Faculty Bibliography

The coronavirus disease 2019 (COVID-19) pandemic has caused more than 675 million confirmed cases and nearly 7 million deaths worldwide [1]. While testing for COVID-19 was initially centered in health care facilities, with required reporting to health departments, it is increasingly being performed in the home with rapid antigen testing [2]. Most at-home tests are self-interpreted and not reported to a provider or health department, which could lead to delayed reporting or underreporting of cases [3]. As such, there is a strong possibility that reported cases may become a less reliable indicator of transmission over time.

We sought to understand the current state of research in adult Hospital Medicine by repeating a 2018 survey of leaders in Hospital Medicine with changes to improve the response rate of surveyed programs. We also analyzed the public sources of federal research funding and MEDLINE-indexed publications from 2010 through 2019 among members of the Society of Hospital Medicine (SHM). Of the 102 contacted leaders of Hospital Medicine groups across the country, 49 responded, for a total response rate of 48%. Among the 3397 faculty members represented in responding programs, 72 (2%) of faculty were identified as conducting research for more than 50% of their time. Respondents noted difficulties at every stage of the research development pipeline, from a lack of mentors to running a fellowship program to a lack of applicants seeking further research training. Improvements to our research training pipeline will be essential to the long-term improvement of our profession.

Understanding patient characteristics associated with scheduling and completing telehealth visits can identify potential biases or latent preferences related to telehealth usage. We describe patient characteristics associated with being scheduled for and completing audio and video visits. We used data from patients at 17 adult primary care departments in a large, urban public healthcare system from August 1, 2020 to July 31, 2021. We used hierarchical multivariable logistic regression to generate adjusted odds ratios (aOR) for patient characteristics associated with having been scheduled for and completed telehealth (vs in-person) visits and for video (vs audio) scheduling and completion during two time periods: a telehealth transition period (N = 190,949) and a telehealth elective period (N = 181,808). Patient characteristics were significantly associated with scheduling and completion of telehealth visits. Many associations were similar across time periods, but others changed over time. Patients who were older (≥ 65 years old vs 18-44 years old: aOR for scheduling 0.53/completion 0.48), Black (0.86/0.71), Hispanic (0.76/0.62), or had Medicaid (0.93/0.84) were among those less likely to be scheduled for or complete video (vs audio) visits. Patients with activated patient portals (1.97/3.34) or more visits (≥ 3 scheduled visits vs 1 visit: 2.40/1.52) were more likely to be scheduled for or complete video visits. Variation in scheduling/completion explained by patient characteristics was 7.2%/7.5%, clustering by provider 37.2%/34.9%, and clustering by facility 43.1%/37.4%. Stable and dynamic associations suggest persistent gaps in access and evolving preferences/biases. Variation explained by patient characteristics was relatively low compared with that explained by provider and facility clustering.

BACKGROUND:The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE:To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN/METHODS:Retrospective cohort. SETTING/METHODS:Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION/METHODS:Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS/METHODS:We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS:Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS/CONCLUSIONS:Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION/CONCLUSIONS:Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

