.18, 95% CI 1.40-3.39) and more telehealth visits (primarily VA: IRR 1.5, 95% CI 1.10-2.04; equal mix: IRR 1.57, 95% CI 1.11-2.24). CONCLUSIONS: Telehealth will likely continue to be an important source of health care for patients, especially following situations like the COVID-19 pandemic. Some groups who may benefit from telehealth are still underserved. Telehealth services and outreach should be improved to provide accessible care for all.

Somatostatin slows Aß plaque deposition in aged APPNL-F/NL-F mice by blocking Aß aggregation.

The neuroendocrine peptide somatostatin (SST) has long been thought of as influencing the deposition of the amyloid ß peptide (Aß) in Alzheimer's disease (AD). Missing have been in vivo data in a relevant Aß amyloidosis model. Here we crossed AppNL-F/NL-F mice with Sst-deficient mice to assess if and how the presence of Sst influences pathological hallmarks of Aß amyloidosis. We found that Sst had no influence on whole brain neprilysin transcript, protein or activity levels, an observation that cannot be accounted for by a compensatory upregulation of the Sst paralog, cortistatin (Cort), that we observed in 15-month-old Sst-deficient mice. Sst-deficiency led to a subtle but significant increase in the density of cortical Aß amyloid plaques. Follow-on western blot analyses of whole brain extracts indicated that Sst interferes with early steps of Aß assembly that manifest in the appearance of SDS-stable smears of 55-150 kDa in Sst null brain samples. As expected, no effect of Sst on tau steady-state levels or its phosphorylation were observed. Results from this study are easier reconciled with an emerging body of data that point toward Sst affecting Aß amyloid plaque formation through direct interference with Aß aggregation rather than through its effects on neprilysin expression.

Misrepresentation and Nonadherence Regarding COVID-19 Public Health Measures.

Importance: The effectiveness of public health measures implemented to mitigate the spread and impact of SARS-CoV-2 relies heavily on honesty and adherence from the general public. Objective: To examine the frequency of, reasons for, and factors associated with misrepresentation and nonadherence regarding COVID-19 public health measures. Design, Setting, and Participants: This survey study recruited a national, nonprobability sample of US adults to participate in an online survey using Qualtrics online panels (participation rate, 1811 of 2260 [80.1%]) from December 8 to 23, 2021. The survey contained screening questions to allow for a targeted sample of one-third who had had COVID-19, one-third who had not had COVID-19 and were vaccinated, and one-third who had not had COVID-19 and were unvaccinated. Main Outcomes and Measures: The survey assessed 9 different types of misrepresentation and nonadherence related to COVID-19 public health measures and the reasons underlying such behaviors. Additional questions measured COVID-19-related beliefs and behaviors and demographic characteristics. Results: The final sample included 1733 participants. The mean (SD) participant age was 41 (15) years and the sample predominantly identified as female (1143 of 1732 [66.0%]) and non-Hispanic White (1151 of 1733 [66.4%]). Seven hundred twenty-one participants (41.6%) reported misrepresentation and/or nonadherence in at least 1 of the 9 items; telling someone they were with or about to be with in person that they were taking more COVID-19 preventive measures than they actually were (420 of 1726 [24.3%]) and breaking quarantine rules (190 of 845 [22.5%]) were the most common manifestations. The most commonly endorsed reasons included wanting life to feel normal and wanting to exercise personal freedom. All age groups younger than 60 years (eg, odds ratio for those aged 18-29 years, 4.87 [95% CI, 3.27-7.34]) and those who had greater distrust in science (odds ratio, 1.14 [95% CI, 1.05-1.23]) had significantly higher odds of misrepresentation and/or nonadherence for at least 1 of the 9 items. Conclusions and Relevance: In this survey study of US adults, nearly half of participants reported misrepresentation and/or nonadherence regarding public health measures against COVID-19. Future work is needed to examine strategies for communicating the consequences of misrepresentation and nonadherence and to address contributing factors.

Incidence of Dermatomyositis in a Nationwide Cohort Study of US Veterans.

