Hospitalist perspective on pandemic related clinical and administrative changes: a cross sectional survey study.

OBJECTIVE: Hospitalists have played a leading role in caring for hospitalized COVID-19 patients. Many clinical and administrative changes occurred in hospitals to meet the varied pandemic needs. We surveyed hospitalists to understand their perspective on pandemic-related changes in technology, models of care, administration and leadership, impact on personal lives, and which of these changes should be continued versus reverting to pre-pandemic practices. METHODS: A 30-question survey was distributed to hospitalists working across the United States between 6 April 2022 to 16 May 2022. Baseline demographics were measured, and post-pandemic perspectives related to changes were analyzed. Perspectives were measured using a 5-point Likert scale and responses were categorized into 'agree' and 'did not agree' for analysis. Variation was assessed using Chi-square or Fisher exact tests. Open-ended questions were reported following qualitative content analysis organized into themes and reported as frequency. RESULTS: 177 respondents (39%) completed the survey. Nearly three-fourths favored hybrid meetings, and two-thirds preferred to continue new models of care. Nearly 90% desired more family and leisure time, continued wellness, and support services, and resumption of social gatherings. No major differences in perspectives were noted between hospitalists at teaching facilities and non-teaching facilities except for resuming protected time for non-clinical activities in those from teaching facilities (83.0% vs 62.5%). Respondents less than age 50 were more likely to prefer virtual meetings (59.0% vs 31.3%). Content analysis of open-ended questions resulted in different themes for each question. Respondents favored more work-life balance and less administrative and logistical work burden. CONCLUSIONS: Hospitalists preferred to continue the use of technology and new models of care even in the post-pandemic period and express a desire for more work-life balance and less administrative and logistical work burden.

An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems.

BACKGROUND: We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores. METHODS: This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis. RESULTS: Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P > 0.827) with c-statistics ranged 0.849-0.856, calibration slopes 0.911-1.173, and Hosmer-Lemeshow P > 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P < 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores. CONCLUSION: The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice.

Natural Language Processing CAM Algorithm Improves Delirium Detection Compared With Conventional Methods.

Delirium is known to be underdiagnosed and underdocumented. Delirium detection in retrospective studies occurs mostly by clinician diagnosis or nursing documentation. This study aims to assess the effectiveness of natural language processing-confusion assessment method (NLP-CAM) algorithm when compared to conventional modalities of delirium detection. A multicenter retrospective study analyzed 4351 COVID-19 hospitalized patient records to identify delirium occurrence utilizing three different delirium detection modalities namely clinician diagnosis, nursing documentation, and the NLP-CAM algorithm. Delirium detection by any of the 3 methods is considered positive for delirium occurrence as a comparison. NLP-CAM captured 80% of overall delirium, followed by clinician diagnosis at 55%, and nursing flowsheet documentation at 43%. Increase in age, Charlson comorbidity score, and length of hospitalization had increased delirium detection odds regardless of the detection method. Artificial intelligence-based NLP-CAM algorithm, compared to conventional methods, improved delirium detection from electronic health records and holds promise in delirium diagnostics.

Characteristics, Treatment Patterns, and Clinical Outcomes After Heart Failure Hospitalizations During the COVID-19 Pandemic, March to October 2020.

OBJECTIVE: To compare clinical characteristics, treatment patterns, and 30-day all-cause readmission and mortality between patients hospitalized for heart failure (HF) before and during the coronavirus disease 2019 (COVID-19) pandemic. PATIENTS AND METHODS: The study was conducted at 16 hospitals across 3 geographically dispersed US states. The study included 6769 adults (mean age, 74 years; 56% [5033 of 8989] men) with cumulative 8989 HF hospitalizations: 2341 hospitalizations during the COVID-19 pandemic (March 1 through October 30, 2020) and 6648 in the pre-COVID-19 (October 1, 2018, through February 28, 2020) comparator group. We used Poisson regression, Kaplan-Meier estimates, multivariable logistic, and Cox regression analysis to determine whether prespecified study outcomes varied by time frames. RESULTS: The adjusted 30-day readmission rate decreased from 13.1% (872 of 6648) in the pre-COVID-19 period to 10.0% (234 of 2341) in the COVID-19 pandemic period (relative risk reduction, 23%; hazard ratio, 0.77; 95% CI, 0.66 to 0.89). Conversely, all-cause mortality increased from 9.7% (645 of 6648) in the pre-COVID-19 period to 11.3% (264 of 2341) in the COVID-19 pandemic period (relative risk increase, 16%; number of admissions needed for one additional death, 62.5; hazard ratio, 1.19; 95% CI, 1.02 to 1.39). Despite significant differences in rates of index hospitalization, readmission, and mortality across the study time frames, the disease severity, HF subtypes, and treatment patterns remained unchanged (P>0.05). CONCLUSION: The findings of this large tristate multicenter cohort study of HF hospitalizations suggest lower rates of index hospitalizations and 30-day readmissions but higher incidence of 30-day mortality with broadly similar use of HF medication, surgical interventions, and devices during the COVID-19 pandemic compared with the pre-COVID-19 time frame.

Post-discharge early assessment with remote video link (PEARL) initiative for patients discharged from hospital medicine services.

