Performance of Cardiovascular Physical Exam Skills by Internal Medicine Residents.

OBJECTIVE: Few studies have assessed the ability of internal medicine residents to perform a cardiovascular physical examination using real patients. METHODS: First year internal medicine interns from two large academic medical centers in Maryland examined the same patient with aortic insufficiency as part of the Assessment of Physical Examination and Communication Skills (APECS). Interns were assessed on five clinical domains: physical exam technique, identifying physical signs, generating a differential diagnosis, clinical judgement, and maintaining patient welfare. Spearman's correlation test was used to describe associations between clinical domains. Preceptor comments were examined to identify common errors in physical exam technique and identifying physical signs. RESULTS: One-hundred and nine interns examined the same patient with aortic insufficiency across 14 APECS sessions. Only 58 interns (53.2%) correctly identified the presence of a diastolic murmur, and only 52 interns (47.7%) included aortic insufficiency on their differential diagnosis. There was a significant and positive correlation between physical exam technique and identification of the correct physical findings (r=0.42, p<0.001). Both technique (r=0.34, p=0.003) and identifying findings (r=0.42, p<0.001) were significantly associated with generating an appropriate differential diagnosis. Common errors in technique included auscultating over the gown, timing the cardiac cycle with the radial pulse, and failing to palpate for the apical impulse. CONCLUSIONS: Internal medicine interns had variable skills in performing and interpreting the cardiovascular physical exam. Improving cardiovascular exam skills would likely lead to increased identification of relevant cardiovascular findings, inform clinical decision making and improve overall patient care.

Preparing the Frontlines: Delivering Special Pathogen Training to Maryland Hospital Staff.

Healthcare workers (HCWs) at community hospitals, also known as frontline hospitals (FLHs), may encounter patients with possible infectious diseases, including those caused by high-consequence pathogens such as Zaire ebolavirus. We created and piloted a 1-day, in-person, didactic and skills training program to determine the feasibility and acceptability of implementing an educational program to enhance the knowledge and skills needed to respond when a patient with a potential high-consequence pathogen presents to an FLH. The Maryland Department of Health queried all 104 state FLHs to identify their interest in participating in the pilot training program. HCWs from 12 (75%) of the 16 interested FLHs participated in the program before it was interrupted by the COVID-19 pandemic. In addition to pathogen-specific training based on the Identify, Isolate, and Inform framework, we provided skills training in the proper use of personal protective equipment, spill cleanup, and removal of an incapacitated HCW from an isolation area. We conducted a paired pretraining and posttraining knowledge assessment and measured a significant learning gain among 135 participants (2-tailed t test, P<.05). Over 95% of the participants reported that the training was relevant to their daily work and the clinical simulations and reference material were useful and appropriate for their learning level. Findings from this pilot program demonstrated the feasibility and acceptability of a 1-day combined didactic and skills training program focused on high-consequence pathogens. We plan to reengage the original FLHs and add regional FLHs in an updated training effort based on our findings.

The ethics of using COVID-19 host genomic information for clinical and public health decision-making: A survey of US health professionals.

Several genetic variants linked to COVID-19 have been identified by host genomics researchers. Further advances in this research will likely play a role in the clinical management and public health control of future infectious disease outbreaks. The implementation of genetic testing to identify host genomic risk factors associated with infectious diseases raises several ethical, legal, and social implications (ELSIs). As an important stakeholder group, health professionals can provide key insights into these ELSI issues. In 2021, a cross-sectional online survey was fielded to US health professionals. The survey explored how they view the value and ethical acceptability of using COVID-19 host genomic information in three main decision-making settings: (1) clinical, (2) public health, and (3) workforce. The survey also assessed participants' personal and professional experience with genomics and infectious diseases and collected key demographic data. A total of 603 participants completed the survey. A majority (84%) of participants agreed that it is ethically acceptable to use host genomics to make decisions about clinical care and 73% agreed that genetic screening has an important role to play in the public health control of COVID-19. However, more than 90% disagreed that it is ethically acceptable to use host genomics to deny resources or admission to individuals when hospital resources are scarce. Understanding stakeholder perspectives and anticipating ELSI issues will help inform policies for hospitals and public health departments to evaluate and perhaps adopt host genomic technologies in an ethically and socially responsible manner during future infectious disease outbreaks.

