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.

Deriving Meaningful Aspects of Health Related to Physical Activity in Chronic Disease: Concept Elicitation Using Machine Learning-Assisted Coding of Online Patient Conversations.

OBJECTIVES: Clinical outcome assessment (COA) developers must ensure that measures assess aspects of health that are meaningful to the target patient population. Although the methodology for doing this is well understood for certain COAs, such as patient-reported outcome measures, there are fewer examples of this practice in the development of digital endpoints using mobile sensor technology such as physical activity monitors. This study explored the utility of social media data, specifically, posts on online health boards, in understanding meaningful aspects of health related to physical activity in 3 different chronic diseases: fibromyalgia, chronic obstructive pulmonary disease, and chronic heart failure. METHODS: We used machine learning and manual coding to summarize the content of posts extracted from 4 online health boards. Where available, patient age and sex were retrieved from post content or user profiles. We utilized analytical approaches to assess the robustness of findings to differences in the characteristics of online samples compared to the true patient population. Finally, we assessed concept saturation by measuring the convergence of autocorrelations. RESULTS: We identify a number of aspects of health described as important by patients in our samples, and summarize these into concepts for measurement. For chronic heart failure, these included purposeful walking duration and speed, fatigue, difficulty going upstairs, standing, and aspects of physical exercise. Overall and age-adjusted results did not differ considerably for each disease group. CONCLUSIONS: This study illustrates the potential of performing concept elicitation research using social media data, which may provide valuable insight to inform COA development.

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.

CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

PURPOSE: Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC. METHODS: We propose an absolute risk prediction model, CBCRisk-Black, specifically for Black BC patients. It uses data on Black women from two sources: Breast Cancer Surveillance Consortium (BCSC) and Surveillance, Epidemiology, and End Results (SEER). First, a matched lasso logistic regression model for estimating relative risks (RR) is developed. Then, it is combined with relevant hazard rates and attributable risks to obtain absolute risks. Six-fold cross-validation is used to internally validate CBCRisk-Black. We also compare CBCRisk-Black with CBCRisk, an existing CBC risk prediction model. RESULTS: The RR model uses data from BCSC on 744 Black women (186 cases). CBCRisk-Black has four risk factors (RR compared to baseline): breast density (2.13 for heterogeneous/extremely dense), family history of BC (2.28 for yes), first BC tumor size (2.14 for T3/T4, 1.56 for TIS), and age at first diagnosis of BC (1.41 for < 40). The area under the receiver operating characteristic curve (AUC) for 3- and 5-year predictions are 0.72 and 0.65 for CBCRisk-Black while those are 0.65 and 0.60 for CBCRisk. CONCLUSION: CBCRisk-Black may serve as a useful tool to clinicians in counseling Black BC patients by providing a more accurate and personalized CBC risk estimate.

Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer.

PURPOSE: Increased mammographic breast density is a significant risk factor for breast cancer. It is not clear if it is also a risk factor for the development of contralateral breast cancer. METHODS: The data were obtained from Breast Cancer Surveillance Consortium and included women diagnosed with invasive breast cancer or ductal carcinoma in situ between ages 18 and 88 and years 1995 and 2009. Each case of contralateral breast cancer was matched with three controls based on year of first breast cancer diagnosis, race, and length of follow-up. A total of 847 cases and 2541 controls were included. The risk factors included in the study were mammographic breast density, age of first breast cancer diagnosis, family history of breast cancer, anti-estrogen treatment, hormone replacement therapy, menopausal status, and estrogen receptor status, all from the time of first breast cancer diagnosis. Both univariate analysis and multivariate conditional logistic regression analysis were performed. RESULTS: In the final multivariate model, breast density, family history of breast cancer, and anti-estrogen treatment remained significant with p values less than 0.01. Increasing breast density had a dose-dependent effect on the risk of contralateral breast cancer. Relative to 'almost entirely fat' category of breast density, the adjusted odds ratios (and p values) in the multivariate analysis for 'scattered density,' 'heterogeneously dense,' and 'extremely dense' categories were 1.65 (0.036), 2.10 (0.002), and 2.32 (0.001), respectively. CONCLUSION: Breast density is an independent and significant risk factor for development of contralateral breast cancer. This risk factor should contribute to clinical decision making.

Validation of a personalized risk prediction model for contralateral breast cancer.