This cohort study evaluates the incidence of dermatomyositis and its trend over time in the US Department of Veterans Affairs health care system.

Oral Emergency Contraception Provision in the Veterans Health Administration: a Retrospective Cohort Study.

BACKGROUND: In the USA, oral emergency contraception (EC) use to prevent unintended pregnancy is increasing. Oral EC methods include levonorgestrel (LNG) and ulipristal acetate (UPA), with increased UPA efficacy over LNG in high BMI users and those beyond 3 days post intercourse. The Veterans Health Administration (VHA) provides oral EC at low or no cost, yet prescription-level Veteran data are lacking. OBJECTIVE: To describe oral EC provision in VHA, including method type and Veteran user and prescriber characteristics. DESIGN: A retrospective cohort study using VHA administrative data. PARTICIPANTS: All VHA oral EC prescriptions from January 1, 2016, to December 31, 2020. MAIN MEASURES: We linked Veteran-level sociodemographic and military characteristics and provider-level data with each prescription to identify variables associated with oral EC method. KEY RESULTS: A total of 4280 EC prescriptions (85% LNG) occurred for 3120 unique Veterans over 5 years. While prescriptions remained low annually, the proportion of UPA prescriptions increased from 12 to 19%. Compared to LNG users, UPA users were older (34% vs 25% over age 35 years, p <0.001); more likely to identify as white (57% vs 46%) and non-Hispanic (84% vs 79%) (p <0.001); and more likely to have a BMI ≥ 25 (76% vs 67%, p <0.001). UPA prescriptions originated most frequently from VA Medical Centers (87%) and women's health clinics (76%) compared to community-based or other clinic types. In multivariable regression models, race, ethnicity, BMI ≥30, and prescriber facility type of a VA Medical Center or a women's clinic location were predictive of UPA prescription. CONCLUSIONS: Oral EC provision in VHA remains low, but UPA use is increasing. LNG prescription occurs frequently in high BMI Veterans who would benefit from increased efficacy of UPA. Interventions to expand oral EC access in VHA are essential to ensure Veterans' ability to avert unwanted pregnancies.

Communicating about COVID-19 vaccine development and safety.

PURPOSE: Beliefs that the risks from a COVID-19 vaccine outweigh the risks from getting COVID-19 and concerns that the vaccine development process was rushed and lacking rigor have been identified as important drivers of hesitancy and refusal to get a COVID-19 vaccine. We tested whether messages designed to address these beliefs and concerns might promote intentions to get a COVID-19 vaccine. METHOD: We conducted an online survey fielded between March 8-23, 2021 with US Veteran (n = 688) and non-Veteran (n = 387) respondents. In a between-subjects experiment, respondents were randomly assigned to a control group (with no message) or to read one of two intervention messages: 1. a fact-box styled message comparing the risks of getting COVID-19 compared to the vaccine, and 2. a timeline styled message describing the development process of the COVID-19 mRNA vaccines. RESULTS: Most respondents (60%) wanted a COVID-19 vaccine. However, 17% expressed hesitancy and 23% did not want to get a COVID-19 vaccine. The fact-box styled message and the timeline message did not significantly improve vaccination intentions, F(2,358) = 0.86, p = .425, [Formula: see text] = .005, or reduce the time respondents wanted to wait before getting vaccinated, F(2,306) = 0.79, p = .453, [Formula: see text] = .005, compared to no messages. DISCUSSION: In this experimental study, we did not find that providing messages about vaccine risks and the development process had an impact on respondents' vaccine intentions. Further research is needed to identify how to effectively address concerns about the risks associated with COVID-19 vaccines and the development process and to understand additional factors that influence vaccine intentions.

Communications to Promote Interest and Confidence in COVID-19 Vaccines.

