Integrating Cost into Shared Decision-Making for Heart Failure with Reduced Ejection Fraction (POCKET-COST-HF): A Trial Providing Out-of-Pocket Costs for Heart Failure Medications during Clinical Encounters.

BACKGROUND: Evidence-based medical therapy for heart failure with reduced ejection fraction (HFrEF) often entails substantial out-of-pocket costs that can vary appreciably between patients. This has raised concerns regarding financial toxicity, equity, and adherence to medical therapy. In spite of these concerns, cost discussions in the HFrEF population appear to be rare, partly because out-of-pocket costs are generally unavailable during clinical encounters. In this trial, out-of-pocket cost information is given to patients and clinicians during outpatient encounters with the aim to assess the impact of providing this information on medication discussions and decisions. HYPOTHESIS: Cost-informed decision-making will be facilitated by providing access to patient-specific out-of-pocket cost estimates at the time of clinical encounter. DESIGN: Integrating Cost into Shared Decision-Making for Heart Failure with Reduced Ejection Fraction (POCKET-COST-HF) is a multicenter trial based at Emory Healthcare and University of Colorado Health. Adapting an existing patient activation tool from the EPIC-HF trial, patients and clinicians are presented a checklist with medications approved for treatment of HFrEF with or without patient-specific out-of-pocket costs (obtained from a financial navigation firm). Clinical encounters are audio-recorded, and patients are surveyed about their experience. The trial utilizes a stepped-wedge cluster randomized design, allowing for each site to enroll control and intervention group patients while minimizing contamination of the control arm. DISCUSSION: This trial will elucidate the potential impact of robust cost disclosure efforts and key information regarding patient and clinician perspectives related to cost and cost communication. It also will reveal important challenges associated with providing out-of-pocket costs for medications during clinical encounters. Acquiring medication costs for this trial requires an involved process and outsourcing of work. In addition, costs may change throughout the year, raising questions regarding what specific information is most valuable. These data will represent an important step towards understanding the role of integrating cost discussions into heart failure care. GOV IDENTIFIER: NCT04793880.

Classification of Documented Goals of Care Among Hospitalized Patients with High Mortality Risk: a Mixed-Methods Feasibility Study.

BACKGROUND: The ability to classify patients' goals of care (GOC) from clinical documentation would facilitate serious illness communication quality improvement efforts and pragmatic measurement of goal-concordant care. Feasibility of this approach remains unknown. OBJECTIVE: To evaluate the feasibility of classifying patients' GOC from clinical documentation in the electronic health record (EHR), describe the frequency and patterns of changes in patients' goals over time, and identify barriers to reliable goal classification. DESIGN: Retrospective, mixed-methods chart review study. PARTICIPANTS: Adults with high (50-74%) and very high (≥ 75%) 6-month mortality risk admitted to three urban hospitals. MAIN MEASURES: Two physician coders independently reviewed EHR notes from 6 months before through 6 months after admission to identify documented GOC discussions and classify GOC. GOC were classified into one of four prespecified categories: (1) comfort-focused, (2) maintain or improve function, (3) life extension, or (4) unclear. Coder interrater reliability was assessed using kappa statistics. Barriers to classifying GOC were assessed using qualitative content analysis. KEY RESULTS: Among 85 of 109 (78%) patients, 338 GOC discussions were documented. Inter-rater reliability was substantial (75% interrater agreement; Cohen's kappa = 0.67; 95% CI, 0.60-0.73). Patients' initial documented goal was most frequently "life extension" (N = 37, 44%), followed by "maintain or improve function" (N = 28, 33%), "unclear" (N = 17, 20%), and "comfort-focused" (N = 3, 4%). Among the 66 patients whose goals' classification changed over time, most changed to "comfort-focused" goals (N = 49, 74%). Primary reasons for unclear goals were the observation of concurrently held or conditional goals, patient and family uncertainty, and limited documentation. CONCLUSIONS: Clinical notes in the EHR can be used to reliably classify patients' GOC into discrete, clinically germane categories. This work motivates future research to use natural language models to promote scalability of the approach in clinical care and serious illness research.

A mixed model approach to estimate the survivor average causal effect in cluster-randomized trials.

