Timely follow-up of positive cancer screening results: A systematic review and recommendations from the PROSPR Consortium.

Timely follow-up for positive cancer screening results remains suboptimal, and the evidence base to inform decisions on optimizing the timeliness of diagnostic testing is unclear. This systematic review evaluated published studies regarding time to follow-up after a positive screening for breast, cervical, colorectal, and lung cancers. The quality of available evidence was very low or low across cancers, with potential attenuated or reversed associations from confounding by indication in most studies. Overall, evidence suggested that the risk for poorer cancer outcomes rises with longer wait times that vary within and across cancer types, which supports performing diagnostic testing as soon as feasible after the positive result, but evidence for specific time targets is limited. Within these limitations, we provide our opinion on cancer-specific recommendations for times to follow-up and how existing guidelines relate to the current evidence. Thresholds set should consider patient worry, potential for loss to follow-up with prolonged wait times, and available resources. Research is needed to better guide the timeliness of diagnostic follow-up, including considerations for patient preferences and existing barriers, while addressing methodological weaknesses. Research is also needed to identify effective interventions for reducing wait times for diagnostic testing, particularly in underserved or low-resource settings. CA Cancer J Clin 2018;68:199-216. © 2018 American Cancer Society.

Intensive Care Unit Capacity Strain and Outcomes of Critical Illness in a Resource-Limited Setting: A 2-Hospital Study in South Africa.

OBJECTIVE: To measure the association of intensive care unit (ICU) capacity strain with processes of care and outcomes of critical illness in a resource-limited setting. METHODS: We performed a retrospective cohort study of 5332 patients referred to the ICUs at 2 public hospitals in South Africa using the country's first published multicenter electronic critical care database. We assessed the association between multiple ICU capacity strain metrics (ICU occupancy, turnover, census acuity, and referral burden) at different exposure time points (ICU referral, admission, and/or discharge) with clinical and process of care outcomes. The association of ICU capacity strain at the time of ICU admission with ICU length of stay (LOS), the primary outcome, was analyzed with a multivariable Cox proportional hazard model. Secondary outcomes of ICU triage decision (with strain at ICU referral), ICU mortality (with strain at ICU admission), and ICU LOS (with strain at ICU discharge), were analyzed with linear and logistic multivariable regression. RESULTS: No measure of ICU capacity strain at the time of ICU admission was associated with ICU LOS, the primary outcome. The ICU occupancy at the time of ICU admission was associated with increased odds of ICU mortality (odds ratio = 1.07, 95% confidence interval: 1.02-1.11; P = .004), a secondary outcome, such that a 10% increase in ICU occupancy would be associated with a 7% increase in the odds of ICU mortality. CONCLUSIONS: In a resource-limited setting in South Africa, ICU capacity strain at the time of ICU admission was not associated with ICU LOS. In secondary analyses, higher ICU occupancy at the time of ICU admission, but not other measures of capacity strain, was associated with increased odds of ICU mortality.

Discriminative Accuracy of Physician and Nurse Predictions for Survival and Functional Outcomes 6 Months After an ICU Admission.