PURPOSE: Communicating about COVID-19 vaccine side effects and efficacy is crucial for promoting transparency and informed decision-making, but there is limited evidence on how to do so effectively. DESIGN: A within-subjects experiment. SETTING: Online survey from January 21 to February 6, 2021. SUBJECTS: 596 US Veterans and 447 non-Veterans. INTERVENTION: 5 messages about COVID-19 vaccine side effects and 4 messages about COVID-19 vaccine efficacy. MEASURES: COVID-19 vaccine interest (1 = "I definitely do NOT want the vaccine" to 7 = "I definitely WANT the vaccine" with the midpoint 4 = "Unsure"). Confidence about COVID-19 vaccine efficacy (1= "Not at all confident," 2 = "Slightly confident," 3 = "Somewhat confident," 4 = "Moderately confident," 5 = "Extremely confident"). RESULTS: Compared to providing information about side effects alone (M = 5.62 [1.87]), messages with additional information on the benefits of vaccination (M = 5.77 [1.82], P < .001, dz = .25), reframing the likelihood of side effects (M = 5.74 [1.84], P < .001, dz = .23), and emphasizing that post-vaccine symptoms indicate the vaccine is working (M = 5.72 [1.84], P < .001, dz = .17) increased vaccine interest. Compared to a vaccine efficacy message containing verbal uncertainty and an efficacy range (M = 3.97 [1.25]), messages conveying verbal certainty with an efficacy range (M = 4.00 [1.24], P = .042, dz=.08), verbal uncertainty focused on the upper efficacy limit (M = 4.03 [1.26], P < .001, dz = .13), and communicating the point estimate with certainty (M = 4.02 [1.25], P < .001, dz = .11) increased confidence. Overall, Veteran respondents were more interested (MVeterans = 5.87 [1.72] vs MNonVeterans = 5.45 [2.00], P < .001, d = .22) and confident (MVeterans = 4.13 [1.19] vs MNonVeterans = 3.84 [1.32], P < .001, d = .23) about COVID-19 vaccines than non-Veterans. CONCLUSIONS: These strategies can be implemented in large-scale communications (e.g., webpages, social media, and leaflets/posters) and can help guide healthcare professionals when discussing vaccinations in clinics to promote interest and confidence in COVID-19 vaccines.

Factors Associated With PCSK9 Inhibitor Initiation Among US Veterans.

Background Few adults at high risk for atherosclerotic cardiovascular disease events use a PCSK9i (proprotein convertase subtilisin/kexin type 9 inhibitor). Methods and Results Using data from the US Veterans Health Administration, we identified veterans who initiated a PCSK9i between January 2018 and December 2019, matched 1:4 to veterans who did not initiate this medication over this time period (case-cohort study). Two cohorts of veterans were analyzed: (1) atherosclerotic cardiovascular disease, with a most recent low-density lipoprotein cholesterol (LDL-C) ≥70 mg/dL; and (2) severe hypercholesterolemia (ie, familial hypercholesterolemia or any prior LDL-C ≥190 mg/dL, with most recent LDL-C ≥100 mg/dL). Conditional logistic regression was used to analyze factors associated with PCSK9i initiation, adjusting for all factors, simultaneously. There were 2394 initiators and 9576 noninitiators in the atherosclerotic cardiovascular disease cohort (median LDL-C, 141 and 96 mg/dL, respectively; P<0.001). Factors associated with a higher likelihood of PCSK9i initiation included age 65 to <75 versus <65 years, highest versus lowest quartile of median area-level income, familial hypercholesterolemia, former statin use, and current ezetimibe use. PCSK9i initiation was lower among veterans of a race/ethnicity other than non-Hispanic White. There were 245 initiators and 980 noninitiators in the severe hypercholesterolemia cohort (median LDL-C, 183 and 151 mg/dL, respectively; P<0.001). Age ≥75 versus <65 years, history of chronic kidney disease, former statin use, and current ezetimibe use were associated with a higher likelihood of PCSK9i initiation. Conclusions Several patient-level factors, including age, sex, and race/ethnicity, were significantly associated with PCSK9i initiation, suggesting an unmet treatment need in several patient groups.

Angiotensin II receptor blocker or angiotensin-converting enzyme inhibitor use and COVID-19-related outcomes among US Veterans.