In many medical studies, the outcome measure (such as quality of life, QOL) for some study participants becomes informatively truncated (censored, missing, or unobserved) due to death or other forms of dropout, creating a nonignorable missing data problem. In such cases, the use of a composite outcome or imputation methods that fill in unmeasurable QOL values for those who died rely on strong and untestable assumptions and may be conceptually unappealing to certain stakeholders when estimating a treatment effect. The survivor average causal effect (SACE) is an alternative causal estimand that surmounts some of these issues. While principal stratification has been applied to estimate the SACE in individually randomized trials, methods for estimating the SACE in cluster-randomized trials are currently limited. To address this gap, we develop a mixed model approach along with an expectation-maximization algorithm to estimate the SACE in cluster-randomized trials. We model the continuous outcome measure with a random intercept to account for intracluster correlations due to cluster-level randomization, and model the principal strata membership both with and without a random intercept. In simulations, we compare the performance of our approaches with an existing fixed-effects approach to illustrate the importance of accounting for clustering in cluster-randomized trials. The methodology is then illustrated using a cluster-randomized trial of telecare and assistive technology on health-related QOL in the elderly.

How do surrogates make treatment decisions for patients with dementia: An experimental survey study.

Despite the growing need for surrogate decision-making for older adults, little is known about how surrogates make decisions and whether advance directives would change decision-making. We conducted a nationally representative experimental survey that cross-randomized cognitive impairment, gender, and characteristics of advance care planning among hospitalized older adults through a series of vignettes. Our study yielded three main findings: first, respondents were much less likely to recommend life-sustaining treatments for patients with dementia, especially after personal exposure. Second, respondents were more likely to ignore patient preferences for life-extending treatment when the patient had dementia, and choose unwanted life-extending treatments for patients without dementia. Third, in scenarios where the patient's wishes were unclear, respondents were more likely to choose treatments that matched their own preferences. These findings underscore the need for improved communication and decision-making processes for patients with cognitive impairment and highlight the importance of choosing a surrogate decision-maker with similar treatment preferences.

Structured Mobilization for Critically Ill Patients: A Pragmatic Cluster-randomized Trial.

Rationale: Small trials and professional recommendations support mobilization interventions to improve recovery among critically ill patients, but their real-world effectiveness is unknown. Objective: To evaluate a low-cost, multifaceted mobilization intervention. Methods: We conducted a stepped-wedge cluster-randomized trial across 12 ICUs with diverse case mixes. The primary and secondary samples included patients mechanically ventilated for ⩾48 hours who were ambulatory before admission, and all patients with ICU stays ⩾48 hours, respectively. The mobilization intervention included 1) designation and posting of daily mobilization goals; 2) interprofessional closed-loop communication coordinated by each ICU's facilitator; and 3) performance feedback. Measurements and Main Results: From March 4, 2019 through March 15, 2020, 848 and 1,069 patients were enrolled in the usual care and intervention phases in the primary sample, respectively. The intervention did not increase the primary outcome, patient's maximal Intensive Care Mobility Scale (range, 0-10) score within 48 hours before ICU discharge (estimated mean difference, 0.16; 95% confidence interval, -0.31 to 0.63; P = 0.51). More patients in the intervention (37.2%) than usual care (30.7%) groups achieved the prespecified secondary outcome of ability to stand before ICU discharge (odds ratio, 1.48; 95% confidence interval, 1.02 to 2.15; P = 0.04). Similar results were observed among the 7,115 patients in the secondary sample. The percentage of days on which patients received physical therapy mediated 90.1% of the intervention effect on standing. ICU mortality (31.5% vs. 29.0%), falls (0.7% vs. 0.4%), and unplanned extubations (2.0% vs. 1.8%) were similar between groups (all P > 0.3). Conclusions: A low-cost, multifaceted mobilization intervention did not improve overall mobility but improved patients' odds of standing and was safe. Clinical trial registered with www.clinicaltrials.gov (NCT03863470).

Default Palliative Care Consultation for Seriously Ill Hospitalized Patients: A Pragmatic Cluster Randomized Trial.