IMPORTANCE: Predictions of long-term survival and functional outcomes influence decision making for critically ill patients, yet little is known regarding their accuracy. OBJECTIVE: To determine the discriminative accuracy of intensive care unit (ICU) physicians and nurses in predicting 6-month patient mortality and morbidity, including ambulation, toileting, and cognition. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study conducted in 5 ICUs in 3 hospitals in Philadelphia, Pennsylvania, and enrolling patients who spent at least 3 days in the ICU from October 2013 until May 2014 and required mechanical ventilation, vasopressors, or both. These patients' attending physicians and bedside nurses were also enrolled. Follow-up was completed in December 2014. MAIN OUTCOMES AND MEASURES: ICU physicians' and nurses' binary predictions of in-hospital mortality and 6-month outcomes, including mortality, return to original residence, ability to toilet independently, ability to ambulate up 10 stairs independently, and ability to remember most things, think clearly, and solve day-to-day problems (ie, normal cognition). For each outcome, physicians and nurses provided a dichotomous prediction and rated their confidence in that prediction on a 5-point Likert scale. Outcomes were assessed via interviews with surviving patients or their surrogates at 6 months. Discriminative accuracy was measured using positive and negative likelihood ratios (LRs), C statistics, and other operating characteristics. RESULTS: Among 340 patients approached, 303 (89%) consented (median age, 62 years [interquartile range, 53-71]; 57% men; 32% African American); 6-month follow-up was completed for 299 (99%), of whom 169 (57%) were alive. Predictions were made by 47 physicians and 128 nurses. Physicians most accurately predicted 6-month mortality (positive LR, 5.91 [95% CI, 3.74-9.32]; negative LR, 0.41 [95% CI, 0.33-0.52]; C statistic, 0.76 [95% CI, 0.72-0.81]) and least accurately predicted cognition (positive LR, 2.36 [95% CI, 1.36-4.12]; negative LR, 0.75 [95% CI, 0.61-0.92]; C statistic, 0.61 [95% CI, 0.54-0.68]). Nurses most accurately predicted in-hospital mortality (positive LR, 4.71 [95% CI, 2.94-7.56]; negative LR, 0.61 [95% CI, 0.49-0.75]; C statistic, 0.68 [95% CI, 0.62-0.74]) and least accurately predicted cognition (positive LR, 1.50 [95% CI, 0.86-2.60]; negative LR, 0.88 [95% CI, 0.73-1.06]; C statistic, 0.55 [95% CI, 0.48-0.62]). Discriminative accuracy was higher when physicians and nurses were confident about their predictions (eg, for physicians' confident predictions of 6-month mortality: positive LR, 33.00 [95% CI, 8.34-130.63]; negative LR, 0.18 [95% CI, 0.09-0.35]; C statistic, 0.90 [95% CI, 0.84-0.96]). Compared with a predictive model including objective clinical variables, a model that also included physician and nurse predictions had significantly higher discriminative accuracy for in-hospital mortality, 6-month mortality, and return to original residence (P < .01 for all). CONCLUSIONS AND RELEVANCE: ICU physicians' and nurses' discriminative accuracy in predicting 6-month outcomes of critically ill patients varied depending on the outcome being predicted and confidence of the predictors. Further research is needed to better understand how clinicians derive prognostic estimates of long-term outcomes.

A randomized trial of nighttime physician staffing in an intensive care unit.

BACKGROUND: Increasing numbers of intensive care units (ICUs) are adopting the practice of nighttime intensivist staffing despite the lack of experimental evidence of its effectiveness. METHODS: We conducted a 1-year randomized trial in an academic medical ICU of the effects of nighttime staffing with in-hospital intensivists (intervention) as compared with nighttime coverage by daytime intensivists who were available for consultation by telephone (control). We randomly assigned blocks of 7 consecutive nights to the intervention or the control strategy. The primary outcome was patients' length of stay in the ICU. Secondary outcomes were patients' length of stay in the hospital, ICU and in-hospital mortality, discharge disposition, and rates of readmission to the ICU. For length-of-stay outcomes, we performed time-to-event analyses, with data censored at the time of a patient's death or transfer to another ICU. RESULTS: A total of 1598 patients were included in the analyses. The median Acute Physiology and Chronic Health Evaluation (APACHE) III score (in which scores range from 0 to 299, with higher scores indicating more severe illness) was 67 (interquartile range, 47 to 91), the median length of stay in the ICU was 52.7 hours (interquartile range, 29.0 to 113.4), and mortality in the ICU was 18%. Patients who were admitted on intervention days were exposed to nighttime intensivists on more nights than were patients admitted on control days (median, 100% of nights [interquartile range, 67 to 100] vs. median, 0% [interquartile range, 0 to 33]; P<0.001). Nonetheless, intensivist staffing on the night of admission did not have a significant effect on the length of stay in the ICU (rate ratio for the time to ICU discharge, 0.98; 95% confidence interval [CI], 0.88 to 1.09; P=0.72), ICU mortality (relative risk, 1.07; 95% CI, 0.90 to 1.28), or any other end point. Analyses restricted to patients who were admitted at night showed similar results, as did sensitivity analyses that used different definitions of exposure and outcome. CONCLUSIONS: In an academic medical ICU in the United States, nighttime in-hospital intensivist staffing did not improve patient outcomes. (Funded by University of Pennsylvania Health System and others; ClinicalTrials.gov number, NCT01434823.).

