Intensivist physician-to-patient ratios and mortality in the intensive care unit.

PURPOSE: A high daily census may hinder the ability of physicians to deliver quality care in the intensive care unit (ICU). We sought to determine the relationship between intensivist-to-patient ratios and mortality among ICU patients. METHODS: We performed a retrospective cohort study of intensivist-to-patient ratios in 29 ICUs in 10 hospitals in the United States from 2018 to 2020. We used meta-data from progress notes in the electronic health record to determine an intensivist-specific caseload for each ICU day. We then fit a multivariable proportional hazards model with time-varying covariates to estimate the relationship between the daily intensivist-to-patient ratio and ICU mortality at 28 days. RESULTS: The final analysis included 51,656 patients, 210,698 patient days, and 248 intensivist physicians. The average caseload per day was 11.8 (standard deviation: 5.7). There was no association between the intensivist-to-patient ratio and mortality (hazard ratio for each additional patient: 0.987, 95% confidence interval: 0.968-1.007, p = 0.2). This relationship persisted when we defined the ratio as caseload over the sample-wide average (hazard ratio: 0.907, 95% confidence interval: 0.763-1.077, p = 0.26) and cumulative days with a caseload over the sample-wide average (hazard ratio: 0.991, 95% confidence interval: 0.966-1.018, p = 0.52). The relationship was not modified by the presence of physicians-in-training, nurse practitioners, and physician assistants (p value for interaction term: 0.14). CONCLUSIONS: Mortality for ICU patients appears resistant to high intensivist caseloads. These results may not generalize to ICUs organized differently than those in this sample, such as ICUs outside the United States.

Adoption and Deadoption of Medications to Treat Hospitalized Patients With COVID-19.

OBJECTIVES: The COVID-19 pandemic was characterized by rapidly evolving evidence regarding the efficacy of different therapies, as well as rapidly evolving health policies in response to that evidence. Data on adoption and deadoption are essential as we learn from this pandemic and prepare for future public health emergencies. DESIGN: We conducted an observational cohort study in which we determined patterns in the use of multiple medications to treat COVID-19: remdesivir, hydroxychloroquine, IV corticosteroids, tocilizumab, heparin-based anticoagulants, and ivermectin. We analyzed changes both overall and within subgroups of critically ill versus Noncritically ill patients. SETTING: Data from Optum's deidentified Claims-Clinical Dataset, which contains multicenter electronic health record data from U.S. hospitals. PATIENTS: Adults hospitalized with COVID-19 from January 2020 to June 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 141,533 eligible patients, 34,515 (24.4%) required admission to an ICU, 14,754 (10.4%) required mechanical ventilation, and 18,998 (13.4%) died during their hospitalization. Averaged over the entire time period, corticosteroid use was most common (47.0%), followed by remdesivir (33.2%), anticoagulants (19.3%), hydroxychloroquine (7.3%), and tocilizumab (3.4%). Usage patterns varied substantially across treatments. For example, hydroxychloroquine use peaked in March 2020 and leveled off to near zero by June 2020, whereas the use of remdesivir, corticosteroids, and tocilizumab all increased following press releases announcing positive results of large international trials. Ivermectin use increased slightly over the study period but was extremely rare overall (0.4%). CONCLUSIONS: During the COVID-19 pandemic, medication treatment patterns evolved reliably in response to emerging evidence and changes in policy. These findings may inform efforts to promote optimal adoption and deadoption of treatments for acute care conditions.

Willingness to Treat with Therapies of Unknown Effectiveness in Severe COVID-19: A Survey of Intensivist Physicians.

Rationale: Little is known about how physicians develop their beliefs about new treatments or update their beliefs in the face of new clinical evidence. These issues are particularly salient in the context of the coronavirus disease (COVID-19) pandemic, which created rapid demand for novel therapies in the absence of robust evidence. Objectives: To identify psychological traits associated with physicians' willingness to treat with unproven therapies and willingness to update their treatment preferences in the setting of new evidence in the context of COVID-19. Methods: We administered a longitudinal e-mail survey to United States physicians board certified in intensive care medicine in April and May 2020 (phase one) and October and November 2020 (phase two). We assessed five psychological traits potentially related to evidence uptake: need for cognition, evidence skepticism, need for closure, risk tolerance, and research engagement. We then examined the relationship between these traits and physician preferences for pharmacological treatment for a hypothetical patient with severe COVID-19 pneumonia. Results: There were 592 responses to the phase one survey, conducted prior to publication of trial data. At this time physicians were most willing to treat with macrolide antibiotics (50.5%), followed by antimalaria agents (36.1%), corticosteroids (24.5%), antiretroviral agents (22.6%), and angiotensin inhibitors (4.4%). Greater evidence skepticism (relative risk [RR], 1.40; 95% confidence interval [CI], 1.30-1.52; P < 0.001), greater need for closure (RR, 1.19; 95% CI, 1.06-1.34; P = 0.003), and greater risk tolerance (RR, 1.17; 95% CI, 1.08-1.26; P < 0.001) were associated with an increased willingness to treat, whereas greater need for cognition (RR, 0.85; 95% CI, 0.75-0.96, P = 0.010) and greater research engagement (RR, 0.91; 95% CI, 0.88-0.95; P < 0.0001) were associated with decreased willingness to treat. In phase two, most physicians updated their beliefs after publication of trial data about antimalarial agents and corticosteroids. Physicians with greater evidence skepticism were more likely to persist in their beliefs. Conclusions: Psychological traits associated with clinical decisions in the setting of uncertain evidence may provide insight into strategies to better align clinical practice with published evidence.

Actions Taken by US Hospitals to Prepare for Increased Demand for Intensive Care During the First Wave of COVID-19: A National Survey.

BACKGROUND: The COVID-19 pandemic placed considerable strain on critical care resources. How US hospitals responded to this crisis is unknown. RESEARCH QUESTION: What actions did US hospitals take to prepare for a potential surge in demand for critical care services in the context of the COVID-19 pandemic? STUDY DESIGN AND METHODS: From September to November 2020, the chief nursing officers of a representative sample of US hospitals were surveyed regarding organizational actions taken to increase or maintain critical care capacity during the COVID-19 pandemic. Weighted proportions of hospitals for each potential action were calculated to create estimates across the entire population of US hospitals, accounting for both the sampling strategy and nonresponse. Also examined was whether the types of actions taken varied according to the cumulative regional incidence of COVID-19 cases. RESULTS: Responses were received from 169 of 540 surveyed US hospitals (response rate, 31.3%). Almost all hospitals canceled or postponed elective surgeries (96.7%) and nonsurgical procedures (94.8%). Few hospitals created new medical units in areas not typically dedicated to health care (12.9%), and almost none adopted triage protocols (5.6%) or protocols to connect multiple patients to a single ventilator (4.8%). Actions to increase or preserve ICU staff, including use of ICU telemedicine, were highly variable, without any single dominant strategy. Hospitals experiencing a higher incidence of COVID-19 did not consistently take different actions compared with hospitals facing lower incidence. INTERPRETATION: Responses of hospitals to the mass need for critical care services due to the COVID-19 pandemic were highly variable. Most hospitals canceled procedures to preserve ICU capacity and scaled up ICU capacity using existing clinical space and staffing. Future research linking hospital response to patient outcomes can inform planning for additional surges of this pandemic or other events in the future.