Scott D. Halpern

Rationale: The COVID-19 pandemic created a unique instance of hospital capacity strain including deviations in ICU bed utilization. Objectives: To evaluate trends in ICU utilization among patients with common critical illness syndromes before, during, and after the pandemic, and across degrees of hospital capacity strain. Methods: At 26 U.S. hospitals across two health systems, 2013–2024, we performed a retrospective cohort study among high-acuity patients with sepsis and/or acute respiratory failure (ARF) who did not require mechanical ventilation or vasopressor support in the emergency department. We modeled ICU admission rates and hospital mortality across eras and associations between validated hospital strain indices and ICU admission. Measurements and Main Results: ICU admission rates decreased markedly from the pre-pandemic to the pandemic era and were sustained in the post-pandemic era: sepsis (n = 136,153) 24% (24-24%) pre-pandemic, 16% (15-16%) pandemic, and 14% (14-14%) post-pandemic; ARF (n = 63,290) 36% (35-36%) pre-pandemic, 25% (25-26%) pandemic, and 23% (22-24%) post-pandemic; all p < 0.001. Increasing hospital capacity strain was associated with reduced predicted probability of ICU admission (sepsis: 29% [29-30%] ICU admission at lowest strain to 9% [8-9%] at highest strain; ARF: 51% [49-52%] at lowest strain to 15% [14-16%] at highest strain; all p < 0.001). Compared to the pre-pandemic era, in the post-pandemic era patients with sepsis (11% [11-11%] vs. 14% [13-14%]) and ARF (12% [11-12%] vs. 14% [14-15%]) had reduced mortality (both p < 0.001). Conclusions: Among high acuity patients with sepsis and ARF who did not require initial life support, ICU admission rates decreased during and after the pandemic.

Background: The Epic End of Life Care Index (EOLCI) predicts one-year mortality and was developed to improve serious illness care. However, prior external EOLCI evaluations had limited sample sizes, populations, and equity evaluations. In preparation for a multi-system pragmatic clinical trial, we sought to evaluate the EOLCI performance and equity in the trial’s two participating health systems. Objective: Evaluate EOLCI model performance overall and across key subgroups. Design/Setting/Patients: Retrospective cohort study of patients hospitalized for ≥36 hours in 2022 to 39 hospitals in the Trinity Health and Kaiser Permanente Southern California (KPSC) health systems. Measurements: We predicted one-year mortality risk stratified by health system using the EOLCI, a logistic regression model including age, sex, race/ethnicity, ethnicity, insurance, and diagnoses. We evaluated model performance using Scaled Brier Scores (SBS; range -1 to 1; composite measures of calibration and discrimination), calibration plots, and c-statistics. Results: Among 116,749 Trinity patients with 154,063 encounters, 12,054 (10.3%) patients died within one year. Among 94,489 KPSC patients with 133,043 encounters, 16,872 (17.9%) died within one year. The SBS was -0.007 at Trinity and 0.178 at KPSC. Calibration was poor for both. Trinity’s discrimination was acceptable/good (c-statistic 0.76, 95% CI 0.76-0.77), and KPSC’s was good/very good (c-statistic 0.81, 95% CI 0.81-0.81). Model performance across subgroups was similar to the overall cohort. Limitations: Death data were collected exclusively within Trinity and KPSC, risking outcome misclassification; several subgroup evaluations were limited by small sample sizes. Conclusions: An external evaluation of the widely available Epic EOLCI demonstrated adequate to very good discrimination, poor calibration, and equitable performance across sociodemographic characteristics and diagnoses in two of the nation’s largest health systems. Primary funding source: PCORI PLACER-2022C3-30553.

