A small but significantly greater incidence of inflammatory heart disease identified after vaccination for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2)

Background SARS-CoV-2 vaccines are being administered on an unprecedented scale. Assessing the risks of side effects is needed to aid clinicians in early detection and treatment. This study examined the risk of inflammatory heart disease, including pericarditis and myocarditis, following SARS-CoV-2 vaccination. Methods Intermountain Healthcare patients with inflammatory heart disease from December 15, 2020, to June 15, 2021, and with or without preceding SARS-CoV-2 vaccinations were studied. Relative rates of inflammatory heart disease were examined for vaccinated patients compared to unvaccinated patients. Results Of 67 identified inflammatory heart disease patients, 21 (31.3%) had a SARS-Cov-2 vaccination within the previous 60 days. Overall, 914,611 Intermountain Healthcare patients received a SARS-CoV-2 vaccine, resulting in an inflammatory heart disease rate of 2.30 per 100,000 vaccinated patients. The relative risk of inflammatory heart disease for the vaccinated patients compared to the unvaccinated patients was 2.05 times higher rate within the 30-day window (p=0.01) and had a trend toward increase in the 60-day window (relative rate=1.63; p=0.07). All vaccinated patients with inflammatory heart disease were treated successfully with one death related to a pre-existing condition. Conclusions Though rare, the rate of inflammatory heart disease was greater in a SARS-CoV-2 vaccinated population than the unvaccinated population. This risk is eclipsed by the risk of contracting COVID-19 and its associated, commonly severe outcomes. Nevertheless, clinicians and patients should be informed of this risk to facilitate earlier recognition and treatment.

Follow-Up Blood Cultures in Young Infants With Bacteremic Urinary Tract Infections

BACKGROUND AND OBJECTIVES Researchers in previous studies suggest that the clinical yield of follow-up blood cultures (FUBCs) is low in infants with bacteremic urinary tract infection (UTI) because persistent bacteremia is rare; however, no researchers have analyzed the practice of routinely obtaining FUBCs. In our study, we evaluate outcomes in infants with FUBCs, examine opportunities for improvement of blood culture practices, and add important information to inform both clinical practice as well as further study. DESIGN This retrospective cohort study included infants <90 days of age with bacteremia and UTI with the same pathogen at 22 hospitals that make up Intermountain Healthcare between 2002 to 2020. Infants with culture proven meningitis, osteomyelitis, central line infection, and infections occurring during NICU hospitalization were excluded. RESULTS Total number of patients with bacteremic UTI was 174, 153 (88%) patients had at least 1 FUBC, 14 of 153 (9%) had a positive FUBC with same organism, and 4 of 153 (3%) were contaminants. The length of stay was longer for patients with positive FUBCs. Patients with Escherichia coli are more likely to have a negative FUBC. Readmissions within 30 days were similar among infants with positive FUBCs, negative FUBCs, and no FUBCs. CONCLUSIONS FUBCs in infants with bacteremic UTI should not be routinely performed, especially for E coli, and it is unclear whether FUBCs improve outcomes.

External validation of integrated genetic-epigenetic biomarkers for predicting incident coronary heart disease

Aim: The Framingham Risk Score (FRS) and ASCVD Pooled Cohort Equation (PCE) for predicting risk for incident coronary heart disease (CHD) work poorly. To improve risk stratification for CHD, we developed a novel integrated genetic-epigenetic tool. Materials & methods: Using machine learning techniques and datasets from the Framingham Heart Study (FHS) and Intermountain Healthcare (IM), we developed and validated an integrated genetic-epigenetic model for predicting 3-year incident CHD. Results: Our approach was more sensitive than FRS and PCE and had high generalizability across cohorts. It performed with sensitivity/specificity of 79/75% in the FHS test set and 75/72% in the IM set. The sensitivity/specificity was 15/93% in FHS and 31/89% in IM for FRS, and sensitivity/specificity was 41/74% in FHS and 69/55% in IM for PCE. Conclusion: The use of our tool in a clinical setting could better identify patients at high risk for a heart attack.

Implementation of an Infectious Diseases Telehealth Consultation and Antibiotic Stewardship Program for 16 Small Community Hospitals