Comparison of Treatment Response in Idiopathic and Connective Tissue Disease-associated Pulmonary Arterial Hypertension.

RATIONALE: Studies suggest that patients with connective tissue disease-associated pulmonary arterial hypertension (CTD-PAH) have a poorer treatment response to therapies for PAH compared with patients with idiopathic PAH (IPAH), but individual randomized controlled trials (RCTs) have been underpowered to examine differences within these subgroups. OBJECTIVES: To compare the effect of therapy for PAH in CTD-PAH versus IPAH. METHODS: We obtained individual participant data from phase III placebo-controlled RCTs of therapies for PAH submitted to the U.S. Food and Drug Administration for drug approval. A treatment-by-diagnosis interaction term evaluated differences in treatment response between CTD-PAH and IPAH. Outcomes included change in 6-minute-walk distance (∆6MWD) from baseline to 12 weeks, clinical worsening, and all-cause mortality. MEASUREMENTS AND MAIN RESULTS: The study sample included 827 participants with CTD-PAH and 1,935 with IPAH from 11 RCTs. Patients with CTD-PAH had less improvement in 6MWD when assigned to active treatment versus placebo compared with patients with IPAH (difference in treatment effect on ∆6MWD in CTD-PAH vs. IPAH, -17.3 m; 90% confidence interval, -31.3 to -3.3; P for interaction = 0.043). Treatment was less effective in reducing the occurrence of clinical worsening in CTD-PAH versus IPAH (P for interaction = 0.012), but there was no difference in the placebo-adjusted effect of treatment on mortality (P for interaction = 0.65). CONCLUSIONS: Treatment for PAH was less effective in CTD-PAH compared with IPAH in terms of increasing 6MWD and preventing clinical worsening. The heterogeneity of treatment response supports the need for identifying therapies that are more effective for CTD-PAH.

Are hemodynamics surrogate end points in pulmonary arterial hypertension?

BACKGROUND: Although frequently assessed in trials and clinical practice, hemodynamic response to therapy has never been validated as a surrogate end point for clinical events in pulmonary arterial hypertension (PAH). METHODS AND RESULTS: We performed a patient-level pooled analysis of 4 randomized, placebo-controlled trials to determine whether treatment-induced changes in hemodynamic values at 12 weeks accounted for the relationship between treatment assignment and the probability of early clinical events (death, lung transplantation, atrial septostomy, PAH hospitalization, withdrawal for clinical worsening, or escalation in PAH therapy). We included 1119 subjects with PAH. The median (interquartile range) age was 48 years (37-59 years), and 23% were men. A total of 656 patients (59%) received active therapy (101 [15%] iloprost, 118 [18%] sitaxsentan, 204 [31%] sildenafil, and 233 [36%] subcutaneous treprostinil). Active treatment significantly lowered right atrial pressure, mean pulmonary artery pressure, and pulmonary vascular resistance and increased cardiac output and index (P<0.01 for all). Changes in hemodynamic values (except for right atrial pressure and mean pulmonary artery pressure) were significantly associated with the risk of a clinical event (P<0.02 for all). Although active treatment approximately halved the odds of a clinical event compared with placebo (P<0.001), changes in hemodynamics accounted for only 1.2% to 13.9% of the overall treatment effect. CONCLUSIONS: Treatment-induced changes in hemodynamics at 12 weeks only partially explain the impact of therapy on the probability of early clinical events in PAH. These findings suggest that resting hemodynamics are not valid surrogate end points for short-term events in PAH clinical trials.

An Observational Study of Decision Making by Medical Intensivists.

OBJECTIVES: The ICU is a place of frequent, high-stakes decision making. However, the number and types of decisions made by intensivists have not been well characterized. We sought to describe intensivist decision making and determine how the number and types of decisions are affected by patient, provider, and systems factors. DESIGN: Direct observation of intensivist decision making during patient rounds. SETTING: Twenty-four-bed academic medical ICU. SUBJECTS: Medical intensivists leading patient care rounds. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: During 920 observed patient rounds on 374 unique patients, intensivists made 8,174 critical care decisions (mean, 8.9 decisions per patient daily, 102.2 total decisions daily) over a mean of 3.7 hours. Patient factors associated with increased numbers of decisions included a shorter time since ICU admission and an earlier slot in rounding order (both p < 0.05). Intensivist identity explained the greatest proportion of variance in number of decisions per patient even when controlling for all other factors significant in bivariable regression. A given intensivist made more decisions per patient during days later in the 14-day rotation (p < 0.05). Female intensivists made significantly more decisions than male intensivists (p < 0.05). CONCLUSIONS: Intensivists made over 100 daily critical care decisions during rounds. The number of decisions was influenced by a variety of patient- and system-related factors and was highly variable among intensivists. Future work is needed to explore effects of the decision-making burden on providers' choices and on patient outcomes.