OBJECTIVES: The COVID-19 pandemic impacted the availability and accessibility of outpatient care following hospital discharge. Hospitalists (physicians) and hospital medicine advanced practice providers (HM-APPs) coordinate discharge care of hospitalized patients; however, it is unknown if they can deliver post-discharge virtual care and overcome barriers to outpatient care. The objective was to develop and provide post-discharge virtual care for patients discharged from hospital medicine services. METHODS: We developed the Post-discharge Early Assessment with Remote video Link (PEARL) initiative for HM-APPs to conduct a post-discharge video visit (to review recommendations) and telephone follow-up (to evaluate adherence) with patients 2-6 days following hospital discharge. Participants included patients discharged from hospital medicine services at an institution's hospitals in Rochester (May 2020-August 2020) and Austin (November 2020-February 2021) in Minnesota, US. HM-APPs also interviewed patients about their experience with the video visit and completed a survey on their experience with PEARL. RESULTS: Of 386 eligible patients, 61.4% were enrolled (n = 237/386) including 48.1% women (n = 114/237). In patients with complete video visit and telephone follow-up (n = 141/237), most were prescribed new medications (83.7%) and took them as prescribed (93.2%). Among five classes of chronic medications, patient-reported adherence ranged from 59.2% (narcotics) to 91.5% (anti-hypertensives). Patient-reported self-management of 12 discharge recommendations ranged from 40% (smoking cessation) to 100% (checking rashes). Patients reported benefit from the video visit (agree: 77.3%) with an equivocal preference for video visits over clinic visits. Among HM-APPs who responded to the survey (88.2%; n = 15/17), 73.3% reported benefit from visual contact with patients but were uncertain if video visits would reduce emergency department visits. CONCLUSION: In this novel initiative, HM-APPs used video visits to provide care beyond their hospital role, reinforce discharge recommendations for patients, and reduce barriers to outpatient care. The effect of this initiative is under evaluation in a randomized controlled trial.

A Review Study on the Trends of Psychological Challenges, Coping Ways, and Public Support During the COVID-19 Pandemic in the Vulnerable Populations in the United States.

Background: The COVID-19 pandemic resulted in significant mortality and morbidity in the United States. The mental health impact during the pandemic was huge and affected all age groups and population types. We reviewed the existing literature to understand the present trends of psychological challenges and different coping strategies documented across different vulnerable sections of the United States population. This rapid review was carried out to investigate the trends in psychological impacts, coping ways, and public support during the COVID-19 pandemic crisis in the United States. Materials and Methods: We undertook a rapid review of the literature following the COVID-19 pandemic in the United States. We searched PubMed as it is a widely available database for observational and experimental studies that reported the psychological effects, coping ways, and public support on different age groups and healthcare workers (HCWs) during the COVID-19 pandemic. Results: We included thirty-five studies in our review and reported data predominantly from the vulnerable United States population. Our review findings indicate that COVID-19 has a considerable impact on the psychological wellbeing of various age groups differently, especially in the elderly population and HCWs. Review findings suggest that factors like children, elderly population, female gender, overconcern about family, fear of getting an infection, personality, low spirituality, and lower resilience levels were at a higher risk of adverse mental health outcomes during this pandemic. Systemic support, higher resilience levels, and adequate knowledge were identified as protecting and preventing factors. There is a paucity of similar studies among the general population, and we restricted our review specifically to vulnerable subgroups of the population. All the included studies in our review investigated and surveyed the psychological impacts, coping skills, and public support system during the COVID-19 pandemic. Conclusion: The evidence to date suggests that female gender, child and elderly population, and racial factors have been affected by a lack of support for psychological wellbeing. Further, research using our hypothesized framework might help any population group to deal with a pandemic-associated mental health crisis, and in that regard, analysis of wider societal structural factors is recommended.

Delirium occurrence and association with outcomes in hospitalized COVID-19 patients.

Delirium is reported to be one of the manifestations of coronavirus infectious disease 2019 (COVID-19) infection. COVID-19 hospitalized patients are at a higher risk of delirium. Pathophysiology behind the association of delirium and COVID-19 is uncertain. We analyzed the association of delirium occurrence with outcomes in hospitalized COVID-19 patients, across all age groups, at Mayo Clinic hospitals.A retrospective study of all hospitalized COVID-19 patients at Mayo Clinic between March 1, 2020 and December 31, 2020 was performed. Occurrence of delirium and outcomes of mortality, length of stay, readmission, and 30-day mortality after hospital discharge were measured. Chi-square test, student t-test, survival analysis, and logistic regression analysis were performed to measure and compare outcomes of delirium group adjusted for age, sex, Charlson comorbidity score, and COVID-19 severity with no-delirium group.A total of 4351 COVID-19 patients were included in the study. Delirium occurrence in the overall study population was noted to be 22.4%. The highest occurrence of delirium was also noted in patients with critical COVID-19 illness severity. A statistically significant OR 4.35 (3.27-5.83) for in-hospital mortality and an OR 4.54 (3.25-6.38) for 30-day mortality after discharge in the delirium group were noted. Increased hospital length of stay, 30-day readmission, and need for skilled nursing facility on discharge were noted in the delirium group. Delirium in hospitalized COVID-19 patients is a marker for increased mortality and morbidity. In this group, outcomes appear to be much worse when patients are older and have a critical severity of COVID-19 illness.

Severe urticarial rash as the initial symptom of COVID-19 infection.

A 54-year-old woman presented with pruritic rash and hives of 3 days' duration followed by shortness of breath for 1 day. SARS-CoV-2 PCR test for COVID-19 was positive. Cutaneous manifestations of COVID-19 include acral lesions, urticarial rash, erythematous maculopapular rash, vascular rashes and vesicular rash. The cutaneous manifestations are mostly described as self-limiting. Urticarial rashes are not reported as the initial presentation symptom of COVID-19 infection but mostly noted to occur at the same time or after the onset of non-cutaneous symptoms. Management of cutaneous manifestations of COVID-19 affecting quality of life has not been well studied. Antihistamine therapy is the primary recommended therapy. Role of antiviral therapy for severe cases of rash needs to be further assessed.