Importance: Increasing inpatient palliative care delivery is prioritized, but large-scale, experimental evidence of its effectiveness is lacking. Objective: To determine whether ordering palliative care consultation by default for seriously ill hospitalized patients without requiring greater palliative care staffing increased consultations and improved outcomes. Design, Setting, and Participants: A pragmatic, stepped-wedge, cluster randomized trial was conducted among patients 65 years or older with advanced chronic obstructive pulmonary disease, dementia, or kidney failure admitted from March 21, 2016, through November 14, 2018, to 11 US hospitals. Outcome data collection ended on January 31, 2019. Intervention: Ordering palliative care consultation by default for eligible patients, while allowing clinicians to opt-out, was compared with usual care, in which clinicians could choose to order palliative care. Main Outcomes and Measures: The primary outcome was hospital length of stay, with deaths coded as the longest length of stay, and secondary end points included palliative care consult rate, discharge to hospice, do-not-resuscitate orders, and in-hospital mortality. Results: Of 34 239 patients enrolled, 24 065 had lengths of stay of at least 72 hours and were included in the primary analytic sample (10 313 in the default order group and 13 752 in the usual care group; 13 338 [55.4%] women; mean age, 77.9 years). A higher percentage of patients in the default order group received palliative care consultation than in the standard care group (43.9% vs 16.6%; adjusted odds ratio [aOR], 5.17 [95% CI, 4.59-5.81]) and received consultation earlier (mean [SD] of 3.4 [2.6] days after admission vs 4.6 [4.8] days; P < .001). Length of stay did not differ between the default order and usual care groups (percent difference in median length of stay, -0.53% [95% CI, -3.51% to 2.53%]). Patients in the default order group had higher rates of do-not-resuscitate orders at discharge (aOR, 1.40 [95% CI, 1.21-1.63]) and discharge to hospice (aOR, 1.30 [95% CI, 1.07-1.57]) than the usual care group, and similar in-hospital mortality (4.7% vs 4.2%; aOR, 0.86 [95% CI, 0.68-1.08]). Conclusions and Relevance: Default palliative care consult orders did not reduce length of stay for older, hospitalized patients with advanced chronic illnesses, but did improve the rate and timing of consultation and some end-of-life care processes. Trial Registration: ClinicalTrials.gov Identifier: NCT02505035.

The Conditional Effects of Multimorbidity on Operative Versus Nonoperative Management of Emergency General Surgery Conditions: A Retrospective Observational Study Using an Instrumental Variable Analysis.

OBJECTIVE: To understand how multimorbidity impacts operative versus nonoperative management of emergency general surgery (EGS) conditions. BACKGROUND: EGS is a heterogenous field, encompassing operative and nonoperative treatment options. Decision-making is particularly complex for older patients with multimorbidity. METHODS: Using an instrumental variable approach with near-far matching, this national, retrospective observational cohort study of Medicare beneficiaries examines the conditional effects of multimorbidity, defined using qualifying comorbidity sets, on operative versus nonoperative management of EGS conditions. RESULTS: Of 507,667 patients with EGS conditions, 155,493 (30.6%) received an operation. Overall, 278,836 (54.9%) were multimorbid. After adjustment, multimorbidity significantly increased the risk of in-hospital mortality associated with operative management for general abdominal patients (+9.8%; P = 0.002) and upper gastrointestinal patients (+19.9%, P < 0.001) and the risk of 30-day mortality (+27.7%, P < 0.001) and nonroutine discharge (+21.8%, P = 0.007) associated with operative management for upper gastrointestinal patients. Regardless of multimorbidity status, operative management was associated with a higher risk of in-hospital mortality among colorectal patients (multimorbid: + 12%, P < 0.001; nonmultimorbid: +4%, P = 0.003), higher risk of nonroutine discharge among colorectal (multimorbid: +42.3%, P < 0.001; nonmultimorbid: +55.1%, P < 0.001) and intestinal obstruction patients (multimorbid: +14.6%, P = 0.001; nonmultimorbid: +14.8%, P = 0.001), and lower risk of nonroutine discharge (multimorbid: -11.5%, P < 0.001; nonmultimorbid: -11.9%, P < 0.001) and 30-day readmissions (multimorbid: -8.2%, P = 0.002; nonmultimorbid: -9.7%, P < 0.001) among hepatobiliary patients. CONCLUSIONS: The effects of multimorbidity on operative versus nonoperative management varied by EGS condition category. Physicians and patients should have honest conversations about the expected risks and benefits of treatment options, and future investigations should aim to understand the optimal management of multimorbid EGS patients.