Mortality among patients admitted to strained intensive care units.

RATIONALE: The aging population may strain intensive care unit (ICU) capacity and adversely affect patient outcomes. Existing fluctuations in demand for ICU care offer an opportunity to explore such relationships. OBJECTIVES: To determine whether transient increases in ICU strain influence patient mortality, and to identify characteristics of ICUs that are resilient to surges in capacity strain. METHODS: Retrospective cohort study of 264,401 patients admitted to 155 U.S. ICUs from 2001 to 2008. We used logistic regression to examine relationships of measures of ICU strain (census, average acuity, and proportion of new admissions) near the time of ICU admission with mortality. MEASUREMENTS AND MAIN RESULTS: A total of 36,465 (14%) patients died in the hospital. ICU census on the day of a patient's admission was associated with increased mortality (odds ratio [OR], 1.02 per standardized unit increase; 95% confidence interval [CI]: 1.00, 1.03). This effect was greater among ICUs employing closed (OR, 1.07; 95% CI: 1.02, 1.12) versus open (OR, 1.01; 95% CI: 0.99, 1.03) physician staffing models (interaction P value = 0.02). The relationship between census and mortality was stronger when the census was composed of higher acuity patients (interaction P value < 0.01). Averaging strain over the first 3 days of patients' ICU stays yielded similar results except that the proportion of new admissions was now also associated with mortality (OR, 1.04 for each 10% increase; 95% CI: 1.02, 1.06). CONCLUSIONS: Several sources of ICU strain are associated with small but potentially important increases in patient mortality, particularly in ICUs employing closed staffing models. Although closed ICUs may promote favorable outcomes under static conditions, they are susceptible to being overwhelmed by patient influxes.

Outcomes among patients discharged from busy intensive care units.

BACKGROUND: Strains on the capacities of intensive care units (ICUs) may influence the quality of ICU-to-floor transitions. OBJECTIVE: To determine how 3 metrics of ICU capacity strain (ICU census, new admissions, and average acuity) measured on days of patient discharges influence ICU length of stay (LOS) and post-ICU discharge outcomes. DESIGN: Retrospective cohort study from 2001 to 2008. SETTING: 155 ICUs in the United States. PATIENTS: 200 730 adults discharged from ICUs to hospital floors. MEASUREMENTS: Associations between ICU capacity strain metrics and discharged patient ICU LOS, 72-hour ICU readmissions, subsequent in-hospital death, post-ICU discharge LOS, and hospital discharge destination. RESULTS: Increases in the 3 strain variables on the days of ICU discharge were associated with shorter preceding ICU LOS (all P < 0.001) and increased odds of ICU readmissions (all P < 0.050). Going from the 5th to 95th percentiles of strain was associated with a 6.3-hour reduction in ICU LOS (95% CI, 5.3 to 7.3 hours) and a 1.0% increase in the odds of ICU readmission (CI, 0.6% to 1.5%). No strain variable was associated with increased odds of subsequent death, reduced odds of being discharged home from the hospital, or longer total hospital LOS. LIMITATION: Long-term outcomes could not be measured. CONCLUSION: When ICUs are strained, triage decisions seem to be affected such that patients are discharged from the ICU more quickly and, perhaps consequentially, have slightly greater odds of being readmitted to the ICU. However, short-term patient outcomes are unaffected. These results suggest that bed availability pressures may encourage physicians to discharge patients from the ICU more efficiently and that ICU readmissions are unlikely to be causally related to patient outcomes. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality; National Heart, Lung, and Blood Institute; and Society of Critical Care Medicine.

Validation of 6-minute walk distance as a surrogate end point in pulmonary arterial hypertension trials.