OBJECTIVE/UNASSIGNED:The objective of this study was to evaluate the relative validity of the nine-item Diet Risk Score (DRS) among Chinese American adults using Healthy Eating Index (HEI)-2015 scores. We provide insights into the application of the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) for this population, and report on lessons learned from carrying out participant recruitment during the COVID-19 pandemic. METHODS/UNASSIGNED:Thirty-three Chinese American adults (mean age=40; 36% male) were recruited from the community and through ResearchMatch. Participants completed the DRS and two 24-hour food records, which were entered into the ASA 24-Hour Dietary Assessment Tool (ASA24) by community health workers (CHWs). HEI-2015 scores were calculated from each food record and an average score was obtained for each participant. One-way analysis of variance and Spearman correlations were used to compare total and component scores between the DRS and HEI-2015. RESULTS/UNASSIGNED:Mean HEI-2015 score was 56.7/100 (SD 10.6) and mean DRS score was 11.8/27 (SD 4.7), with higher scores reflecting better and worse diets, respectively. HEI-2015 and DRS scores were inversely correlated (r=-0.43, p<0.05). The strongest correlations were between HEI-2015 Total Vegetables and DRS Vegetables (r=-0.5, p<0.01), HEI-2015 Total Vegetables and Green Vegetables (r=-0.43, p=0.01) and HEI-2015 Seafood/Plant Protein and DRS Fish (r=-0.47, p<0.01). The inability to advertise and recruit for the study in person at community centres due to pandemic restrictions impeded the recruitment of less-acculturated individuals. A lack of cultural food items in the ASA24 database made it difficult to record dietary intake as reported by participants. CONCLUSION/UNASSIGNED:The DRS can be a valuable tool for physicians to identify and reach Chinese Americans at risk of cardiometabolic disease.

BACKGROUND:Burnout has risen across healthcare workers during the pandemic, contributing to workforce turnover. While prior literature has largely focused on physicians and nurses, there is a need to better characterize and identify actionable predictors of burnout and work intentions across healthcare role types. OBJECTIVE:To characterize the association of work overload with rates of burnout and intent to leave (ITL) the job in a large national sample of healthcare workers. DESIGN:Cross-sectional survey study conducted between April and December 2020. SETTING:A total of 206 large healthcare organizations. PARTICIPANTS:Physicians, nurses, other clinical staff, and non-clinical staff. MEASURES:Work overload, burnout, and ITL. RESULTS:The sample of 43,026 respondents (mean response rate 44%) was comprised of 35.2% physicians, 25.7% nurses, 13.3% other clinical staff, and 25.8% non-clinical staff. The overall burnout rate was 49.9% (56.0% in nursing, 54.1% in other clinical staff, 47.3% in physicians, and 45.6% in non-clinical staff; p < 0.001 for difference). ITL was reported by 28.7% of healthcare workers, with nurses most likely to report ITL (41.0%), followed by non-clinical staff (32.6%), other clinical staff (32.1%), and physicians (24.3%) (p < 0.001 for difference). The prevalence of perceived work overload ranged from 37.1% among physicians to 47.4% in other clinical staff. In propensity-weighted models, work overload was significantly associated with burnout (adjusted risk ratio (ARR) 2.21 to 2.90) and intent to leave (ARR 1.73 to 2.10) across role types. LIMITATIONS:Organizations' participation in the survey was voluntary. CONCLUSIONS:There are high rates of burnout and intent to leave the job across healthcare roles. Proactively addressing work overload across multiple role types may help with concerning trends across the healthcare workforce. This will require a more granular understanding of sources of work overload across different role types, and a commitment to matching work demands to capacity for all healthcare workers.

INTRODUCTION/BACKGROUND:Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown. METHODS:Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission. RESULTS:Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97). CONCLUSIONS:Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers. IMPLICATIONS/CONCLUSIONS:Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