BACKGROUND: Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) may positively or negatively impact outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association of ARB or ACEI use with coronavirus disease 2019 (COVID-19)-related outcomes in US Veterans with treated hypertension using an active comparator design, appropriate covariate adjustment, and negative control analyses. METHODS AND FINDINGS: In this retrospective cohort study of Veterans with treated hypertension in the Veterans Health Administration (01/19/2020-08/28/2020), we compared users of (A) ARB/ACEI vs. non-ARB/ACEI (excluding Veterans with compelling indications to reduce confounding by indication) and (B) ARB vs. ACEI among (1) SARS-CoV-2+ outpatients and (2) COVID-19 hospitalized inpatients. The primary outcome was all-cause hospitalization or mortality (outpatients) and all-cause mortality (inpatients). We estimated hazard ratios (HR) using propensity score-weighted Cox regression. Baseline characteristics were well-balanced between exposure groups after weighting. Among outpatients, there were 5.0 and 6.0 primary outcomes per 100 person-months for ARB/ACEI (n = 2,482) vs. non-ARB/ACEI (n = 2,487) users (HR 0.85, 95% confidence interval [CI] 0.73-0.99, median follow-up 87 days). Among outpatients who were ARB (n = 4,877) vs. ACEI (n = 8,704) users, there were 13.2 and 14.8 primary outcomes per 100 person-months (HR 0.91, 95%CI 0.86-0.97, median follow-up 85 days). Among inpatients who were ARB/ACEI (n = 210) vs. non-ARB/ACEI (n = 275) users, there were 3.4 and 2.0 all-cause deaths per 100 person months (HR 1.25, 95%CI 0.30-5.13, median follow-up 30 days). Among inpatients, ARB (n = 1,164) and ACEI (n = 2,014) users had 21.0 vs. 17.7 all-cause deaths, per 100 person-months (HR 1.13, 95%CI 0.93-1.38, median follow-up 30 days). CONCLUSIONS: This observational analysis supports continued ARB or ACEI use for patients already using these medications before SARS-CoV-2 infection. The novel beneficial association observed among outpatients between users of ARBs vs. ACEIs on hospitalization or mortality should be confirmed with randomized trials.

Automated Travel History Extraction From Clinical Notes for Informing the Detection of Emergent Infectious Disease Events: Algorithm Development and Validation.

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.

Association Between Contact Precautions and Transmission of Methicillin-Resistant Staphylococcus aureus in Veterans Affairs Hospitals.

Importance: The effectiveness and importance of contact precautions for endemic pathogens has long been debated, and their use has broad implications for infection control of other pathogens. Objective: To estimate the association between contact precautions and transmission of methicillin-resistant Staphylococcus aureus (MRSA) across US Department of Veterans Affairs (VA) hospitals. Design, Setting, and Participants: This retrospective cohort study used mathematical models applied to data from a population-based sample of adults hospitalized in 108 VA acute care hospitals for at least 24 hours from January 1, 2008, to December 31, 2017. Data were analyzed from May 2, 2019, to December 11, 2020. Exposures: A positive MRSA test result, presumed to indicate contact precautions use according to the VA MRSA Prevention Initiative. Main Outcomes and Measures: The main outcome was the association between contact precautions and MRSA transmission, defined as the relative transmissibility attributed to contact precautions. A contact precaution effect estimate (<1 indicates a reduction in transmission associated with contact precautions) was estimated for each hospital and then pooled over time and across hospitals using meta-regression. Results: In this cohort study of 108 VA hospitals, more than 2 million unique individuals had over 5.6 million admissions, of which 14.1% were presumed to have contact precautions with more than 8.4 million MRSA surveillance tests. Pooled estimates found associations between contact precautions and transmission to be stable from 2008 to 2017, with estimated transmission reductions ranging from 43% (95% credible interval [CrI], 38%-48%) to 51% (95% CrI, 46%-55%). Over the entire 10-year study period, contact precautions reduced transmission 47% (95% CrI, 45%-49%), and the intrafacility autocorrelation coefficient estimate was 0.99, suggesting consistent estimates over time within facilities. Larger facilities and those with higher admission screening compliance observed additional reductions in transmission associated with contact precautions (relative rate, 0.84; 95% CI, 0.74-0.96 and 0.74; 95% CI, 0.58-0.96, respectively) compared with smaller facilities and those with lower admission screening compliance. Facilities in the southern US had a smaller transmission reduction attributable to contact precautions (relative rate, 1.14; 95% CI, 1.01-1.28) compared with facilities in other regions in the US. Conclusions and Relevance: In this cohort study of adults in VA hospitals, transmissibility of MRSA was found to be reduced by approximately 50% among patients with contact precautions. These results provide an explanation for decreasing acquisition rates in VA hospitals since the MRSA Prevention Initiative.