Navigating the Landscape of Precision Education: Insights From On-the-Ground Initiatives.

ABSTRACT: A central goal of precision education (PE) is efficiently delivering the right educational intervention to the right learner at the right time. This can be achieved through a PE cycle that involves gathering inputs, using analytics to generate insights, planning and implementing interventions, learning and assessing outcomes, and then using lessons learned to inform modifications to the cycle. In this paper, the authors describe 3 PE initiatives utilizing this cycle. The Graduate Medical Education Laboratory (GEL) uses longitudinal data on graduate trainee behavior, clinical skills, and wellness to improve clinical performance and professional fulfillment. The Transition to Residency Advantage (TRA) program uses learner data from medical school coupled with individualized coaching to improve the transition to residency. The Anesthesia Research Group for Educational Technology (TARGET) is developing an automated tool to deliver individualized education to anesthesia residents based on a longitudinal digital representation of the learner. The authors discuss strengths of the PE cycle and transferrable learnings for future PE innovations. Common challenges are identified, including related to data (e.g., volume, variety, sharing across institutions, using the electronic health record), analytics (e.g., validating augmented intelligence models), and interventions (e.g., scaling up learner assessments with limited resources). PE developers need to share their experiences in order to overcome these challenges, develop best practices, and ensure ethical development of future systems. Adapting a common framework to develop and assess PE initiatives will lead to a clearer understanding of their impact, help to mitigate potential risks, and allow deployment of successful practices on a larger scale.

Skin Pigmentation and Pulse Oximeter Accuracy in the Intensive Care Unit: a Pilot Prospective Study.

Rationale: Despite multiple reports of pulse oximeter inaccuracy among hospitalized Black individuals, regulatory testing of pulse oximeters is performed on healthy volunteers. Objective: Evaluate pulse oximeter accuracy among intensive care unit patients with diverse skin pigmentation. Methods: Skin pigmentation was measured using a chromameter in 12 patients and individual typology angle (ITA), a measure of constitutive pigmentation, calculated. Arterial blood gas (ABG) arterial oxygen saturation (SaO 2 ) sampling was precisely matched to pulse oximetry (SpO 2 ) using arterial line waveforms analysis. Error (SpO 2 -SaO 2 ), bias, and average root mean square error (A RMS ) were calculated. Multivariable linear mixed effects models evaluated the association of SpO 2 -SaO 2 with skin pigmentation. Measurements and Main Results: Sampling time was determined for 350 ABGs. Five participants (N=96 ABGs) were darkly pigmented (forehead ITA<-30°), and 7 lighter pigmented (N=254 ABGs). Darkly pigmented individuals had 1.05% bias and 4.15% A RMS compared to 0.34% bias and 1.97% A RMS among lighter pigmented individuals. After adjusting for SaO 2 , pH, heart rate, and mean arterial pressure, SpO 2 -SaO 2 was falsely elevated by 1.00% more among darkly pigmented individuals (95% confidence interval: 0.25-1.76%). SpO 2 significantly overestimated SaO 2 for dark, brown, and tan forehead or forearm pigmentation and brown and tan finger pad pigmentation compared to intermediate/light pigmentation. Conclusions: The pulse oximeter in clinical use at an academic medical center performed worse in darkly pigmented critically ill patients than established criteria for FDA clearance. Pulse oximeter testing in ICU settings is feasible, and could be required by regulators to ensure equivalent device performance by skin pigmentation among patients.

Information Challenges Associated With Accessing and Sharing of Patient Information in Disasters: A Qualitative Analysis.