BACKGROUND: Nearly all available treatments for pulmonary arterial hypertension have been approved based on change in 6-minute walk distance (Δ6MWD) as a clinically important end point, but its validity as a surrogate end point has never been shown. We aimed to validate the difference in Δ6MWD against the probability of a clinical event in pulmonary arterial hypertension trials. METHODS AND RESULTS: First, to determine whether Δ6MWD between baseline and 12 weeks mediated the relationship between treatment assignment and development of clinical events, we conducted a pooled analysis of patient-level data from the 10 randomized placebo-controlled trials previously submitted to the US Food and Drug Administration (n=2404 patients). Second, to identify a threshold effect for the Δ6MWD that indicated a statistically significant reduction in clinical events, we conducted a meta-regression among 21 drug/dose-level combinations. Δ6MWD accounted for 22.1% (95% confidence interval, 12.1%- 31.1%) of the treatment effect (P<0.001). The meta-analysis showed an average difference in Δ6MWD of 22.4 m (95% confidence interval, 17.4-27.5 m), favoring active treatment over placebo. Active treatment decreased the probability of a clinical event (summary odds ratio, 0.44; 95% confidence interval, 0.33-0.57). The meta-regression revealed a significant threshold effect of 41.8 m. CONCLUSIONS: Our results suggest that Δ6MWD does not explain a large proportion of the treatment effect, has only modest validity as a surrogate end point for clinical events, and may not be a sufficient surrogate end point. Further research is necessary to determine whether the threshold value of 41.8 m is valid for long-term outcomes or whether it differs among trials using background therapy or lacking placebo controls entirely.

Real-world cost of care and site of care in patients with multiple sclerosis initiating infused disease-modifying therapies.

AIM: Evaluate the real-world costs over two years and costs by site of care for ocrelizumab (OCR), natalizumab (NTZ), and alemtuzumab (ATZ) in patients with multiple sclerosis (MS). METHODS: This retrospective study used HealthCore Integrated Research Database and included continuously enrolled adults with MS initiating OCR, NTZ, and ATZ between April 2017 and July 2019 (i.e. patient identification period). Annual total cost of care (pharmacy and medical costs) was evaluated for the first- and second-year of follow-up, further stratified by site of care. Costs were measured using health plan allowed amount and adjusted to 2019 US dollars. Sensitivity analyses were conducted in patients who completed yearly dosing schedule according to Food and Drug Administration approved prescribing information. RESULTS: Overall, 1,058, 166, and 46 patients were included in OCR, NTZ, and ATZ cohorts, respectively. Mean (standard deviation [SD]) total cost of care during first- and second-year follow-up were $125,597 ($72,274) and $109,618 ($75,085) for OCR, $117,033 ($57,102) and $106,626 ($54,872) for NTZ, and $179,809 ($97,530) and $108,636 ($77,973) for ATZ. Infusible drug cost was the main driver in all three cohorts accounting for >78% of the total costs. Annual total cost of care increased substantially after patients started/switched to infusible DMTs. Across site of care, hospital outpatient infusion was common (OCR 58%, NTZ 37%, ATZ 49%) and expensive followed by physician office infusion (OCR 28%, NTZ 40%, ATZ 16%); home infusion was the least common (<10%) and least expensive. LIMITATIONS: The results were limited to commercially insured patients (specifically those with Anthem-affiliated health plans). CONCLUSIONS: Real-world costs increased after patients started/switched to infusible DMTs. Drug cost is the main driver for the total costs, which varied substantially by site of care. Controlling drug cost markups and using home setting for infusion can reduce costs in the treatment of MS patients.

Ocrelizumab (OCR), natalizumab (NTZ), and alemtuzumab (ATZ) are infusible drugs to treat patients with multiple sclerosis (MS). We did a study to understand the costs of these infusible MS drugs in real-world settings by analyzing a patients' pharmacy and medical claims database. A total of 1,058 patients were included. We found that the annual total costs increased substantially after patients started to use these infusible MS drugs. Specifically, the average first- and second-year total costs for patients were $125,597 and $109,618 for OCR, $117,033 and $106,626 for NTZ, and $179,809 and $108,636 for ATZ, respectively. We also found that the cost of the drug itself is the main driver for the overall healthcare spending, accounting for >78% of the total costs. Additionally, we found that the cost varies depending on where patients receive these infusible MS drugs, and generally speaking, infusions received from hospital outpatient settings would be more expensive than received from home settings. In summary, this study showed that the real-world costs of these infusible MS drugs are very high. Shifting patients away from more costly hospital outpatient departments or using MS drugs that do not require infusion resources (e.g. oral/self-injectable) may help reduce the overall healthcare spending on MS.