Rationale: Patients with sepsis and/or acute respiratory failure are at high risk for death or long hospital stays, yet limited evidence exists to guide triage to intensive care units (ICUs) or general medical wards for the majority of these patients who do not initially require life support. Objectives: To identify factors that influence how hospitals triage patients with capacity-sensitive conditions and those factors that may account for observed ICU relative to ward, or ward relative to ICU, benefits for such patients. Methods: We conducted an explanatory sequential mixed-methods study. As part of a 27-hospital, two–health system retrospective cohort study, we calculated hospital-specific measurements of ICU net benefit for patients with sepsis and/or acute respiratory failure. Hospitals among the highest ICU net benefit and lowest ICU net benefit (or highest ward net benefit) from each study health system were selected for in-depth qualitative study. At each hospital, interviews were conducted with emergency department, ward, and ICU clinicians and administrators. Interview transcripts were analyzed using flexible coding and the framework method. Results: Interviews were conducted with 118 respondents (46 physicians, 43 nurses, 5 advanced practice providers, and 24 administrators) from four hospitals. Respondents across hospitals agreed that the prediction of patient trajectory is central to triage decisions, but there was variation in opinion across work locations about optimal pretriage emergency department interventions in terms of intensity, repetition, clinical reassessment, and observation duration. The main difference observed between high and low ICU net benefit hospitals related to the way respondents working in the ICU and ward described their responses to patients who experience rapid clinical deviations from triage-expected trajectories, including sustained lack of critical care needs after admission to the ICU and acute critical care needs after admission to the ward. Hospitals with low ICU net benefit (or high ward net benefit) had particularly robust and proactive rapid response and clinical decompensation surveillance practices for ward-admitted patients. Conclusions: Particularly proactive rapid response programs that deliver on-location critical care may quantitatively increase ward net benefit by bringing ICU benefits without ICU-associated harms to ward patients who become critically ill.

Background: Height recorded in electronic health records (EHRs) is used extensively in diagnosis and treatment, either in isolation or as a component of body-mass index (BMI), but is often falsely high because many adults overestimate their height. Statistical models to predict height could therefore improve population health, but to date models have required extensive input and have not been externally validated. Methods: We used the National Health and Nutrition Examination Survey (NHANES) to develop sex-stratified predictive models for examiner-measured height based on self-reported height and age in a random 90% sample of data. We internally validated the model in a held-out 10% sample and externally validated the model in two cohorts: The National Adolescent to Adult Longitudinal Health Study (Add Health) and the University of Michigan Health and Retirement Study (HRS). We assessed discrimination with C-index, calibration by visual inspection of calibration plots, and accuracy using root mean square error (RMSE). Results: Models were trained using 62,032 NHANES subjects (51.9% women, 21.7% Black, 23.9% Hispanic or Latino, with median age 48 [IQR 31 – 64]), and evaluated in the NHANES held-out test set (n=6,846), Add Health (n=5,749), and HRS (n=5,655). Models demonstrated excellent discrimination in all validation cohorts (C-index range 0.88 – 0.89). Models were well-calibrated in all validation cohorts. Model-predicted height demonstrated lower root mean square error (RMSE) compared to self-reported height in all validation cohorts and when stratified by race and ethnicity, with greatest improvements in participants aged 45 and over. Conclusions and Relevance: A model requiring minimal input data improves estimation of height over self-reported height at least as much as more complex models across stratifications of sex, age, race and ethnicity in internal validation, and is the first model to improve height estimation that has demonstrated external validity.