Computerized Mortality Prediction for Community-acquired Pneumonia at 117 Veterans Affairs Medical Centers.

Rationale: Computerized severity assessment for community-acquired pneumonia could improve consistency and reduce clinician burden. Objectives: To develop and compare 30-day mortality-prediction models using electronic health record data, including a computerized score with all variables from the original Pneumonia Severity Index (PSI) except confusion and pleural effusion ("ePSI score") versus models with additional variables. Methods: Among adults with community-acquired pneumonia presenting to emergency departments at 117 Veterans Affairs Medical Centers between January 1, 2006, and December 31, 2016, we compared an ePSI score with 10 novel models employing logistic regression, spline, and machine learning methods using PSI variables, age, sex and 26 physiologic variables as well as all 69 PSI variables. Models were trained using encounters before January 1, 2015; tested on encounters during and after January 1, 2015; and compared using the areas under the receiver operating characteristic curve, confidence intervals, and patient event rates at a threshold PSI score of 970. Results: Among 297,498 encounters, 7% resulted in death within 30 days. When compared using the ePSI score (confidence interval [CI] for the area under the receiver operating characteristic curve, 0.77-0.78), performance increased with model complexity (CI for the logistic regression PSI model, 0.79-0.80; CI for the boosted decision-tree algorithm machine learning PSI model using the Extreme Gradient Boosting algorithm [mlPSI] with the 19 original PSI factors, 0.83-0.85) and the number of variables (CI for the logistic regression PSI model using all 69 variables, 0.84-085; CI for the mlPSI with all 69 variables, 0.86-0.87). Models limited to age, sex, and physiologic variables also demonstrated high performance (CI for the mlPSI with age, sex, and 26 physiologic factors, 0.84-0.85). At an ePSI score of 970 and a mortality-risk cutoff of <2.7%, the ePSI score identified 31% of all patients as being at "low risk"; the mlPSI with age, sex, and 26 physiologic factors identified 53% of all patients as being at low risk; and the mlPSI with all 69 variables identified 56% of all patients as being at low risk, with similar rates of mortality, hospitalization, and 7-day secondary hospitalization being determined. Conclusions: Computerized versions of the PSI accurately identified patients with pneumonia who were at low risk of death. More complex models classified more patients as being at low risk of death and as having similar adverse outcomes.

Attributable Cost of Healthcare-Associated Methicillin-Resistant Staphylococcus aureus Infection in a Long-term Care Center.

BACKGROUND: Studies have shown that healthcare-associated infections (HAIs) due to methicillin-resistant Staphylococcus aureus (MRSA) can lead to substantial healthcare costs in acute care settings. However, little is known regarding the consequences of these infections on patients in long-term care centers (LTCCs). The purpose of this study was to estimate the attributable cost of MRSA HAIs in LTCCs within the Department of Veterans Affairs (VA). METHODS: We performed a retrospective cohort study of patients admitted to VA LTCCs between 1 January 2009 and 30 September 2015. MRSA HAIs were defined as a positive clinical culture at least 48 hours after LTCC admission so as to exclude community-acquired infections. Positive cultures were further classified by site (sterile or nonsterile). We used multivariable generalized linear models and 2-part models to compare the LTCC and acute care costs between patients with and without an MRSA HAI. RESULTS: In our primary analysis, there was no difference in LTCC costs between patients with and without a MRSA HAI. There was, however, a significant increase in the odds of being transferred to an acute care facility (odds ratio, 4.40 [95% confidence interval {CI}, 3.40-5.67]) and in acute care costs ($9711 [95% CI, $6961-$12 462]). CONCLUSIONS: Our findings of high cost and increased risk of transfer from LTCC to acute care are important because they highlight the substantial clinical and economic impact of MRSA infections in this population.