Prediction of In-hospital Mortality Among Intensive Care Unit Patients Using Modified Daily Laboratory-based Acute Physiology Score, Version 2.

BACKGROUND: Mortality prediction for intensive care unit (ICU) patients frequently relies on single ICU admission acuity measures without accounting for subsequent clinical changes. OBJECTIVE: Evaluate novel models incorporating modified admission and daily, time-updating Laboratory-based Acute Physiology Score, version 2 (LAPS2) to predict in-hospital mortality among ICU patients. RESEARCH DESIGN: Retrospective cohort study. PATIENTS: ICU patients in 5 hospitals from October 2017 through September 2019. MEASURES: We used logistic regression, penalized logistic regression, and random forest models to predict in-hospital mortality within 30 days of ICU admission using admission LAPS2 alone in patient-level and patient-day-level models, or admission and daily LAPS2 at the patient-day level. Multivariable models included patient and admission characteristics. We performed internal-external validation using 4 hospitals for training and the fifth for validation, repeating analyses for each hospital as the validation set. We assessed performance using scaled Brier scores (SBS), c -statistics, and calibration plots. RESULTS: The cohort included 13,993 patients and 107,699 ICU days. Across validation hospitals, patient-day-level models including daily LAPS2 (SBS: 0.119-0.235; c -statistic: 0.772-0.878) consistently outperformed models with admission LAPS2 alone in patient-level (SBS: 0.109-0.175; c -statistic: 0.768-0.867) and patient-day-level (SBS: 0.064-0.153; c -statistic: 0.714-0.861) models. Across all predicted mortalities, daily models were better calibrated than models with admission LAPS2 alone. CONCLUSIONS: Patient-day-level models incorporating daily, time-updating LAPS2 to predict mortality among an ICU population performs as well or better than models incorporating modified admission LAPS2 alone. The use of daily LAPS2 may offer an improved tool for clinical prognostication and risk adjustment in research in this population.

Association of ICU Admission and Outcomes in Sepsis and Acute Respiratory Failure.

Rationale: Many decisions to admit patients to the ICU are not grounded in evidence regarding who benefits from such triage, straining ICU capacity and limiting its cost-effectiveness. Objectives: To measure the benefits of ICU admission for patients with sepsis or acute respiratory failure. Methods: At 27 United States hospitals across two health systems from 2013 to 2018, we performed a retrospective cohort study using two-stage instrumental variable quantile regression with a strong instrument (hospital capacity strain) governing ICU versus ward admission among high-acuity patients (i.e., laboratory-based acute physiology score v2 ⩾ 100) with sepsis and/or acute respiratory failure who did not require mechanical ventilation or vasopressors in the emergency department. Measurements and Main Results: Among patients with sepsis (n = 90,150), admission to the ICU was associated with a 1.32-day longer hospital length of stay (95% confidence interval [CI], 1.01-1.63; P < 0.001) (when treating deaths as equivalent to long lengths of stay) and higher in-hospital mortality (odds ratio, 1.48; 95% CI, 1.13-1.88; P = 0.004). Among patients with respiratory failure (n = 45,339), admission to the ICU was associated with a 0.82-day shorter hospital length of stay (95% CI, -1.17 to -0.46; P < 0.001) and reduced in-hospital mortality (odds ratio, 0.75; 95% CI, 0.57-0.96; P = 0.04). In sensitivity analyses of length of stay, excluding, ignoring, or censoring death, results were similar in sepsis but not in respiratory failure. In subgroup analyses, harms of ICU admission for patients with sepsis were concentrated among older patients and those with fewer comorbidities, and the benefits of ICU admission for patients with respiratory failure were concentrated among older patients, highest-acuity patients, and those with more comorbidities. Conclusions: Among high-acuity patients with sepsis who did not require life support in the emergency department, initial admission to the ward, compared with the ICU, was associated with shorter length of stay and improved survival, whereas among patients with acute respiratory failure, triage to the ICU compared with the ward was associated with improved survival.

A Data-Driven Analysis of Ward Capacity Strain Metrics That Predict Clinical Outcomes Among Survivors of Acute Respiratory Failure.