PURPOSE: Women diagnosed with unilateral breast cancer are increasingly choosing to remove their other unaffected breast through contralateral prophylactic mastectomy (CPM) to reduce the risk of contralateral breast cancer (CBC). Yet a large proportion of CPMs are believed to be medically unnecessary. Thus, there is a pressing need to educate patients effectively on their CBC risk. We had earlier developed a CBC risk prediction model called CBCRisk based on eight personal risk factors. METHODS: In this study, we validate CBCRisk on independent clinical data from the Johns Hopkins University (JH) and MD Anderson Cancer Center (MDA). Women whose first breast cancer diagnosis was either invasive and/or ductal carcinoma in situ and whose age at first diagnosis was between 18 and 88 years were included in the cohorts because CBCRisk was developed specifically for these women. A woman who develops CBC is called a case whereas a woman who does not is called a control. The cohort sizes are 6035 (with 117 CBC cases) for JH and 5185 (with 111 CBC cases) for MDA. We computed the relevant calibration and validation measures for 3- and 5-year risk predictions. RESULTS: We found that the model performs reasonably well for both cohorts. In particular, area under the receiver-operating characteristic curve for the two cohorts range from 0.61 to 0.65. CONCLUSIONS: With this independent validation, CBCRisk can be used confidently in clinical settings for counseling BC patients by providing their individualized CBC risk. In turn, this may potentially help alleviate the rate of medically unnecessary CPMs.

A model for individualized risk prediction of contralateral breast cancer.

PURPOSE: Patients diagnosed with invasive breast cancer (BC) or ductal carcinoma in situ are increasingly choosing to undergo contralateral prophylactic mastectomy (CPM) to reduce their risk of contralateral BC (CBC). This is a particularly disturbing trend as a large proportion of these CPMs are believed to be medically unnecessary. Many BC patients tend to substantially overestimate their CBC risk. Thus, there is a pressing need to educate patients effectively on their CBC risk. We develop a CBC risk prediction model to aid physicians in this task. METHODS: We used data from two sources: Breast Cancer Surveillance Consortium and Surveillance, Epidemiology, and End Results to build the model. The model building steps are similar to those used in developing the BC risk assessment tool (popularly known as Gail model) for counseling women on their BC risk. Our model, named CBCRisk, is exclusively designed for counseling women diagnosed with unilateral BC on the risk of developing CBC. RESULTS: We identified eight factors to be significantly associated with CBC-age at first BC diagnosis, anti-estrogen therapy, family history of BC, high-risk pre-neoplasia status, estrogen receptor status, breast density, type of first BC, and age at first birth. Combining the relative risk estimates with the relevant hazard rates, CBCRisk projects absolute risk of developing CBC over a given period. CONCLUSIONS: By providing individualized CBC risk estimates, CBCRisk may help in counseling of BC patients. In turn, this may potentially help alleviate the rate of medically unnecessary CPMs.

Racial Disparities in Length of Stay Among Severely Ill Patients Presenting With Sepsis and Acute Respiratory Failure.

Importance: Although racial and ethnic minority patients with sepsis and acute respiratory failure (ARF) experience worse outcomes, how patient presentation characteristics, processes of care, and hospital resource delivery are associated with outcomes is not well understood. Objective: To measure disparities in hospital length of stay (LOS) among patients at high risk of adverse outcomes who present with sepsis and/or ARF and do not immediately require life support and to quantify associations with patient- and hospital-level factors. Design, Setting, and Participants: This matched retrospective cohort study used electronic health record data from 27 acute care teaching and community hospitals across the Philadelphia metropolitan and northern California areas between January 1, 2013, and December 31, 2018. Matching analyses were performed between June 1 and July 31, 2022. The study included 102 362 adult patients who met clinical criteria for sepsis (n = 84 685) or ARF (n = 42 008) with a high risk of death at the time of presentation to the emergency department but without an immediate requirement for invasive life support. Exposures: Racial or ethnic minority self-identification. Main Outcomes and Measures: Hospital LOS, defined as the time from hospital admission to the time of discharge or inpatient death. Matches were stratified by racial and ethnic minority patient identity, comparing Asian and Pacific Islander patients, Black patients, Hispanic patients, and multiracial patients with White patients in stratified analyses. Results: Among 102 362 patients, the median (IQR) age was 76 (65-85) years; 51.5% were male. A total of 10.2% of patients self-identified as Asian American or Pacific Islander, 13.7% as Black, 9.7% as Hispanic, 60.7% as White, and 5.7% as multiracial. After matching racial and ethnic minority patients to White patients on clinical presentation characteristics, hospital capacity strain, initial intensive care unit admission, and the occurrence of inpatient death, Black patients experienced longer LOS relative to White patients in fully adjusted matches (sepsis: 1.26 [95% CI, 0.68-1.84] days; ARF: 0.97 [95% CI, 0.05-1.89] days). Length of stay was shorter among Asian American and Pacific Islander patients with ARF (-0.61 [95% CI, -0.88 to -0.34] days) and Hispanic patients with sepsis (-0.22 [95% CI, -0.39 to -0.05] days) or ARF (-0.47 [-0.73 to -0.20] days). Conclusions and Relevance: In this cohort study, Black patients with severe illness who presented with sepsis and/or ARF experienced longer LOS than White patients. Hispanic patients with sepsis and Asian American and Pacific Islander and Hispanic patients with ARF both experienced shorter LOS. Because matched differences were independent of commonly implicated clinical presentation-related factors associated with disparities, identification of additional mechanisms that underlie these disparities is warranted.