Expanding an Economic Evaluation of the Veterans Affairs (VA) Methicillin-resistant Staphylococcus aureus (MRSA) Prevention Initiative to Include Prevention of Infections From Other Pathogens.

BACKGROUND: In October 2007, Veterans Affairs (VA) launched a nationwide effort to reduce methicillin-resistant Staphylococcus aureus (MRSA) transmission called the National MRSA Prevention Initiative. Although the initiative focused on MRSA, recent evidence suggests that it also led to a significant decrease in hospital-onset (HO) gram-negative rod (GNR) bacteremia, vancomycin-resistant Enterococci (VRE), and Clostridioides difficile infections. The objective of this analysis was to evaluate the cost-effectiveness and the budget impact of the initiative taking into account MRSA, GNR, VRE, and C. difficile infections. METHODS: We developed an economic model using published data on the rate of MRSA hospital-acquired infections (HAIs) and HO-GNR bacteremia in the VA from October 2007 to September 2015, estimates of the attributable cost and mortality of these infections, and the costs associated with the intervention obtained through a microcosting approach. We explored several different assumptions for the rate of infections that would have occurred if the initiative had not been implemented. Effectiveness was measured in life-years (LYs) gained. RESULTS: We found that during fiscal years 2008-2015, the initiative resulted in an estimated 4761-9236 fewer MRSA HAIs, 1447-2159 fewer HO-GNR bacteremia, 3083-3602 fewer C. difficile infections, and 2075-5393 fewer VRE infections. The initiative itself was estimated to cost $561 million over this 8-year period, whereas the cost savings from prevented MRSA HAIs ranged from $165 to $315 million and from prevented HO-GNR bacteremia, CRE and C. difficile infections ranged from $174 to $200 million. The incremental cost-effectiveness of the initiative ranged from $12 146 to $38 673/LY when just including MRSA HAIs and from $1354 to $4369/LY when including the additional pathogens. The overall impact on the VA's budget ranged from $67 to$195 million. CONCLUSIONS: An MRSA surveillance and prevention strategy in VA may have prevented a substantial number of infections from MRSA and other organisms. The net increase in cost from implementing this strategy was quite small when considering infections from all types of organisms. Including spillover effects of organism-specific prevention efforts onto other organisms can provide a more comprehensive evaluation of the costs and benefits of these interventions.

Transmission Dynamics of Clostridioides difficile in 2 High-Acuity Hospital Units.

BACKGROUND: The key epidemiological drivers of Clostridioides difficile transmission are not well understood. We estimated epidemiological parameters to characterize variation in C. difficile transmission, while accounting for the imperfect nature of surveillance tests. METHODS: We conducted a retrospective analysis of C. difficile surveillance tests for patients admitted to a bone marrow transplant (BMT) unit or a solid tumor unit (STU) in a 565-bed tertiary hospital. We constructed a transmission model for estimating key parameters, including admission prevalence, transmission rate, and duration of colonization to understand the potential variation in C. difficile dynamics between these 2 units. RESULTS: A combined 2425 patients had 5491 admissions into 1 of the 2 units. A total of 3559 surveillance tests were collected from 1394 patients, with 11% of the surveillance tests being positive for C. difficile. We estimate that the transmission rate in the BMT unit was nearly 3-fold higher at 0.29 acquisitions per percentage colonized per 1000 days, compared to our estimate in the STU (0.10). Our model suggests that 20% of individuals admitted into either the STU or BMT unit were colonized with C. difficile at the time of admission. In contrast, the percentage of surveillance tests that were positive within 1 day of admission to either unit for C. difficile was 13.4%, with 15.4% in the STU and 11.6% in the BMT unit. CONCLUSIONS: Although prevalence was similar between the units, there were important differences in the rates of transmission and clearance. Influential factors may include antimicrobial exposure or other patient-care factors.