Supply-demand mismatch of ward resources ("ward capacity strain") alters care and outcomes. Narrow strain definitions and heterogeneous populations limit strain literature. Evaluate the predictive utility of a large set of candidate strain variables for in-hospital mortality and discharge destination among acute respiratory failure (ARF) survivors. In a retrospective cohort of ARF survivors transferred from intensive care units (ICUs) to wards in five hospitals from 4/2017-12/2019, we applied 11 machine learning (ML) models to identify ward strain measures during the first 24 hours after transfer most predictive of outcomes. Measures spanned patient volume (census, admissions, discharges), staff workload (medications administered, off-ward transports, transfusions, isolation precautions, patients per respiratory therapist and nurse), and average patient acuity (Laboratory Acute Physiology Score version 2, ICU transfers) domains. The cohort included 5,052 visits in 43 wards. Median age was 65 years (IQR 56-73); 2,865 (57%) were male; and 2,865 (57%) were white. 770 (15%) patients died in the hospital or had hospice discharges, and 2,628 (61%) were discharged home and 964 (23%) to skilled nursing facilities (SNFs). Ward admissions, isolation precautions, and hospital admissions most consistently predicted in-hospital mortality across ML models. Patients per nurse most consistently predicted discharge to home and SNF, and medications administered predicted SNF discharge. In this hypothesis-generating analysis of candidate ward strain variables' prediction of outcomes among ARF survivors, several variables emerged as consistently predictive of key outcomes across ML models. These findings suggest targets for future inferential studies to elucidate mechanisms of ward strain's adverse effects.

Multimorbidity Confers Greater Risk for Older Patients in Emergency General Surgery Than the Presence of Multiple Comorbidities: A Retrospective Observational Study.

BACKGROUND: Little is known about the impact of multimorbidity on outcomes for older emergency general surgery patients. OBJECTIVE: The aim was to understand whether having multiple comorbidities confers the same amount of risk as specific combinations of comorbidities (multimorbidity) for a patient undergoing emergency general surgery. RESEARCH DESIGN: Retrospective observational study using state discharge data. SUBJECTS: Medicare beneficiaries who underwent an operation for an emergency general surgery condition in New York, Florida, or Pennsylvania (2012-2013). MEASURES: Patients were classified as multimorbid using Qualifying Comorbidity Sets (QCSs). Outcomes included in-hospital mortality, hospital length of stay and discharge status. RESULTS: Of 312,160 patients, a large minority (37.4%) were multimorbid. Non-QCS patients did not have a specific combination of comorbidities to satisfy a QCS, but 64.1% of these patients had 3+ comorbid conditions. Multimorbidity was associated with increased in-hospital mortality (10.5% vs. 3.9%, P <0.001), decreased rates of discharge to home (16.2% vs. 37.1%, P <0.001), and longer length of stay (10.4 d±13.5 vs. 6.7 d±9.3, P <0.001) when compared with non-QCS patients. Risks varied between individual QCSs. CONCLUSIONS: Multimorbidity, defined by satisfying a specific QCS, is strongly associated with poor outcomes for older patients requiring emergency general surgery in the United States. Variation in risk of in-hospital mortality, discharge status, and length of stay between individual QCSs suggests that multimorbidity does not carry the same prognostic weight as having multiple comorbidities-the specifics of which are important in setting expectations for individual, complex patients.

A Qualitative Analysis of Factors Influencing Critical Care Trial Enrollment Among Surrogates.

BACKGROUND: We sought to identify factors that influence surrogate decision makers' decisions to enroll patients into a critical care randomized controlled trial. METHODS: We conducted a qualitative study embedded within a randomized controlled trial testing the effect of a behavioral nudge intervention for surrogate decision makers on enrollment rate in a sham ventilatory weaning trial among patients with acute respiratory failure. Participants were adult surrogate decision makers of patients receiving mechanical ventilation for acute respiratory failure. The study was conducted in 10 ICUs across 2 urban hospitals within an academic medical center in Philadelphia, Pennsylvanaia, United States. Immediately following their trial enrollment decision, surrogate decision makers were asked to enter free-text responses about the factors that influenced their decision. Responses were analyzed using content analysis. RESULTS: Of the 90 (49%) participants who provided free-text responses, the mean age was 54.9 years (SD 14.3), 69 (79%) were Caucasian, and 48 (53%) were the spouse of the eligible patient. We identified 5 themes influencing enrollment decisions: (i) trial characteristics, (ii) patient clinical condition, (iii) decision making processes, (iv) altruism, and (v) enrollment attempt. Among surrogates who enrolled the patient in the trial (n = 40), the most commonly cited factors were helping future patients (n = 24, 60%) and following the patient's wishes (n = 11, 28%). In contrast, those who declined enrollment (n = 50) most commonly reported that the patient was too sick (n = 27, 54%) and that they feared complicating the patient's condition (n = 11, 22%). CONCLUSIONS: Surrogates who enroll patients into trials most often cite altruistic motivations, while those who decline enrollment are most often concerned with the severity of the patients' condition.