Background Telehealth improves access to infectious diseases (ID) and antibiotic stewardship (AS) services in small community hospitals (SCHs), but the optimal model has not been defined. We describe implementation and impact of an integrated ID telehealth (IDt) service for 16 SCHs in the Intermountain Healthcare system. Methods The Intermountain IDt service included a 24-hour advice line, eConsults, telemedicine consultations (TCs), daily AS surveillance, long-term AS program (ASP) support by an IDt pharmacist, and a monthly telementoring webinar. We evaluated program measures from November 2016 through April 2018. Results A total of 2487 IDt physician interactions with SCHs were recorded: 859 phone calls (35% of interactions), 761 eConsults (30%), and 867 TCs (35%). Of 1628 eConsults and TCs, 1400 (86%) were SCH provider requests, while 228 (14%) were IDt pharmacist generated. Six SCHs accounted for >95% of interactions. Median consultation times for each initial telehealth interaction type were 5 (interquartile range [IQR], 5–10) minutes for phone calls, 20 (IQR, 15–25) minutes for eConsults, and 50 (IQR, 35–60) minutes for TCs. Thirty-two percent of consults led to in-person ID clinic follow-up. Bacteremia was the most common reason for consultation (764/2487 [31%]) and Staphylococcus aureus the most common organism identified. ASPs were established at 16 facilities. Daily AS surveillance led to 2229 SCH pharmacist and 1305 IDt pharmacist recommendations. Eight projects were completed with IDt pharmacist support, leading to significant reductions in meropenem, vancomycin, and fluoroquinolone use. Conclusions An integrated IDt model led to collaborative ID/ASP interventions and improvements in antibiotic use at 16 SCHs. These findings provide insight into clinical and logistical considerations for IDt program implementation.

Implementation and Outcomes of a Telehealth Neonatology Program in a Single Healthcare System

Background: Intermountain Healthcare, an early adopter and champion for newborn video-assisted resuscitation (VAR), identified a reduction in facility-level transfers and an estimated savings of $1. 2 million in potentially avoided transfers in a 2018 study. This study was conducted to increase understanding of VAR at the individual, newborn level.Study Aim: To compare transfers to a newborn intensive care unit (NICU), length of stay (LOS), and days of life on oxygen between newborns managed by neonatal VAR and those receiving standard care (SC).Methods: This retrospective, nonequivalent group study includes infants born in an Intermountain hospital between 2013 and 2017, 34 weeks gestation or greater, and requiring oxygen support in the first 15 minutes of life. Data came from billing and clinical records from Intermountain's enterprise data warehouse and chart reviews. We used logistic regression to estimate neonatal VAR's impact on transfers. Negative binomial regression estimated the impact on LOS and days of life on supplemental oxygen.Results: The VAR intervention was used in 46.2 percent of post-implementation cases and is associated with (1) a 12 percentage points reduction in the transfer rate, p = 0.02, (2) a reduction in spoke hospital (SH) LOS of 8.33 h (p < 0.01) for all transfers; (3) a reduction in SH LOS of 2.21 h (p < 0.01) for newborns transferred within 24 h; (4) a reduction in SH LOS of 17.85 h (p = 0.06) among non-transferred newborns; (5) a reduction in days of life on supplemental oxygen of 1.4 days (p = 0.08) among all transferred newborns, and (6) a reduction in days of life on supplemental oxygen of 0.41 days (p = 0.04) among non-transferred newborns.Conclusion: This study provides evidence that neonatal VAR improves care quality and increases local hospitals' capabilities to keep patients close to home. There is an ongoing demand for support to rural and community hospitals for urgent newborn resuscitations, and complex, mandatory NICU transfers. Efforts may be necessary to encourage neonatal VAR since the intervention was only used in 46.2 percent of this study's potential cases. Additional work is needed to understand the short- and long-term impacts of Neonatal VAR on health outcomes.

Forecasting Future Asthma Hospital Encounters of Patients With Asthma in an Academic Health Care System: Predictive Model Development and Secondary Analysis Study

Background Asthma affects a large proportion of the population and leads to many hospital encounters involving both hospitalizations and emergency department visits every year. To lower the number of such encounters, many health care systems and health plans deploy predictive models to prospectively identify patients at high risk and offer them care management services for preventive care. However, the previous models do not have sufficient accuracy for serving this purpose well. Embracing the modeling strategy of examining many candidate features, we built a new machine learning model to forecast future asthma hospital encounters of patients with asthma at Intermountain Healthcare, a nonacademic health care system. This model is more accurate than the previously published models. However, it is unclear how well our modeling strategy generalizes to academic health care systems, whose patient composition differs from that of Intermountain Healthcare. Objective This study aims to evaluate the generalizability of our modeling strategy to the University of Washington Medicine (UWM), an academic health care system. Methods All adult patients with asthma who visited UWM facilities between 2011 and 2018 served as the patient cohort. We considered 234 candidate features. Through a secondary analysis of 82,888 UWM data instances from 2011 to 2018, we built a machine learning model to forecast asthma hospital encounters of patients with asthma in the subsequent 12 months. Results Our UWM model yielded an area under the receiver operating characteristic curve (AUC) of 0.902. When placing the cutoff point for making binary classification at the top 10% (1464/14,644) of patients with asthma with the largest forecasted risk, our UWM model yielded an accuracy of 90.6% (13,268/14,644), a sensitivity of 70.2% (153/218), and a specificity of 90.91% (13,115/14,426). Conclusions Our modeling strategy showed excellent generalizability to the UWM, leading to a model with an AUC that is higher than all of the AUCs previously reported in the literature for forecasting asthma hospital encounters. After further optimization, our model could be used to facilitate the efficient and effective allocation of asthma care management resources to improve outcomes. International Registered Report Identifier (IRRID) RR2-10.2196/resprot.5039