BACKGROUND: Guideline-directed medical therapy for heart failure (HF) with reduced ejection fraction can entail high out-of-pocket (OOP) costs, prompting concerns about financial toxicity and access. OOP costs are generally unavailable during encounters. This trial assessed the impact of providing patient-specific OOP costs to patients and clinicians. METHODS: This trial was conducted between June 2021 and August 2023 at 6 clinics in 2 health systems using a stepped-wedge, clinic-level cluster-randomized design. Adult patients with HF with reduced ejection fraction (left ventricular ejection fraction ≤40%) were enrolled. The intervention was built upon the EPIC-HF (Electronically Delivered, Patient-Activation Tool for Intensification of Medications for Chronic Heart Failure with Reduced Ejection Fraction) checklist of approved HF with reduced ejection fraction medications. Patients and clinicians received this checklist with (intervention) or without (control) patient-specific OOP cost estimates for higher-cost medications at the time of encounter. Estimates were obtained by providing pharmacy benefit information to a financial navigation firm. Encounters were audio-recorded, and patients were surveyed 2 weeks later. The primary outcome was cost-informed decision-making, defined by mentioning HF medication cost during the encounter. The primary analysis used a generalized linear mixed model. Secondary outcomes were assessed via transcript subcoding and analysis of survey responses. RESULTS: Demographic characteristics of 247 patients (mean age, 62.9 years; 29.5% female; 26.3% Black; and 3.2% Hispanic/LatinX) treated by 39 clinicians in intervention and control periods were similar. In the primary model, the rate of cost-informed decision-making was higher in the intervention group than the control group (68% versus 49%; P =0.021). Baseline rates of cost discussions and the impact of the intervention varied across sites. When cost discussions were present, fewer discussions in the intervention group involved contingency plans to address potential costs (16.5% versus 31.9%; P =0.028). Most other secondary outcomes were not significantly different. CONCLUSIONS: Disclosing comprehensive OOP medication costs to patients with HF with reduced ejection fraction increased cost-informed decision-making. Further work is needed to optimize implementation and assess the impact on medication choices and adherence. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04793880.

Distracted driving is responsible for nearly 1 million crashes each year in the United States alone, and a major source of driver distraction is handheld phone use. We conducted a randomized, controlled trial to compare the effectiveness of interventions designed to create sustained reductions in handheld use while driving (NCT04587609). Participants were 1,653 consenting Progressive® Snapshot® usage-based auto insurance customers ages 18 to 77 who averaged at least 2 min/h of handheld use while driving in the month prior to study invitation. They were randomly assigned to one of five arms for a 10-wk intervention period. Arm 1 (control) got education about the risks of handheld phone use, as did the other arms. Arm 2 got a free phone mount to facilitate hands-free use. Arm 3 got the mount plus a commitment exercise and tips for hands-free use. Arm 4 got the mount, commitment, and tips plus weekly goal gamification and social competition. Arm 5 was the same as Arm 4, plus offered behaviorally designed financial incentives. Postintervention, participants were monitored until the end of their insurance rating period, 25 to 65 d more. Outcome differences were measured using fractional logistic regression. Arm 4 participants, who received gamification and competition, reduced their handheld use by 20.5% relative to control ( P < 0.001); Arm 5 participants, who additionally received financial incentives, reduced their use by 27.6% ( P < 0.001). Both groups sustained these reductions through the end of their insurance rating period.

Background: Women are more likely than men to report delays in the diagnosis of chronic obstructive pulmonary disease (COPD), though the etiology of these delays is unknown. We sought to test whether delays in COPD diagnosis persist after the performance of spirometry. Methods: We used the Optum Labs Data Warehouse to identify patients 18 years of age and older without a prior diagnosis of COPD, with a post-bronchodilator forced expiratory volume in 1 second (FEV ₁ ) to forced vital capacity (FVC) ratio of less than 0.7 on spirometry. We used a Cox proportional hazards model to compare the time to diagnosis after spirometry in men and women, adjusting for age, race, ethnicity, tobacco use, and post-bronchodilator FEV ₁ /FVC. Results: The probability of receiving a COPD diagnosis after the performance of spirometry was lower among women than men (adjusted hazard ratio [aHR] 0.66, 95% confidence interval [CI] 0.50 to 0.88) Conclusion: In this retrospective cohort study of patients with spirometric evidence of obstruction, the time to diagnosis of COPD was greater among women than men. While previous vignette-based studies have found that gender differences in the diagnosis of COPD resolve with the performance of spirometry, we found that gender differences persist after spirometry has been performed. Clinicians were less likely to diagnose COPD in women even when spirometry supported this diagnosis.