Hospital Strain and Variation in Sepsis ICU Admission Practices and Associated Outcomes.

To understand how strain-process-outcome relationships in patients with sepsis may vary among hospitals. DESIGN: Retrospective cohort study using a validated hospital capacity strain index as a within-hospital instrumental variable governing ICU versus ward admission, stratified by hospital. SETTING: Twenty-seven U.S. hospitals from 2013 to 2018. PATIENTS: High-acuity emergency department patients with sepsis who do not require life support therapies. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The mean predicted probability of ICU admission across strain deciles ranged from 4.9% (lowest ICU-utilizing hospital for sepsis without life support) to 61.2% (highest ICU-utilizing hospital for sepsis without life support). The difference in the predicted probabilities of ICU admission between the lowest and highest strain deciles ranged from 9.0% (least strain-sensitive hospital) to 45.2% (most strain-sensitive hospital). In pooled analyses, emergency department patients with sepsis (n = 90,150) experienced a 1.3-day longer median hospital length of stay (LOS) if admitted initially to the ICU compared with the ward, but across the 27 study hospitals (n = 517-6,564), this effect varied from 9.0 days shorter (95% CI, -10.8 to -7.2; p < 0.001) to 19.0 days longer (95% CI, 16.7-21.3; p < 0.001). Corresponding ranges for inhospital mortality with ICU compared with ward admission revealed odds ratios (ORs) from 0.16 (95% CI, 0.03-0.99; p = 0.04) to 4.62 (95% CI, 1.16-18.22; p = 0.02) among patients with sepsis (pooled OR = 1.48). CONCLUSIONS: There is significant among-hospital variation in ICU admission rates for patients with sepsis not requiring life support therapies, how sensitive those ICU admission decisions are to hospital capacity strain, and the association of ICU admission with hospital LOS and hospital mortality. Hospital-level heterogeneity should be considered alongside patient-level heterogeneity in critical and acute care study design and interpretation.

Among-Hospital Variation in Intensive Care Unit Admission Practices and Associated Outcomes for Patients with Acute Respiratory Failure.

Rationale: We have previously shown that hospital strain is associated with intensive care unit (ICU) admission and that ICU admission, compared with ward admission, may benefit certain patients with acute respiratory failure (ARF). Objectives: To understand how strain-process-outcomes relationships in patients with ARF may vary among hospitals and what hospital practice differences may account for such variation. Methods: We examined high-acuity patients with ARF who did not require mechanical ventilation or vasopressors in the emergency department (ED) and were admitted to 27 U.S. hospitals from 2013 to 2018. Stratifying by hospital, we compared hospital strain-ICU admission relationships and hospital length of stay (LOS) and mortality among patients initially admitted to the ICU versus the ward using hospital strain as a previously validated instrumental variable. We also surveyed hospital practices and, in exploratory analyses, evaluated their associations with the above processes and outcomes. Results: There was significant among-hospital variation in ICU admission rates, in hospital strain-ICU admission relationships, and in the association of ICU admission with hospital LOS and hospital mortality. Overall, ED patients with ARF (n = 45,339) experienced a 0.82-day shorter median hospital LOS if admitted initially to the ICU compared with the ward, but among the 27 hospitals (n = 224-3,324), this effect varied from 5.85 days shorter (95% confidence interval [CI], -8.84 to -2.86; P < 0.001) to 4.38 days longer (95% CI, 1.86-6.90; P = 0.001). Corresponding ranges for in-hospital mortality with ICU compared with ward admission revealed odds ratios from 0.08 (95% CI, 0.01-0.56; P < 0.007) to 8.89 (95% CI, 1.60-79.85; P = 0.016) among patients with ARF (pooled odds ratio, 0.75). In exploratory analyses, only a small number of measured hospital practices-the presence of a sepsis ED disposition guideline and maximum ED patient capacity-were potentially associated with hospital strain-ICU admission relationships. Conclusions: Hospitals vary considerably in ICU admission rates, the sensitivity of those rates to hospital capacity strain, and the benefits of ICU admission for patients with ARF not requiring life support therapies in the ED. Future work is needed to more fully identify hospital-level factors contributing to these relationships.