As disasters increase in frequency and severity, so too does the health impact on affected populations. Disasters exacerbate the already challenging health information-sharing landscape. A reduced capacity to access and share patient information may have negative impacts on providers' ability to care for patients individually and to address disaster health outcomes at the population level. Between October 2018 and July 2019, we conducted 21 semistructured interviews with physicians experienced in providing healthcare during disasters to understand the challenges related to patient information sharing in disaster responses. Key informants noted challenges with patient information management-including accessing, sharing, and transferring information-and that it was a barrier to providing effective clinical care in disasters. Three major areas were identified as challenges: (1) lack of systematic mechanisms for patient information sharing during disaster handoffs, (2) lack of access to a patient's past medical history, and (3) population-level impacts of patient information-sharing breakdowns in disasters. Reducing barriers to effective patient information sharing is a critical need during disasters. Requirements generally fall to overburdened clinicians, and novel solutions that ease this responsibility and leverage existing infrastructure should be explored. Work conducted during the COVID-19 pandemic may inform new solutions. Integrated approaches that support information sharing in real time will improve patient care at the individual level and can support operational improvements to current and future disaster responses.

Clinical Outcomes Associated With Overestimation of Oxygen Saturation by Pulse Oximetry in Patients Hospitalized With COVID-19.

Importance: Many pulse oximeters have been shown to overestimate oxygen saturation in persons of color, and this phenomenon has potential clinical implications. The relationship between overestimation of oxygen saturation with timing of COVID-19 medication delivery and clinical outcomes remains unknown. Objective: To investigate the association between overestimation of oxygen saturation by pulse oximetry and delay in administration of COVID-19 therapy, hospital length of stay, risk of hospital readmission, and in-hospital mortality. Design, Setting, and Participants: This cohort study included patients hospitalized for COVID-19 at 186 acute care facilities in the US with at least 1 functional arterial oxygen saturation (SaO2) measurement between March 2020 and October 2021. A subset of patients were admitted after July 1, 2020, without immediate need for COVID-19 therapy based on pulse oximeter saturation (SpO2 levels of 94% or higher without supplemental oxygen). Exposures: Self-reported race and ethnicity, difference between concurrent SaO2 and pulse oximeter saturation (SpO2) within 10 minutes, and initially unrecognized need for COVID-19 therapy (first SaO2 reading below 94% despite SpO2 levels of 94% or above). Main Outcome and Measures: The association of race and ethnicity with degree of pulse oximeter measurement error (SpO2 - SaO2) and odds of unrecognized need for COVID-19 therapy were determined using linear mixed-effects models. Associations of initially unrecognized need for treatment with time to receipt of therapy (remdesivir or dexamethasone), in-hospital mortality, 30-day hospital readmission, and length of stay were evaluated using mixed-effects models. All models accounted for demographics, clinical characteristics, and hospital site. Effect modification by race and ethnicity was evaluated using interaction terms. Results: Among 24 504 patients with concurrent SpO2 and SaO2 measurements (mean [SD] age, 63.9 [15.8] years; 10 263 female [41.9%]; 3922 Black [16.0%], 7895 Hispanic [32.2%], 2554 Asian, Native American or Alaskan Native, Hawaiian or Pacific Islander, or another race or ethnicity [10.4%], and 10 133 White [41.4%]), pulse oximetry overestimated SaO2 for Black (adjusted mean difference, 0.93 [95% CI, 0.74-1.12] percentage points), Hispanic (0.49 [95% CI, 0.34-0.63] percentage points), and other (0.53 [95% CI, 0.35-0.72] percentage points) patients compared with White patients. In a subset of 8635 patients with a concurrent SpO2 - SaO2 pair without immediate need for COVID-19 therapy, Black patients were significantly more likely to have pulse oximetry values that masked an indication for COVID-19 therapy compared with White patients (adjusted odds ratio [aOR], 1.65; 95% CI, 1.33-2.03). Patients with an unrecognized need for COVID-19 therapy were 10% less likely to receive COVID-19 therapy (adjusted hazard ratio, 0.90; 95% CI, 0.83-0.97) and higher odds of readmission (aOR, 2.41; 95% CI, 1.39-4.18) regardless of race (P for interaction = .45 and P = .14, respectively). There was no association of unrecognized need for COVID-19 therapy with in-hospital mortality (aOR, 0.84; 95% CI, 0.71-1.01) or length of stay (mean difference, -1.4 days; 95% CI, -3.1 to 0.2 days). Conclusions and Relevance: In this cohort study, overestimation of oxygen saturation by pulse oximetry led to delayed delivery of COVID-19 therapy and higher probability of readmission regardless of race. Black patients were more likely to have unrecognized need for therapy with potential implications for population-level health disparities.