Patient perspectives on states worse than death: A qualitative study with implications for patient-centered outcomes and values elicitation.

BACKGROUND: Seriously ill patients rate several health outcomes as states worse than death. It is unclear what factors underlie such valuations, and whether consideration of such states is useful when making medical decisions. AIM: We sought to (1) use qualitative approaches to identify states worse than death, (2) identify attributes common to such undesirable health states, and (3) determine how participants might use information on these states in making medical decisions. DESIGN: Qualitative study of semi-structured interviews utilizing content analysis with constant comparison techniques. SETTING, PARTICIPANTS: We interviewed adults age 65 or older with serious illnesses after discharge home from one of two urban, academic hospitals. Eligible patients were purposively sampled to achieve balance in gender and race. RESULTS: Of 29 participants, 15 (52%) were female, and 15 were white (52%), with a median age of 72 (interquartile range 69, 75). Various physical, cognitive, and social impairments were identified as states worse than death. The most commonly reported attributes underlying states worse than death were perceived burden on loved ones and inability to maintain human connection. Patients believed information on states worse than death must be individualized, and were concerned their opinions could change with time and fluctuations in health status. CONCLUSIONS: Common factors underlying undesirable states suggest that for care to be patient-centered it must also be family-centered. Patients' views on using states worse than death in decision making highlight barriers to using avoidance of such states as a quality measure, but also suggest opportunities for eliciting patients' values.

Equitably Allocating Resources during Crises: Racial Differences in Mortality Prediction Models.

Rationale: Crisis standards of care (CSCs) guide critical care resource allocation during crises. Most recommend ranking patients on the basis of their expected in-hospital mortality using the Sequential Organ Failure Assessment (SOFA) score, but it is unknown how SOFA or other acuity scores perform among patients of different races. Objectives: To test the prognostic accuracy of the SOFA score and version 2 of the Laboratory-based Acute Physiology Score (LAPS2) among Black and white patients. Methods: We included Black and white patients admitted for sepsis or acute respiratory failure at 27 hospitals. We calculated the discrimination and calibration for in-hospital mortality of SOFA, LAPS2, and modified versions of each, including categorical SOFA groups recommended in a popular CSC and a SOFA score without creatinine to reduce the influence of race. Measurements and Main Results: Of 113,158 patients, 27,644 (24.4%) identified as Black. The LAPS2 demonstrated higher discrimination (area under the receiver operating characteristic curve [AUC], 0.76; 95% confidence interval [CI], 0.76-0.77) than the SOFA score (AUC, 0.68; 95% CI, 0.68-0.69). The LAPS2 was also better calibrated than the SOFA score, but both underestimated in-hospital mortality for white patients and overestimated in-hospital mortality for Black patients. Thus, in a simulation using observed mortality, 81.6% of Black patients were included in lower-priority CSC categories, and 9.4% of all Black patients were erroneously excluded from receiving the highest prioritization. The SOFA score without creatinine reduced racial miscalibration. Conclusions: Using SOFA in CSCs may lead to racial disparities in resource allocation. More equitable mortality prediction scores are needed.

A Pragmatic Trial of E-Cigarettes, Incentives, and Drugs for Smoking Cessation.