Generalizability of an Automatic Explanation Method for Machine Learning Prediction Results on Asthma-Related Hospital Visits in Patients With Asthma: Quantitative Analysis

Background Asthma exerts a substantial burden on patients and health care systems. To facilitate preventive care for asthma management and improve patient outcomes, we recently developed two machine learning models, one on Intermountain Healthcare data and the other on Kaiser Permanente Southern California (KPSC) data, to forecast asthma-related hospital visits, including emergency department visits and hospitalizations, in the succeeding 12 months among patients with asthma. As is typical for machine learning approaches, these two models do not explain their forecasting results. To address the interpretability issue of black-box models, we designed an automatic method to offer rule format explanations for the forecasting results of any machine learning model on imbalanced tabular data and to suggest customized interventions with no accuracy loss. Our method worked well for explaining the forecasting results of our Intermountain Healthcare model, but its generalizability to other health care systems remains unknown. Objective The objective of this study is to evaluate the generalizability of our automatic explanation method to KPSC for forecasting asthma-related hospital visits. Methods Through a secondary analysis of 987,506 data instances from 2012 to 2017 at KPSC, we used our method to explain the forecasting results of our KPSC model and to suggest customized interventions. The patient cohort covered a random sample of 70% of patients with asthma who had a KPSC health plan for any period between 2015 and 2018. Results Our method explained the forecasting results for 97.57% (2204/2259) of the patients with asthma who were correctly forecasted to undergo asthma-related hospital visits in the succeeding 12 months. Conclusions For forecasting asthma-related hospital visits, our automatic explanation method exhibited an acceptable generalizability to KPSC. International Registered Report Identifier (IRRID) RR2-10.2196/resprot.5039

Incidence and cost of radical prostatectomy for NCCN low-risk prostate cancer in Utah.

232 Background: Guidelines Support active surveillance (AS) as the preferred treatment for men with NCCN low-risk prostate cancer (Gleason 3+3, prostate-specific antigen [PSA] <10 ng/ml, ≤T2a). Recent work from Mahal BA et al. (JAMA 2019) reports AS rates are increasing, but only 42.1% of men with low-risk prostate cancer underwent AS in 2015. Low-risk prostate cancer accounted for 30.1% of diagnoses. The majority of Utah residents treated for prostate cancer receive therapy at either The Huntsman Cancer Institute or Intermountain Healthcare facilities. We modeled the costs associated with the presumptive overtreatment of men with low-risk disease treated in 2017-2019. Methods: Data from The Huntsman Cancer Institute and Intermountain Healthcare cancer databases from 2017 to 2019 were retrospectively analyzed. Men with available pathologic, laboratory and clinical data who had undergone prostatectomy were stratified by having NCCN low, intermediate, and high-risk disease. Rates of radical prostatectomy by year and institution were analyzed. The cost of prostatectomy compared to AS was estimated to be $14,453 from recent work by Trogdon JG et al. (JAMA Oncol 2019). Results: Data was available for 1,155 Utahn men (Table). Of the 1155 surgeries performed, 69 (6%) were in low-risk patients. The total costs of care that might have been avoided over these three years are estimated to be $1 million. Conclusions: Approximately 6% of prostatectomies performed in Utah are in men with NCCN low-risk prostate cancer. While these rates are lower than the national average, we estimate approximately $1 million in medical costs and toxicities could be deferred had these patients opted for AS. Work is ongoing to characterize clinical toxicity of treatment in these men, and a multi-institutional collaborative education outreach program to reduce overtreatment is in development. [Table: see text]

Survey of physician and pharmacist steward perceptions of their antibiotic stewardship programs

Objective: To examine how individual steward characteristics (eg, steward role, sex, and specialized training) are associated with their views of antimicrobial stewardship program (ASP) implementation at their institution. Design: Descriptive survey from a mixed-methods study. Setting: Two large national healthcare systems; the Veterans’ Health Administration (VA) (n = 134 hospitals) and Intermountain Healthcare (IHC; n = 20 hospitals). Participants: We sent the survey to 329 antibiotic stewards serving in 154 hospitals; 152 were physicians and 177 were pharmacists. In total, 118 pharmacists and 64 physicians from 126 hospitals responded. Methods: The survey was grounded in constructs of the Consolidated Framework for Implementation Research, and it assessed stewards’ views on the development and implementation of antibiotic stewardship programs (ASPs) at their institutions We then examined differences in stewards’ views by demographic factors. Results: Regardless of individual factors, stewards agreed that the ASP added value to their institution and was advantageous to patient care. Stewards also reported high levels of collegiality and self-efficacy. Stewards who had specialized training or those volunteered for the role were less likely to think that the ASP was implemented due to a mandate. Similarly volunteers and those with specialized training felt that they had authority in the antibiotic decisions made in their facility. Conclusions: Given the importance of ASPs, it may be beneficial for healthcare institutions to recruit and train individuals with a true interest in stewardship.