Characterizing Equity of Intensive Care Unit Admissions for Sepsis and Acute Respiratory Failure.

Rationale: Patients who identify as from racial or ethnic minority groups who have sepsis or acute respiratory failure (ARF) experience worse outcomes relative to nonminority patients, but processes of care accounting for disparities are not well-characterized. Objectives: Determine whether reductions in intensive care unit (ICU) admission during hospital-wide capacity strain occur preferentially among patients who identify with racial or ethnic minority groups. Methods: This retrospective cohort among 27 hospitals across the Philadelphia metropolitan area and Northern California between 2013 and 2018 included adult patients with sepsis and/or ARF who did not require life support at the time of hospital admission. An updated model of hospital-wide capacity strain was developed that permitted determination of relationships between patient race, ethnicity, ICU admission, and strain. Results: After adjustment for demographics, disease severity, and study hospital, patients who identified as Asian or Pacific Islander had the highest adjusted ICU admission odds relative to patients who identified as White in both the sepsis and ARF populations (odds ratio, 1.09; P = 0.006 and 1.26; P < 0.001). ICU admission was also elevated for patients with ARF who identified as Hispanic (odds ratio, 1.11; P = 0.020). Capacity strain did not modify differences in ICU admission for patients who identified with a minority group in either disease population (all interactions, P > 0.05). Conclusions: Systematic differences in ICU admission patterns were observed for patients that identified as Asian, Pacific Islander, and Hispanic. However, ICU admission was not restricted from these groups, and capacity strain did not preferentially reduce ICU admission from patients identifying with minority groups. Further characterization of provider decision-making can help contextualize these findings as the result of disparate decision-making or a mechanism of equitable care.

Comparing Smoking Cessation Interventions among Underserved Patients Referred for Lung Cancer Screening: A Pragmatic Trial Protocol.

Smoking burdens are greatest among underserved patients. Lung cancer screening (LCS) reduces mortality among individuals at risk for smoking-associated lung cancer. Although LCS programs must offer smoking cessation support, the interventions that best promote cessation among underserved patients in this setting are unknown. This stakeholder-engaged, pragmatic randomized clinical trial will compare the effectiveness of four interventions promoting smoking cessation among underserved patients referred for LCS. By using an additive study design, all four arms provide standard "ask-advise-refer" care. Arm 2 adds free or subsidized pharmacologic cessation aids, arm 3 adds financial incentives up to $600 for cessation, and arm 4 adds a mobile device-delivered episodic future thinking tool to promote attention to long-term health goals. We hypothesize that smoking abstinence rates will be higher with the addition of each intervention when compared with arm 1. We will enroll 3,200 adults with LCS orders at four U.S. health systems. Eligible patients include those who smoke at least one cigarette daily and self-identify as a member of an underserved group (i.e., is Black or Latinx, is a rural resident, completed a high school education or less, and/or has a household income <200% of the federal poverty line). The primary outcome is biochemically confirmed smoking abstinence sustained through 6 months. Secondary outcomes include abstinence sustained through 12 months, other smoking-related clinical outcomes, and patient-reported outcomes. This pragmatic randomized clinical trial will identify the most effective smoking cessation strategies that LCS programs can implement to reduce smoking burdens affecting underserved populations. Clinical trial registered with clinicaltrials.gov (NCT04798664). Date of registration: March 12, 2021. Date of trial launch: May 17, 2021.