Potential drug-drug interactions among U.S. adults treated with nirmatrelvir/ritonavir: A cross-sectional study of the National Covid Cohort Collaborative (N3C).

STUDY OBJECTIVE: To estimate the prevalence of potential moderate to severe drug-drug interactions (DDIs) involving nirmatrelvir/ritonavir, identify interacting medications, and evaluate risk factors associated with potential DDIs. DESIGN: Cross-sectional study. DATA SOURCE: Electronic health records from the National COVID Cohort Collaborative Enclave, one of the largest COVID-19 data resources in the United States. PATIENTS: Outpatients aged ≥18 years and started nirmatrelvir/ritonavir between December 23, 2021 and March 31, 2022. INTERVENTION: Nirmatrelvir/ritonavir. MEASUREMENTS: The outcome is potential moderate to severe DDIs, defined as starting interacting medications reported by National Institutes of Health 30 days before or 10 days after starting nirmatrelvir/ritonavir. MAIN RESULTS: Of 3214 outpatients who started nirmatrelvir/ritonavir, the mean age was 56.8 ± 17.1 years, 39.5% were male, and 65.8% were non-Hispanic white. Overall, 521 (16.2%) were potentially exposed to at least one moderate to severe DDI, most commonly to atorvastatin (19.2% of all DDIs), hydrocodone (14.0%), or oxycodone (14.0%). After adjustment for covariates, potential DDIs were more likely among individuals who were older (odds ratio [OR] 1.16 per 10-year increase, 95% confidence interval [CI] 1.08-1.25), male (OR 1.36, CI 1.09-1.71), smokers (OR 1.38, CI 1.10-1.73), on more co-medications (OR 1.35, CI 1.31-1.39), and with a history of solid organ transplant (OR 3.63, CI 2.05-6.45). CONCLUSIONS: One in six of individuals receiving nirmatrelvir/ritonavir were at risk of a potential moderate or severe DDI, underscoring the importance of clinical and pharmacy systems to mitigate such risks.

Internal medicine intern performance on the gastrointestinal physical exam.

OBJECTIVES: The gastrointestinal (GI) physical exam provides critical information about underlying disease states. However, since assessment of physical examination skills is rarely conducted as part of internal medicine residency training, little is known about resident performance on the GI physical exam. METHODS: During a clinical skills assessment that took place between November 2019 and February 2020, internal medicine interns examined the same patient with chronic liver disease while being observed by faculty preceptors. We compared the exam maneuvers performed with those expected by the faculty evaluators. We noted which maneuvers were performed incorrectly, whether physical exam technique correlated with identification of physical exam findings, and if performance on the physical exam was associated with building an appropriate differential diagnosis. This four-hour assessment was required for internal medicine interns within two different residency programs in the Baltimore area. RESULTS: More than half of the 29 participating interns (n=17, 58.6 %) received a "needs improvement" score on their physical exam technique. Technique was highly correlated with identifying the correct physical signs (r=0.88, p<0.0001). The most commonly excluded maneuvers were assessing for splenomegaly and hepatomegaly. The most commonly missed findings were splenomegaly and hepatomegaly. Most interns included chronic liver disease as part of their differential diagnosis even if they received "needs improvement" scores on physical exam technique or identifying physical signs. CONCLUSIONS: Internal medicine interns would benefit from learning an organized approach to the gastrointestinal exam. This would likely lead to increased identification of important gastrointestinal findings.

Evaluation of Plasma Biomarkers to Predict Major Adverse Kidney Events in Hospitalized Patients With COVID-19.