BACKGROUND: Whether financial incentives, pharmacologic therapies, and electronic cigarettes (e-cigarettes) promote smoking cessation among unselected smokers is unknown. METHODS: We randomly assigned smokers employed by 54 companies to one of four smoking-cessation interventions or to usual care. Usual care consisted of access to information regarding the benefits of smoking cessation and to a motivational text-messaging service. The four interventions consisted of usual care plus one of the following: free cessation aids (nicotine-replacement therapy or pharmacotherapy, with e-cigarettes if standard therapies failed); free e-cigarettes, without a requirement that standard therapies had been tried; free cessation aids plus $600 in rewards for sustained abstinence; or free cessation aids plus $600 in redeemable funds, deposited in a separate account for each participant, with money removed from the account if cessation milestones were not met. The primary outcome was sustained smoking abstinence for 6 months after the target quit date. RESULTS: Among 6131 smokers who were invited to enroll, 125 opted out and 6006 underwent randomization. Sustained abstinence rates through 6 months were 0.1% in the usual-care group, 0.5% in the free cessation aids group, 1.0% in the free e-cigarettes group, 2.0% in the rewards group, and 2.9% in the redeemable deposit group. With respect to sustained abstinence rates, redeemable deposits and rewards were superior to free cessation aids (P<0.001 and P=0.006, respectively, with significance levels adjusted for multiple comparisons). Redeemable deposits were superior to free e-cigarettes (P=0.008). Free e-cigarettes were not superior to usual care (P=0.20) or to free cessation aids (P=0.43). Among the 1191 employees (19.8%) who actively participated in the trial (the "engaged" cohort), sustained abstinence rates were four to six times as high as those among participants who did not actively engage in the trial, with similar relative effectiveness. CONCLUSIONS: In this pragmatic trial of smoking cessation, financial incentives added to free cessation aids resulted in a higher rate of sustained smoking abstinence than free cessation aids alone. Among smokers who received usual care (information and motivational text messages), the addition of free cessation aids or e-cigarettes did not provide a benefit. (Funded by the Vitality Institute; ClinicalTrials.gov number, NCT02328794 .).

The Quality of End-of-Life Care among ICU versus Ward Decedents.

Rationale: Admissions to ICUs are common during terminal hospitalizations, but little is known about how ICU care affects the end-of-life experience for patients dying in hospitals and their families.Objectives: We measured the association between ICU care during terminal hospitalization and family ratings of end-of-life care for patients who died in 106 Veterans Affairs hospitals from 2010 to 2016.Methods: Patients were divided into four categories: no-ICU care, ICU-only care, mixed care (died outside ICU), and mixed care (died in ICU). Multivariable linear probability models were adjusted for patient and hospital characteristics. Patients receiving mixed care were also analyzed based on percentage of time in ICU.Measurements and Main Results: Of 57,550 decedents, 28,062 (48.8%) had a survey completed by a family member or close contact. In adjusted models, ICU-only care was associated with more frequent optimal ratings than no-ICU care, including overall excellent care (56.6% vs. 48.1%; P < 0.001), care consistent with preferences (78.7% vs. 72.4%; P < 0.001), and having pain controlled (51.3% vs. 46.7%; P < 0.001). Among patients with mixed care, increasing ICU time was associated with higher ratings on these same measures (all P < 0.001 for comparisons of those spending >75% time in ICU vs. ≤25% time).Conclusions: Among hospital decedents, ICU care was associated with higher family ratings of quality of end-of-life care than ward care. Reducing ICU use among hospital decedents may not improve end-of-life quality, and efforts to understand how ICU care improves end-of-life quality could help provide better care outside ICUs.

Gender Differences in Authorship of Critical Care Literature.

Rationale: Gender gaps exist in academic leadership positions in critical care. Peer-reviewed publications are crucial to career advancement, and yet little is known regarding gender differences in authorship of critical care research.Objectives: To evaluate gender differences in authorship of critical care literature.Methods: We used a validated database of author gender to analyze authorship of critical care articles indexed in PubMed between 2008 and 2018 in 40 frequently cited journals. High-impact journals were defined as those in the top 5% of all journals. We used mixed-effects logistic regression to evaluate the association of senior author gender with first and middle author gender, as well as association of first author gender with journal impact factor.Measurements and Main Results: Among 18,483 studies, 30.8% had female first authors, and 19.5% had female senior authors. Female authorship rose slightly over the last decade (average annual increases of 0.44% [P < 0.01] and 0.51% [P < 0.01] for female first and senior authors, respectively). When the senior author was female, the odds of female coauthorship rose substantially (first author adjusted odds ratio [aOR], 1.93; 95% confidence interval [CI], 1.71-2.17; middle author aOR, 1.48; 95% CI, 1.29-1.69). Female first authors had higher odds than men of publishing in lower-impact journals (aOR, 1.30; 95% CI, 1.16-1.45).Conclusions: Women comprise less than one-third of first authors and one-fourth of senior authors of critical care research, with minimal increase over the past decade. When the senior author was female, the odds of female coauthorship rose substantially. However, female first authors tend to publish in lower-impact journals. These findings may help explain the underrepresentation of women in critical care academic leadership positions and identify targets for improvement.