Effectiveness and Ethics of Incentives for Research Participation: 2 Randomized Clinical Trials.

Importance: Incentivizing research participation is controversial and variably regulated because of uncertainty regarding whether financial incentives serve as undue inducements by diminishing peoples' sensitivity to research risks or unjust inducements by preferentially increasing enrollment among underserved individuals. Objective: To determine whether incentives improve enrollment in real randomized clinical trials (RCTs) or serve as undue or unjust inducements. Design, Setting, and Participants: Two RCTs of incentives that were embedded in 2 parent RCTs, 1 comparing smoking cessation interventions (conducted at smoking cessation clinics in 2 health systems) and 1 evaluating an ambulation intervention (conducted across wards of the Hospital of the University of Pennsylvania) included all persons eligible for the parent trials who did not have prior knowledge of the incentives trials. Recruitment occurred from September 2017 to August 2019 for the smoking trial and January 2018 through May 2019 for the ambulation trial; data were analyzed from January 2020 to July 2020. Interventions: Patients were randomly assigned to incentives of $0, $200, or $500 for participating in the smoking cessation trial and $0, $100, or $300 for the ambulation trial. Main Outcomes and Measures: The primary outcome of each incentive trial was the proportion of people assigned to each recruitment strategy that consented to participate. Each trial was powered to test the hypotheses that incentives served neither as undue inducements (based on the interaction between incentive size and perceived research risk, as measured using a 10-point scale, on the primary outcome), nor unjust inducements (based on the interaction between incentive size and participants' self-reported income). Noninferiority methods were used to test whether the data were compatible with these 2 effects of incentives and superiority methods to compare the primary and other secondary outcomes. Results: There were a total of 654 participants (327 women [50.0%]; mean [SD] age, 50.6 [12.1] years; 394 Black/African American [60.2%], 214 White [32.7%], and 24 multiracial individuals [3.7%]) in the smoking trial, and 642 participants (364 women [56.7%]; mean [SD] age, 46.7 [15.6] years; 224 Black/African American [34.9%], 335 White [52.2%], and 5 multiracial individuals [0.8%]) in the ambulation trial. Incentives significantly increased consent rates among those in the smoking trial in 47 of 216 (21.8%), 78 of 217 (35.9%), and 104 of 221 (47.1%) in the $0, $200, and $500 groups, respectively (adjusted odds ratio [aOR] for each increase in incentive, 1.70; 95% CI, 1.34-2.17; P < .001). Incentives did not increase consent among those in the ambulation trial: 98 of 216 (45.4%), 102 of 212 (48.1%), and 92 of 214 (43.0%) in the $0, $100, and $300 groups, respectively (aOR, 0.88; 95% CI, 0.64-1.22; P = .45). In neither trial was there evidence of undue or unjust inducement (upper confidence limits of ORs for undue inducement, 1.15 and 0.99; P < .001 showing noninferiority; upper confidence limits of ORs for unjust inducement, 1.21 and 1.26; P = .01 and P < .001, respectively). There were no significant effects of incentive size on the secondary outcomes in either trial, including time spent reviewing the risk sections of consent forms, perceived research risks, trial understanding, perceived coercion, or therapeutic misconceptions. Conclusions and Relevance: In these 2 randomized clinical trials, financial incentives increased trial enrollment in 1 of 2 trials and did not produce undue or unjust inducement or other unintended consequences in either trial. Trial Registration: ClinicalTrials.gov Identifier: NCT02697799.

Prognosticating Outcomes and Nudging Decisions with Electronic Records in the Intensive Care Unit Trial Protocol.