RATIONALE & OBJECTIVE: Patients hospitalized with COVID-19 are at increased risk for major adverse kidney events (MAKE). We sought to identify plasma biomarkers predictive of MAKE in patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: A total of 576 patients hospitalized with COVID-19 between March 2020 and January 2021 across 3 academic medical centers. EXPOSURE: Twenty-six plasma biomarkers of injury, inflammation, and repair from first available blood samples collected during hospitalization. OUTCOME: MAKE, defined as KDIGO stage 3 acute kidney injury (AKI), dialysis-requiring AKI, or mortality up to 60 days. ANALYTICAL APPROACH: Cox proportional hazards regression to associate biomarker level with MAKE. We additionally applied the least absolute shrinkage and selection operator (LASSO) and random forest regression for prediction modeling and estimated model discrimination with time-varying C index. RESULTS: The median length of stay for COVID-19 hospitalization was 9 (IQR, 5-16) days. In total, 95 patients (16%) experienced MAKE. Each 1 SD increase in soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 was significantly associated with an increased risk of MAKE (adjusted HR [AHR], 2.30 [95% CI, 1.86-2.85], and AHR, 2.26 [95% CI, 1.73-2.95], respectively). The C index of sTNFR1 alone was 0.80 (95% CI, 0.78-0.84), and the C index of sTNFR2 was 0.81 (95% CI, 0.77-0.84). LASSO and random forest regression modeling using all biomarkers yielded C indexes of 0.86 (95% CI, 0.83-0.89) and 0.84 (95% CI, 0.78-0.91), respectively. LIMITATIONS: No control group of hospitalized patients without COVID-19. CONCLUSIONS: We found that sTNFR1 and sTNFR2 are independently associated with MAKE in patients hospitalized with COVID-19 and can both also serve as predictors for adverse kidney outcomes. PLAIN-LANGUAGE SUMMARY: Patients hospitalized with COVID-19 are at increased risk for long-term adverse health outcomes, but not all patients suffer long-term kidney dysfunction. Identification of patients with COVID-19 who are at high risk for adverse kidney events may have important implications in terms of nephrology follow-up and patient counseling. In this study, we found that the plasma biomarkers soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 measured in hospitalized patients with COVID-19 were associated with a greater risk of adverse kidney outcomes. Along with clinical variables previously shown to predict adverse kidney events in patients with COVID-19, both sTNFR1 and sTNFR2 are also strong predictors of adverse kidney outcomes.

COVID-19 clinical outcomes by patient disability status: A retrospective cohort study.

BACKGROUND: People with disabilities might experience worse clinical outcomes of SARS-CoV-2 infection, but evidence is limited. OBJECTIVE: To investigate if people with disabilities requiring assistance are more likely to experience severe COVID-19 or death. METHODS: Data from the Johns Hopkins COVID-19 Precision Medicine Analytics Platform Registry (JH-CROWN) included 6494 adult patients diagnosed with COVID-19 and admitted between March 4, 2020-October 29, 2021. Severe COVID-19 and death were defined using the occurrence and timing of clinical events. Assistive needs due to disabilities were reported by patients or their proxies upon admission. Multivariable-adjusted Cox proportional hazards models were used to examine the associations between disability status and severe COVID-19 or death. Primary models adjusted for demographics and secondary models additionally adjusted for clinical covariates. RESULTS: In this clinical cohort (47-73 years, 49% female, 39% Black), patients with disabilities requiring assistance had 1.35 times (95% confidence interval [CI]:1.01, 1.81) the hazard of severe COVID-19 among patients <65 years, but not among those ≥65 years, equating to an additional 17.5 severe COVID-19 cases (95% CI:7.7, 28.2) per 100 patients. A lower risk of mortality was found among patients <65 years, but this finding was not robust due to the small number of deaths. CONCLUSIONS: People with disabilities requiring assistance aged <65 years are more likely to develop severe COVID-19. Although our study is limited by using a medical model of disability, these analyses intend to further our understanding of COVID-19 outcomes among people with disabilities. Also, standardized disability data collection within electronic health records is needed.

Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients.

As clinicians are faced with a deluge of clinical data, data science can play an important role in highlighting key features driving patient outcomes, aiding in the development of new clinical hypotheses. Insight derived from machine learning can serve as a clinical support tool by connecting care providers with reliable results from big data analysis that identify previously undetected clinical patterns. In this work, we show an example of collaboration between clinicians and data scientists during the COVID-19 pandemic, identifying sub-groups of COVID-19 patients with unanticipated outcomes or who are high-risk for severe disease or death. We apply a random forest classifier model to predict adverse patient outcomes early in the disease course, and we connect our classification results to unsupervised clustering of patient features that may underpin patient risk. The paradigm for using data science for hypothesis generation and clinical decision support, as well as our triaged classification approach and unsupervised clustering methods to determine patient cohorts, are applicable to driving rapid hypothesis generation and iteration in a variety of clinical challenges, including future public health crises.