N-of-1 trials in the medical literature: a systematic review.

BACKGROUND: N-of-1 trials (multiple crossover studies conducted in single individuals) may be ideal for determining individual treatment effects and as a tool to estimate heterogeneity of treatment effects (HTE) in a population. However, comprehensive data on n-of-1 trial methodology and analysis is lacking. We performed this study to describe n-of-1 trial characteristics, examine treatment changes resulting from n-of-1 trial participation, and to determine if trial reporting is adequate for estimating HTE. METHODS: We undertook a systematic review of n-of-1 trials published between 1985 and December 2010. Included trials were those having individual treatment episodes as the unit of randomization and reporting individual-specific treatment effects. We abstracted trial characteristics, treatment change information, and analytic methods. RESULTS: We included 108 trials reporting on 2154 participants. Approximately half (49%) of the trials used a statistical cutoff to determine a superior treatment, whereas the remainder used a graphical comparison (25%) or a clinical significance cutoff (20%). Sixty-seven trials, reporting on 488 people, provided treatment change information: 54% of participants had subsequent treatment decisions consistent with the results of the trial, 8% had decisions inconsistent with trial results, and 38% had ambiguous results. Less than half of the trials (45%) reported adequate information to facilitate the calculation of HTE. CONCLUSION: N-of-1 trials are a useful tool for enhancing therapeutic precision in a range of conditions and should be conducted more often. To facilitate future meta-analysis, and the estimation of HTE, researchers reporting n-of-1 trial results should clearly describe individual data.

What's behind the white coat: Potential mechanisms of physician-attributable variation in critical care.

BACKGROUND: Critical care intensity is known to vary across regions and centers, yet the mechanisms remain unidentified. Physician behaviors have been implicated in the variability of intensive care near the end of life, but physician characteristics that may underlie this association have not been determined. PURPOSE: We sought to identify behavioral attributes that vary among intensivists to generate hypotheses for mechanisms of intensivist-attributable variation in critical care delivery. METHODS: We administered a questionnaire to intensivists who participated in a prior cohort study in which intensivists made prognostic estimates. We evaluated the degree to which scores on six attribute measures varied across intensivists. Measures were selected for their relevance to preference-sensitive critical care: a modified End-of-Life Preferences (EOLP) scale, Life Orientation Test-Revised (LOT-R), Jefferson Scale of Empathy (JSE), Physicians' Reactions to Uncertainty (PRU) scale, Collett-Lester Fear of Death (CLFOD) scale, and a test of omission bias. We conducted regression analyses assessing relationships between intensivists' attribute scores and their prognostic accuracy, as physicians' prognostic accuracy may influence preference-sensitive decisions. RESULTS: 20 of 25 eligible intensivists (80%) completed the questionnaire. Intensivists' scores on the EOLP, LOT-R, PRU, CLFOD, and omission bias measures varied considerably, while their responses on the JSE scale did not. There were no consistent associations between attribute scores and prognostic accuracy. CONCLUSIONS: Intensivists vary in feasibly measurable attributes relevant to preference-sensitive critical care delivery. These attributes represent candidates for future research aimed at identifying mechanisms of clinician-attributable variation in critical care and developing effective interventions to reduce undue variation.

Intuitive vs Deliberative Approaches to Making Decisions About Life Support: A Randomized Clinical Trial.