Background: “Aging in place” (AIP), the ability to remain in one’s home with age, has broad appeal to policy makers and professionals providing services to adults with serious illness. AIP is viewed as both an intervention for people with dementia (PWD) and as a desirable outcome. However, it’s not clear that AIP is always associated with sustained quality of life, and in some circumstances, may hinder it. As clinical and policy efforts increase to promote AIP for PWD, it is imperative to understand how AIP aligns with patient and family values and what factors influence choice and ability to remain in one’s home.Method: In this qualitative study, we explored stakeholders’ perspectives on what makes a “good day” for a PWD and their family caregivers and decision making around AIP. We conducted semi‐structured interviews among PWD or cognitive impairment, family caregivers of PWD or cognitive impairment, and clinicians who care for PWD. Participants were purposively sampled to enroll individuals with a range of dementia severity, professional expertise, and demographic characteristics. All interviews were audio‐recorded and transcribed. De‐identified transcripts were reviewed by the research team independently and during weekly consensus meetings to identify relevant themes. Sample size was determined by reaching thematic saturation within each stakeholder sub‐group.Result: We conducted 70 interviews among 13 patients, 33 caregivers, and 24 clinicians (Table 1). Caregiver burden, caregiver guilt, patient independence, patient safety, perceptions of care facilities, and financial consideration were all themes that influence whether a person can and will AIP (Table 2). Among patient‐caregiver dyads who wished to prioritize AIP, a change in the patient’s living situation was only pursued if and when a “breaking point” was reached by the caregiver. Themes were organized in a conceptual model as patient, caregiver, or systems factors (Figure).Conclusion: Numerous factors influence the ability and choice of PWD and their family caregivers to AIP and likely impact the quality of life of patient and family caregivers as dementia progresses. Any program seeking to enhance AIP must take these factors into account. Furthermore, measuring success of AIP will need outcome measures that better capture these dimensions.

Background: Composite measures of survival and residence, such as institution‐free days (IFDs), encompass many patient and family priorities and are readily measured using payer claims or electronic health record data. However, knowledge gaps limit their application to studies of people with dementia (PWD). First, PWD, family care partners, and clinician perspectives on survival‐residence composite outcomes are unknown. Second, approaches to measuring IFDs consider all institution days equally poor and all home days equally well, which may be inconsistent with stakeholder assessments.Method: We conducted a qualitative study to explore stakeholders’ perspectives on what makes a “good day” for a PWD. This included semi‐structured interviews with clinicians who provide care to PWD. Clinicians were also asked for their opinions regarding the use of survival‐residence composite outcomes in dementia research. Interviews were audio‐recorded and professionally transcribed. De‐identified transcripts were reviewed by the research team independently and during weekly consensus meetings to identify relevant themes.Result: Thematic saturation was reached after 24 interviews. Nearly half of clinicians also had personal experience as a care partner of a PWD. Participant characteristics are summarized in Table 1. Salient themes were identified and grouped into 2 major categories: (1) attributes of quality of days for PWD, and (2) impressions of survival‐residence composite outcomes (Table 2). Key attributes of quality of days were safety, socialization and engagement, and neuropsychiatric distress. These qualities were more important in defining “home” than type of residence (Figure). Clinicians appreciated that a survival‐residence composite outcome, such as IFDs, could capture the important aspects of “aging in place” and avoiding burdensome hospitalizations. They also noted a desire for such a measure to capture the quality of those days. Concerns were raised over how differential access to home‐based services due to socioeconomic factors would influence patient accrual of IFDs and whether such a measure might also increase existing stigma around institutions.Conclusion: Future work will integrate these findings with the perspectives of PWD and their family care partners as well as further explore the relative values of these attributes of a survival‐residence composite outcome for studies of patients with ADRD.