Locally Informed Simulation to Predict Hospital Capacity Needs During the COVID-19 Pandemic.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic challenges hospital leaders to make time-sensitive, critical decisions about clinical operations and resource allocations. OBJECTIVE: To estimate the timing of surges in clinical demand and the best- and worst-case scenarios of local COVID-19-induced strain on hospital capacity, and thus inform clinical operations and staffing demands and identify when hospital capacity would be saturated. DESIGN: Monte Carlo simulation instantiation of a susceptible, infected, removed (SIR) model with a 1-day cycle. SETTING: 3 hospitals in an academic health system. PATIENTS: All people living in the greater Philadelphia region. MEASUREMENTS: The COVID-19 Hospital Impact Model (CHIME) (http://penn-chime.phl.io) SIR model was used to estimate the time from 23 March 2020 until hospital capacity would probably be exceeded, and the intensity of the surge, including for intensive care unit (ICU) beds and ventilators. RESULTS: Using patients with COVID-19 alone, CHIME estimated that it would be 31 to 53 days before demand exceeds existing hospital capacity. In best- and worst-case scenarios of surges in the number of patients with COVID-19, the needed total capacity for hospital beds would reach 3131 to 12 650 across the 3 hospitals, including 338 to 1608 ICU beds and 118 to 599 ventilators. LIMITATIONS: Model parameters were taken directly or derived from published data across heterogeneous populations and practice environments and from the health system's historical data. CHIME does not incorporate more transition states to model infection severity, social networks to model transmission dynamics, or geographic information to account for spatial patterns of human interaction. CONCLUSION: Publicly available and designed for hospital operations leaders, this modeling tool can inform preparations for capacity strain during the early days of a pandemic. PRIMARY FUNDING SOURCE: University of Pennsylvania Health System and the Palliative and Advanced Illness Research Center.

A Partially Structured Postoperative Handoff Protocol Improves Communication in 2 Mixed Surgical Intensive Care Units: Findings From the Handoffs and Transitions in Critical Care (HATRICC) Prospective Cohort Study.

OBJECTIVE: To assess the effectiveness of standardizing operating room (OR) to intensive care unit (ICU) handoffs in a mixed surgical population. SUMMARY OF BACKGROUND DATA: Standardizing OR to ICU handoffs improves information transfer after cardiac surgery, but there is limited evidence in other surgical contexts. METHODS: This prospective interventional cohort study (NCT02267174) was conducted in 2 surgical ICUs in 2 affiliated hospitals. From 2014 to 2016, we developed, implemented, and assessed the effectiveness of a new standardized handoff protocol requiring bedside clinician communication using an information template. The primary study outcome was number of information omissions out of 13 possible topics, recorded by trained observers. Data were analyzed using descriptive statistics, bivariate analyses, and multivariable regression. RESULTS: We observed 165 patient transfers (68 pre-, 97 postintervention). Before standardization, observed handoffs had a mean 4.7 ±â€Š2.9 information omissions each. After standardization, information omissions decreased 21.3% to 3.7 ±â€Š1.9 (P = 0.023). In a pre-specified subanalysis, information omissions for new ICU patients decreased 36.2% from 4.7 ±â€Š3.1 to 3.0 ±â€Š1.6 (P = 0.008, interaction term P = 0.008). The decrement in information omissions was linearly associated with the number of protocol steps followed (P < 0.001). After controlling for patient stability, the intervention was still associated with reduced omissions. Handoff duration increased after standardization from 4.1 ±â€Š3.3 to 8.0 ±â€Š3.9 minutes (P < 0.001). ICU mortality and length of stay did not change postimplementation. CONCLUSION: Standardizing OR to ICU handoffs significantly improved information exchange in 2 mixed surgical ICUs, with a concomitant increase in handoff duration. Additional research is needed to identify barriers to and facilitators of handoff protocol adherence.