Importance: Patients with serious illnesses are often encouraged to actively deliberate about the desirability of life support. Yet it is unknown whether deliberation changes the substance or quality of such decisions. Objective: To identify differences in decisions about life support interventions and goals of care made intuitively vs deliberatively by patients with serious illnesses. Design, Setting, and Participants: Randomized clinical trial in which patients were asked to express treatment preferences in a series of clinical scenarios. Participants were 199 hospitalized patients aged 60 years and older with serious oncologic, cardiac, and pulmonary illnesses treated in a large, urban academic hospital from July 1, 2015, through March 15, 2016. Interventions: Patients in the intuitive group were subjected to a cognitive load and instructed to answer each question immediately based on gut instinct. Patients in the deliberative group were not cognitively loaded, were instructed to think carefully about their answers, and were required to explain their answers. Main Outcomes and Measures: Choices regarding life support (4 scenarios) and goals of care (1 scenario), concordance of these choices with patients' valuations of health states that could follow from them, and decisional uncertainty. Results: Of 199 patients, 132 (66%) were male and the mean (SD) age was 67.2 (5.0) years. Similar proportions of patients in the intuitive group (n = 97) and the deliberative group (n = 102) said they would accept a feeding tube for chronic aspiration (42% vs 44%, respectively; difference, -2%; 95% CI, -16% to 12%; P = .79), antibiotics for life-threatening infection in the event of terminal illness (39% vs 43%, respectively; difference, -4%; 95% CI, -18% to 10%; P = .57), a trial of mechanical ventilation (59% vs 60%, respectively; difference,-1%; 95% CI, -15% to 13%; P = .88), and a tracheostomy tube (37% vs 41%, respectively; difference, -4%; 95% CI, -22% to 13%; P = .64). Patients in the deliberative group were slightly more likely than patients in the intuitive group to choose a palliative approach to treatment in the event of serious illness (45% vs 30%, respectively; difference, 15%; 95% CI, 1%-29%; P = .04). Across scenarios, decisional uncertainty was similar between the 2 groups (all P > .05), and intuitive decisions were either equally or more closely aligned with patients' health state valuations than deliberative decisions. Conclusions and Relevance: In this study, encouraging hospitalized patients with serious illnesses to deliberate on end-of-life decisions did not change the content or improve the quality of these decisions. It is important to evaluate whether decision aids and structured communication interventions improve seriously ill patients' choices. Trial Registration: ClinicalTrials.gov Identifier: NCT02487810.

Effect of Financial Incentives on Patient Use of Mailed Colorectal Cancer Screening Tests: A Randomized Clinical Trial.

Importance: Mailing fecal immunochemical test (FIT) kits to patients' homes has been shown to boost colorectal cancer screening rates, but response rates remain limited, and organized programs typically require repeated outreach attempts. Behavioral economics has shown that offering salient financial incentives to patients may increase participation in preventive health. Objective: To compare the impact of different financial incentives for mailed FIT outreach. Design, Setting, and Participants: This 4-parallel-arm randomized clinical trial included patients aged 50 to 75 years who had an established primary care clinician, at least 2 visits in the prior 2 years, and were eligible for colorectal cancer screening and not up-to-date. This study was conducted at urban primary care practices at an academic health system from December 2015 to February 2018. Data analysis was conducted from March 2018 to September 2018. Interventions: Eligible patients received a letter from their primary care clinician that included a mailed FIT kit and instructions for use. They were randomized in a 1:1:1:1 ratio to receive (1) no financial incentive; (2) an unconditional $10 incentive included with the mailing; (3) a $10 incentive conditional on FIT completion; or (4) a conditional lottery with a 1-in-10 chance of winning $100 after FIT completion. Main Outcomes and Measures: Fecal immunochemical test completion within 2 and 6 months of initial outreach. Results: A total of 897 participants were randomized, with a median age of 57 years (interquartile range, 52-62 years); 56% were women, and 69% were black. The overall completion rate across all arms was 23.5% at 2 months. The completion rate at 2 months was 26.0% (95% CI, 20.4%-32.3%) in the no incentive arm, 27.2% (95% CI, 21.5%-33.6%) in the unconditional incentive arm, 23.2% (95% CI, 17.9%-29.3%) in the conditional incentive arm, and 17.7% (95% CI, 13.0%-23.3%) in the lottery incentive arm. None of the arms with an incentive were statistically superior to the arm without incentive. The overall FIT completion rate across all arms was 28.9% at 6 months, and there was also no difference by arm. The completion rate at 6 months was 32.7% (95% CI, 26.6%-39.3%) in the no incentive arm, 31.7% (95% CI, 25.7%-38.2%) in the unconditional incentive arm, 26.8% (95% CI, 21.1%-33.1%) in the conditional incentive arm, and 24.3% (95% CI, 18.9%-30.5%) in the lottery incentive arm. Conclusions and Relevance: Mailed FIT resulted in high colorectal cancer screening response rates in this population, but different forms of financial incentives of the same expected value ($10) did not incrementally increase FIT completion rates. The incentive value may have been too small or financial incentives may not be effective in this context. Trial Registration: ClinicalTrials.gov Identifier: NCT02594150.