Expert recommendations to discuss prognosis and offer palliative options for critically ill patients at high risk of death are variably heeded by intensive care unit (ICU) clinicians. How to best promote such communication to avoid potentially unwanted aggressive care is unknown. The PONDER-ICU (Prognosticating Outcomes and Nudging Decisions with Electronic Records in the ICU) study is a 33-month pragmatic, stepped-wedge cluster randomized trial testing the effectiveness of two electronic health record (EHR) interventions designed to increase ICU clinicians' engagement of critically ill patients at high risk of death and their caregivers in discussions about all treatment options, including care focused on comfort. We hypothesize that the quality of care and patient-centered outcomes can be improved by requiring ICU clinicians to document a functional prognostic estimate (intervention A) and/or to provide justification if they have not offered patients the option of comfort-focused care (intervention B). The trial enrolls all adult patients admitted to 17 ICUs in 10 hospitals in North Carolina with a preexisting life-limiting illness and acute respiratory failure requiring continuous mechanical ventilation for at least 48 hours. Eligibility is determined using a validated algorithm in the EHR. The sequence in which hospitals transition from usual care (control), to intervention A or B and then to combined interventions A + B, is randomly assigned. The primary outcome is hospital length of stay. Secondary outcomes include other clinical outcomes, palliative care process measures, and nurse-assessed quality of dying and death.Clinical trial registered with clinicaltrials.gov (NCT03139838).

Association of a Novel Index of Hospital Capacity Strain with Admission to Intensive Care Units.

Rationale: Prior approaches to measuring healthcare capacity strain have been constrained by using individual care units, limited metrics of strain, or general, rather than disease-specific, populations.Objectives: We sought to develop a novel composite strain index and measure its association with intensive care unit (ICU) admission decisions and hospital outcomes.Methods: Using more than 9.2 million acute care encounters from 27 Kaiser Permanente Northern California and Penn Medicine hospitals from 2013 to 2018, we deployed multivariable ridge logistic regression to develop a composite strain index based on hourly measurements of 22 capacity-strain metrics across emergency departments, wards, step-down units, and ICUs. We measured the association of this strain index with ICU admission and clinical outcomes using multivariable logistic and quantile regression.Results: Among high-acuity patients with sepsis (n = 90,150) and acute respiratory failure (ARF; n = 45,339) not requiring mechanical ventilation or vasopressors, strain at the time of emergency department disposition decision was inversely associated with the probability of ICU admission (sepsis: adjusted probability ranging from 29.0% [95% confidence interval, 28.0-30.0%] at the lowest strain index decile to 9.3% [8.7-9.9%] at the highest strain index decile; ARF: adjusted probability ranging from 47.2% [45.6-48.9%] at the lowest strain index decile to 12.1% [11.0-13.2%] at the highest strain index decile; P < 0.001 at all deciles). Among subgroups of patients who almost always or never went to the ICU, strain was not associated with hospital length of stay, mortality, or discharge disposition (all P ≥ 0.13). Strain was also not meaningfully associated with patient characteristics.Conclusions: Hospital strain, measured by a novel composite strain index, is strongly associated with ICU admission among patients with sepsis and/or ARF. This strain index fulfills the assumptions of a strong within-hospital instrumental variable for quantifying the net benefit of admission to the ICU for patients with sepsis and/or ARF.

Association of an Emergency Department-embedded Critical Care Unit with Hospital Outcomes and Intensive Care Unit Use.

Rationale: A small but growing number of hospitals are experimenting with emergency department-embedded critical care units (CCUs) in an effort to improve the quality of care for critically ill patients with sepsis and acute respiratory failure (ARF).Objectives: To evaluate the potential impact of an emergency department-embedded CCU at the Hospital of the University of Pennsylvania among patients with sepsis and ARF admitted from the emergency department to a medical ward or intensive care unit (ICU) from January 2016 to December 2017.Methods: The exposure was eligibility for admission to the emergency department-embedded CCU, which was defined as meeting a clinical definition for sepsis or ARF and admission to the emergency department during the intervention period on a weekday. The primary outcome was hospital length of stay (LOS); secondary outcomes included total emergency department plus ICU LOS, hospital survival, direct admission to the ICU, and unplanned ICU admission. Primary interrupted time series analyses were performed using ordinary least squares regression comparing monthly means. Secondary retrospective cohort and before-after analyses used multivariable Cox proportional hazard and logistic regression.Results: In the baseline and intervention periods, 3,897 patients met the inclusion criteria for sepsis and 1,865 patients met the criteria for ARF. Among patients admitted with sepsis, opening of the emergency department-embedded CCU was not associated with hospital LOS (ß = -1.82 d; 95% confidence interval [CI], -4.50 to 0.87; P = 0.17 for the first month after emergency department-embedded CCU opening compared with baseline; ß = -0.26 d; 95% CI, -0.58 to 0.06; P = 0.10 for subsequent months). Among patients admitted with ARF, the emergency department-embedded CCU was not associated with a significant change in hospital LOS for the first month after emergency department-embedded CCU opening (ß = -3.25 d; 95% CI, -7.86 to 1.36; P = 0.15) but was associated with a 0.64 d/mo shorter hospital LOS for subsequent months (ß = -0.64 d; 95% CI, -1.12 to -0.17; P = 0.01). This result persisted among higher acuity patients requiring ventilatory support but was not supported by alternative analytic approaches. Among patients admitted with sepsis who did not require mechanical ventilation or vasopressors in the emergency department, the emergency department-embedded CCU was associated with an initial 9.9% reduction in direct ICU admissions in the first month (ß = -0.099; 95% CI, -0.153 to -0.044; P = 0.002), followed by a 1.1% per month increase back toward baseline in subsequent months (ß = 0.011; 95% CI, 0.003-0.019; P = 0.009). This relationship was supported by alternative analytic approaches and was not seen in ARF. No associations with emergency department plus ICU LOS, hospital survival, or unplanned ICU admission were observed among patients with sepsis or ARF.Conclusions: The emergency department-embedded CCU was not associated with clinical outcomes among patients admitted with sepsis or ARF. Among less sick patients with sepsis, the emergency department-embedded CCU was initially associated with reduced rates of direct ICU admission from the emergency department. Additional research is necessary to further evaluate the impact and utility of the emergency department-embedded CCU model.