Impact of Severe Acute Respiratory Syndrome Coronavirus 2 Variants on Inpatient Clinical Outcome.

BACKGROUND: Prior observation has shown differences in COVID-19 hospitalization risk between SARS-CoV-2 variants, but limited information describes hospitalization outcomes. METHODS: Inpatients with COVID-19 at 5 hospitals in the eastern United States were included if they had hypoxia, tachypnea, tachycardia, or fever, and SARS-CoV-2 variant data, determined from whole-genome sequencing or local surveillance inference. Analyses were stratified by history of SARS-CoV-2 vaccination or infection. The average effect of SARS-CoV-2 variant on 28-day risk of severe disease, defined by advanced respiratory support needs, or death was evaluated using models weighted on propensity scores derived from baseline clinical features. RESULTS: Severe disease or death within 28 days occurred for 977 (29%) of 3369 unvaccinated patients and 269 (22%) of 1230 patients with history of vaccination or prior SARS-CoV-2 infection. Among unvaccinated patients, the relative risk of severe disease or death for Delta variant compared with ancestral lineages was 1.30 (95% confidence interval [CI]: 1.11-1.49). Compared with Delta, the risk for Omicron patients was .72 (95% CI: .59-.88) and compared with ancestral lineages was .94 (.78-1.1). Among Omicron and Delta infections, patients with history of vaccination or prior SARS-CoV-2 infection had half the risk of severe disease or death (adjusted hazard ratio: .40; 95% CI: .30-.54), but no significant outcome difference by variant. CONCLUSIONS: Although risk of severe disease or death for unvaccinated inpatients with Omicron was lower than with Delta, it was similar to ancestral lineages. Severe outcomes were less common in vaccinated inpatients, with no difference between Delta and Omicron infections.

Thromboprophylaxis in people hospitalized with COVID-19: Assessing intermediate or standard doses in a retrospective cohort study.

Background and Objectives: Current clinical guidelines recommend thromboprophylaxis for adults hospitalized with coronavirus disease 2019 (COVID-19), yet it is unknown whether higher doses of thromboprophylaxis offer benefits beyond standard doses. Methods: We studied electronic health records from 50 091 adults hospitalized with COVID-19 in the United States between February 2020 and February 2021. We compared standard (enoxaparin 30 or 40 mg/day, fondaparinux 2.5 mg, or heparin 5000 units twice or thrice per day) versus intermediate (enoxaparin 30 or 40 mg twice daily, or up to 1.2 mg/kg of body weight daily, heparin 7500 units thrice per day or heparin 10 000 units twice or thrice per day) thromboprophylaxis. We separately examined risk of escalation to therapeutic anticoagulation, severe disease (first occurrence of high-flow nasal cannula, noninvasive positive pressure ventilation or invasive mechanical ventilation), and death. To summarize risk, we present hazard ratios (HRs) with 95% confidence intervals (CIs) using adjusted time-dependent Cox proportional hazards regression models. Results: People whose first dose was high intensity were younger, more often obese, and had greater oxygen support requirements. Intermediate dose thromboprophylaxis was associated with increased risk of therapeutic anticoagulation (HR, 3.39; 95% CI, 3.22-3.57), severe disease (HR, 1.22; 95% CI, 1.17-1.28), and death (HR, 1.37; 95% CI, 1.21-1.55). Increased risks associated with intermediate-dose thromboprophylaxis persisted in subgroup and sensitivity analyses varying populations and definitions of exposures, outcomes, and covariates. Conclusions: Our findings do not support routine use of intermediate-dose thromboprophylaxis to prevent clinical worsening, severe disease, or death among adults hospitalized with COVID-19.

Use of a Real-Time Locating System to Assess Internal Medicine Resident Location and Movement in the Hospital.