Active Choice Intervention Increases Advance Directive Completion: A Randomized Trial.

Background. Many people recognize the potential benefits of advance directives (ADs), yet few actually complete them. It is unknown whether an active choice intervention influences AD completion. Methods. New employees were randomized to an active choice intervention (n = 642) or usual care (n = 637). The active choice intervention asked employees to complete an AD, confirm prior AD completion, or fill out a declination form. In usual care, participants could complete an AD, confirm prior completion, or skip the task. We used multivariable logistic regression to assess the relationship between the intervention arm and both AD completion online and the return of a signed AD by mail, as well as assess interactions between intervention group and age, gender, race, and clinical degree status. Results. Participants assigned to the active choice intervention more commonly completed ADs online (35.1% v. 20.4%, P < 0.001) (odds ratio [OR] = 2.10; 95% confidence interval [CI] = 1.63-2.71; number needed to treat = 6.8) and returned signed ADs by mail (7.8% v. 3.9%, P = 0.003; number needed to treat = 25.6). The effect of the intervention was significantly greater among men (OR = 4.13; 95% CI = 2.32-7.35) than among women (OR = 1.74; 95% CI = 1.30-2.32) (interaction P value < 0.001). Responses to all eight choices made in the ADs were similar between groups (all P > 0.10). Limitations. A young and healthy participant may not benefit from AD completion as an older or seriously ill patient would. Conclusions. The active choice intervention significantly increased the proportion of participants completing an AD without changing the choices in ADs. This relationship was especially strong among men and may be a useful method to increase AD completion rates without altering choices.

Associations of Intensive Care Unit Capacity Strain with Disposition and Outcomes of Patients with Sepsis Presenting to the Emergency Department.

RATIONALE: Intensive care unit (ICU) capacity strain refers to the potential limits placed on an ICU's ability to provide high-quality care for all patients who may need it at a given time. Few studies have investigated how fluctuations in ICU capacity strain might influence care outside the ICU. OBJECTIVES: To determine whether ICU capacity strain is associated with initial level of inpatient care and outcomes for emergency department (ED) patients hospitalized for sepsis. METHODS: We performed a retrospective cohort study of patients with sepsis admitted from the ED to a medical ward or ICU at three hospitals within the University of Pennsylvania Health System between 2012 and 2015. Patients were excluded if they required life support therapies, defined as invasive or noninvasive ventilatory support or vasopressors, at the time of admission. The exposures were four measures of ICU capacity strain at the time of the ED disposition decision: ICU occupancy, ICU turnover, ICU census acuity, and ward occupancy. The primary outcome was the decision to admit to a ward or to an ICU. Secondary analyses assessed the association of ICU capacity strain with in-hospital outcomes, including mortality. RESULTS: Among 77,142 hospital admissions from the ED, 3,067 patients met the study's eligibility criteria. The ICU capacity strain metrics varied between and within study hospitals over time. In unadjusted analyses, ICU occupancy, ICU turnover, ICU census acuity, and ward occupancy were all negatively associated with ICU admission. In the fully adjusted model including patient-level covariates, only ICU occupancy remained associated with ICU admission (odds ratio, 0.87; 95% confidence interval, 0.79-0.96; P = 0.005), such that a 10% increase in ICU occupancy (e.g., one additional patient in a 10-bed ICU) was associated with a 13% decrease in the odds of ICU admission. Among the subset of patients admitted initially from the ED to a medical ward, ICU occupancy at the time of admission was associated with increased odds of hospital mortality (odds ratio, 1.61; 95% confidence interval, 1.21-2.14; P = 0.001). CONCLUSIONS: The odds that patients in the ED with sepsis who do not require life support therapies will be admitted to the ICU are reduced when those ICUs experience high occupancy but not high levels of other previously explored measures of capacity strain. Patients with sepsis admitted to the wards during times of high ICU occupancy had increased odds of hospital mortality.