Effect of Default Options in Advance Directives on Hospital-Free Days and Care Choices Among Seriously Ill Patients: A Randomized Clinical Trial.

Importance: There is limited evidence regarding how patients make choices in advance directives (ADs) or whether these choices influence subsequent care. Objective: To examine whether default options in ADs influence care choices and clinical outcomes. Design, Setting, and Participants: This randomized clinical trial included 515 patients who met criteria for having serious illness and agreed to participate. Patients were enrolled at 20 outpatient clinics affiliated with the University of Pennsylvania Health System and the University of Pittsburgh Medical Center from February 2014 to April 2016 and had a median follow-up of 18 months. Data analysis was conducted from November 2018 to April 2019. Interventions: Patients were randomly assigned to complete 1 of the 3 following ADs: (1) a comfort-promoting plan of care and nonreceipt of potentially life-sustaining therapies were selected by default (comfort AD), (2) a life-extending plan of care and receipt of potentially life-sustaining therapies were selected by default (life-extending AD), or (3) no choices were preselected (standard AD). Main Outcomes and Measures: This trial was powered to rule out a reduction in hospital-free days in the intervention groups. Secondary outcomes included choices in ADs for an overall comfort-oriented approach to care, choices to forgo 4 forms of life support, patients' quality of life, decision conflict, place of death, admissions to hospitals and intensive care units, and costs of inpatient care. Results: Among 515 patients randomized, 10 withdrew consent and 13 were later found to be ineligible, leaving 492 (95.5%) in the modified intention-to-treat (mITT) sample (median [interquartile range] age, 63 [56-70] years; 279 [56.7%] men; 122 [24.8%] black; 363 [73.8%] with cancer). Of these, 264 (53.7%) returned legally valid ADs and were debriefed about their assigned intervention. Among these, patients completing comfort ADs were more likely to choose comfort care (54 of 85 [63.5%]) than those returning standard ADs (45 of 91 [49.5%]) or life-extending ADs (33 of 88 [37.5%]) (P = .001). Among 492 patients in the mITT sample, 57 of 168 patients [33.9%] who completed the comfort AD, 47 of 165 patients [28.5%] who completed the standard AD, and 35 of 159 patients [22.0%] who completed the life-extending AD chose comfort care (P = .02), with patients not returning ADs coded as not selecting comfort care. In mITT analyses, median (interquartile range) hospital-free days among 168 patients assigned to comfort ADs and 159 patients assigned to life-extending default ADs were each noninferior to those among 165 patients assigned to standard ADs (standard AD: 486 [306-717] days; comfort AD: 554 [296-833] days; rate ratio, 1.05; 95% CI, 0.90-1.23; P < .001; life-extending AD: 550 [325-783] days; rate ratio, 1.03; 95% CI, 0.88-1.20; P < .001). There were no differences among groups in other secondary outcomes. Conclusions and Relevance: In this randomized clinical trial, default options in ADs altered the choices seriously ill patients made regarding their future care without changing clinical outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT02017548.