Age is a predominant risk factor for acute kidney injury (AKI), yet the biological mechanisms underlying this risk are largely unknown and to date no genetic mechanisms for AKI have been established. Clonal hematopoiesis of indeterminate potential (CHIP) is a recently recognized biological mechanism conferring risk of several chronic aging diseases including cardiovascular disease, pulmonary disease and liver disease. In CHIP, blood stem cells acquire mutations in myeloid cancer driver genes such as DNMT3A, TET2, ASXL1 and JAK2 and the myeloid progeny of these mutated cells contribute to end-organ damage through inflammatory dysregulation. We sought to establish whether CHIP causes acute kidney injury (AKI). To address this question, we first evaluated associations with incident AKI events in three population-based epidemiology cohorts (N = 442,153). We found that CHIP was associated with a greater risk of AKI (adjusted HR 1.26, 95% CI: 1.19-1.34, p<0.0001), which was more pronounced in patients with AKI requiring dialysis (adjusted HR 1.65, 95% CI: 1.24-2.20, p=0.001). The risk was particularly high in the subset of individuals where CHIP was driven by mutations in genes other than DNMT3A (HR: 1.49, 95% CI: 1.37-1.61, p<0.0001). We then examined the association between CHIP and recovery from AKI in the ASSESS-AKI cohort and identified that non-DNMT3A CHIP was more common among those with a non-resolving pattern of injury (HR 2.3, 95% CI: 1.14-4.64, p = 0.03). To gain mechanistic insight, we evaluated the role of Tet2-CHIP to AKI in ischemia-reperfusion injury (IRI) and unilateral ureteral obstruction (UUO) mouse models. In both models, we observed more severe AKI and greater post-AKI kidney fibrosis in Tet2-CHIP mice. Kidney macrophage infiltration was markedly increased in Tet2-CHIP mice and Tet2-CHIP mutant renal macrophages displayed greater proinflammatory responses. In summary, this work establishes CHIP as a genetic mechanism conferring risk of AKI and impaired kidney function recovery following AKI via an aberrant inflammatory response in CHIP derived renal macrophages.

INTRODUCTION/BACKGROUND:The contribution of chronotropic incompetence to reduced exercise tolerance after a heart transplant is well known, but its role as a prognostic marker of post-transplant mortality is unclear. The aim of this study is to examine the relationship between post-transplant heart rate response (HRR) and survival. METHODS:We performed a retrospective analysis of all adult heart transplant recipients at the University of Pennsylvania between the years 2000 and 2011 who underwent a cardiopulmonary exercise test (CPET) within a year of transplant. Follow-up time and survival status were observed through October 2019, using data merged from the Penn Transplant Institute. HRR was calculated by subtracting the resting HR from the peak exercise HR. The association between HRR and mortality was analyzed using Cox proportional hazard models and Kaplan-Meier analysis. The optimal cut-off point for HRR was generated by Harrell's C statistic. Patients with submaximal exercise tests were excluded, defined by a respiratory exchange ratio (RER) cut-off of 1.05. RESULTS: CONCLUSION/CONCLUSIONS:In heart transplant patients, a low HRR is associated with increased all-cause mortality and decreased exercise capacity. Additional studies are needed to validate whether targeting HRR in cardiac rehabilitation may improve outcomes.

OBJECTIVES/OBJECTIVE:Patient experience and presence of evidence-based facility services are 2 dimensions of assessing quality of addiction treatment facilities. However, the relationship between these two is not well described. The objective of this study was to explore associations between patient experience measures and service offerings at addiction treatment facilities. METHODS:We used data from cross-sectional surveys of addiction treatment facilities and persons involved in treatment at corresponding facilities to identify facility services (eg, availability of medications for alcohol use disorder, assistance with obtaining social services, etc) and patient experience measures (overall facility rating, extent helped by treatment, ability to deal with daily problems after treatment), respectively. We used hierarchical multiple logistic regression to test for associations between top-box scores for each patient experience outcome and facility services. RESULTS:We analyzed 9191 patient experience surveys from 149 facilities. Assistance with obtaining social services (adjusted odds ratio [95% confidence interval], 0.43 [0.28-0.66]) was associated with lower overall treatment facility ratings. Childcare (2.00 [1.04-3.84]) was associated with top-box scores for extent helped. Availability of cognitive behavioral therapy (2.67 [1.25-5.73]) and childcare (1.77 [1.08-2.92]) were associated with top-box scores for ability to deal with daily problems after treatment. Assistance with obtaining social services (0.61 [0.41-0.90]) was associated with lower scores for ability to deal with problems after treatment. CONCLUSIONS:Few addiction treatment facility services were associated with patient experience measures. Future work should explore bridging the gap between evidence-based services and positive patient experiences.