Importance: The patient-physician clinical encounter is the cornerstone of medical training, yet residents spend as little as 12% of their time in direct patient contact. Objectives: To use a real-time locating system (RTLS) to characterize intern work experiences in the hospital, understand factors associated with time spent at patients' bedsides, and inform future interventions to increase time spent with patients. Design, Setting, and Participants: This cross-sectional study was conducted from July 1, 2018, to June 30, 2019 (ie, the academic year 2018-2019). Internal medicine residents from postgraduate year 1 (interns) at an academic medical center wore an infrared badge that recorded location and duration (eg, patient room, ward hall, physician workroom). Data were analyzed from September 1, 2020, to August 30, 2021. Main Outcomes and Measures: Main outcome was time (in minutes) at the bedside; the unit of analysis was a 24-hour intern day or interval of time within the day (eg, rounding period). Descriptive statistics are reported overall, by intern, and for 5 clinical service categories. Multilevel modeling assessed the association of intern, service, and calendar time with time spent at the bedside. Results: Data from 43 of 52 interns (82.7%) encompassing 95 275 hours of observations were included for analyses. Twenty-six interns (60.5%) were women. Interns were detected for a mean (SD) of 722.8 (194.4) minutes per 24-hour period; 13.4% of this time was spent in patient rooms (mean [SD] time, 96.8 [57.2] minutes) and 33.3% in physician workrooms (mean [SD] time, 240.9 [228.8] minutes). Mean percentage of time at the bedside during a 24-hour period varied among interns from 8.8% to 18.3%. Mean (SD) percentage of time at the bedside varied by service for the 24-hour period from 11.7% (6.6%) for nononcology subspecialties to 15.4% (6.0%) for oncology, and during rounds from 8.0% (12.4%) for nononcology subspecialties to 26.5% (12.1%) for oncology. In multilevel modeling, the individual intern accounted for 8.1% of overall variance in time spent at the bedside during a 24-hour period, and service accounted for 18.0% of variance during rounds. Conclusions and Relevance: The findings of this cross-sectional study support previous evidence suggesting that interns spend only a small proportion of time with hospitalized patients. The differences in time spent in patients' rooms among interns and during rounds constitute an opportunity to design interventions that bring trainees back to the bedside.

Racial and Ethnic Discrepancy in Pulse Oximetry and Delayed Identification of Treatment Eligibility Among Patients With COVID-19.

Importance: Pulse oximetry guides triage and therapy decisions for COVID-19. Whether reported racial inaccuracies in oxygen saturation measured by pulse oximetry are present in patients with COVID-19 and associated with treatment decisions is unknown. Objective: To determine whether there is differential inaccuracy of pulse oximetry by race or ethnicity among patients with COVID-19 and estimate the association of such inaccuracies with time to recognition of eligibility for oxygen threshold-specific COVID-19 therapies. Design, Setting, and Participants: This retrospective cohort study of clinical data from 5 referral centers and community hospitals in the Johns Hopkins Health System included patients with COVID-19 who self-identified as Asian, Black, Hispanic, or White. Exposures: Concurrent measurements (within 10 minutes) of oxygen saturation levels in arterial blood (SaO2) and by pulse oximetry (SpO2). Main Outcomes and Measures: For patients with concurrent SpO2 and SaO2 measurements, the proportion with occult hypoxemia (SaO2<88% with concurrent SpO2 of 92%-96%) was compared by race and ethnicity, and a covariate-adjusted linear mixed-effects model was produced to estimate the association of race and ethnicity with SpO2 and SaO2 difference. This model was applied to identify a separate sample of patients with predicted SaO2 levels of 94% or less before an SpO2 level of 94% or less or oxygen treatment initiation. Cox proportional hazards models were used to estimate differences by race and ethnicity in time to recognition of eligibility for guideline-recommended COVID-19 therapies, defined as an SpO2 level of 94% or less or oxygen treatment initiation. The median delay among individuals who ultimately had recognition of eligibility was then compared. Results: Of 7126 patients with COVID-19, 1216 patients (63 Asian [5.2%], 478 Black [39.3%], 215 Hispanic [17.7%], and 460 White [37.8%] individuals; 507 women [41.7%]) had 32 282 concurrently measured SpO2 and SaO2. Occult hypoxemia occurred in 19 Asian (30.2%), 136 Black (28.5%), and 64 non-Black Hispanic (29.8%) patients compared with 79 White patients (17.2%). Compared with White patients, SpO2 overestimated SaO2 by an average of 1.7% among Asian (95% CI, 0.5%-3.0%), 1.2% among Black (95% CI, 0.6%-1.9%), and 1.1% among non-Black Hispanic patients (95% CI, 0.3%-1.9%). Separately, among 1903 patients with predicted SaO2 levels of 94% or less before an SpO2 level of 94% or less or oxygen treatment initiation, compared with White patients, Black patients had a 29% lower hazard (hazard ratio, 0.71; 95% CI, 0.63-0.80), and non-Black Hispanic patients had a 23% lower hazard (hazard ratio, 0.77; 95% CI, 0.66-0.89) of treatment eligibility recognition. A total of 451 patients (23.7%) never had their treatment eligibility recognized, most of whom (247 [54.8%]) were Black. Among the remaining 1452 (76.3%) who had eventual recognition of treatment eligibility, Black patients had a median delay of 1.0 hour (95% CI, 0.23-1.9 hours; P = .01) longer than White patients. There was no significant median difference in delay between individuals of other racial and ethnic minority groups and White patients. Conclusions and Relevance: The results of this cohort study suggest that racial and ethnic biases in pulse oximetry accuracy were associated with greater occult hypoxemia in Asian, Black, and non-Black Hispanic patients with COVID-19, which was associated with significantly delayed or unrecognized eligibility for COVID-19 therapies among Black and Hispanic patients. This disparity may contribute to worse outcomes among Black and Hispanic patients with COVID-19.

Contributions of the Regional Emerging Special Pathogen Treatment Centers to the US COVID-19 Pandemic Response.

The National Emerging Special Pathogens Training and Education Center (NETEC) was established in 2015 to improve the capabilities of healthcare facilities to provide safe and effective care to patients with Ebola and other special pathogens in the United States. Through NETEC, a collaborative network of 10 Regional Emerging Special Pathogen Treatment Centers (RESPTCs) undertook readiness activities that included potential respiratory pathogens. These preparations, which took place before the COVID-19 pandemic, established a foundation of readiness that enabled RESPTCs to play a pivotal role in the US COVID-19 pandemic response. As initial COVID-19 cases were detected in the United States, RESPTCs provided essential isolation capacity, supplies, and subject matter expertise that allowed for additional time for healthcare systems to prepare. Through the Special Pathogen Research Network, RESPTCs rapidly enrolled patients into early clinical trials. During periods of high community transmission, RESPTCs provided educational, clinical, and logistical support to a wide range of healthcare and nonhealthcare settings. In this article, we describe how NETEC and the RESPTC network leveraged this foundation of special pathogen readiness to strengthen the national healthcare system's response to the COVID-19 pandemic. NETEC and the RESPTC network have proven to be an effective model that can support the national response to future emerging special pathogens.

Creating a Safety Officer Program to Enhance Staff Safety During the Care of COVID-19 Patients.

Staff safety is paramount when managing an infectious disease event. However, early data from the COVID-19 pandemic suggested that staff compliance with personal protective equipment and other safety protocols was poor. In response to patient surges, many hospitals created dedicated "biomode" units to provide care for patients infected with SARS-CoV-2, the virus that causes COVID-19. To enhance staff safety on biomode units and during patient transports, our hospital created a safety officer/transport safety officer (SO/TSO) program. The first SOs/TSOs were nurses, clinical technicians, and other support staff who were redeployed from their home units when the units closed during the initial surge. During subsequent COVID-19 surges, dedicated SOs/TSOs were hired to maintain the program. SOs/TSOs provided just-in-time personal protective equipment training and helped staff safely enter and exit COVID-19 clinical units. SOs/TSOs participated in the transport of over 1,000 COVID-19 patients with no safety incidents reported. SOs/TSOs conducted safety audits throughout the hospital and observed 86% compliance with COVID-19 precautions across 32,500 activities. During contact tracing of frontline staff who became infected with SARS-CoV-2, potential deviations from COVID-19 precautions were identified in only 7.7% of cases. The SO/TSO program contributed to a culture of safety in the biomode units and helped to enhance infection prevention throughout the hospital. This program can serve as a model for other health systems during the response to the current pandemic and during future infectious disease threats.