Barriers and Facilitators of Surrogates Providing Consent for Critically Ill Patients in Clinical Trials: A Qualitative Study

BACKGROUND

Enrollment into critical care clinical trials is often hampered by the need to rely on surrogate decision-makers. To identify potential interventions facilitating enrollment into critical care clinical trials, a better understanding of surrogate decision-making for critical care clinical trial enrollment is needed.

RESEARCH QUESTION

What are the barriers and facilitators of critical care trial enrollment? What are surrogate decision-makers' perspectives on proposed interventions to facilitate trial enrollment?

STUDY DESIGN AND METHODS

We conducted semistructured interviews with 20 surrogate decision-makers of critically ill patients receiving mechanical ventilation. The interviews were recorded and transcribed verbatim, and analyzed for themes using an inductive approach.

RESULTS

Twenty surrogate decision-makers of critically ill patients participated in the semistructured interviews. Thematic analysis confirmed previous research showing that trust in the system, assessing the risks and benefits of trial participation, the desire to help others, and building medical knowledge as important motivating factors for trial enrollment. Two previously undescribed concerns among surrogate decision-makers of critically ill patients were identified, including the potential to interfere with clinical treatment decisions and negative sentiment about placebos. Surrogates viewed public recognition and charitable donations for participation as favorable potential interventions to encourage trial enrollment. However, participants viewed direct financial incentives and prioritizing research participants during medical rounds negatively.

INTERPRETATION

This study confirms and extends previous findings that health system trust, study risks and benefits, altruism, knowledge generation, interference with clinical care, and placebos are key concerns and barriers for surrogate decision-makers to enroll patients in critical care trials. Future studies are needed to evaluate if charitable giving on the patient's behalf and public recognition are effective strategies to promote enrollment into critical care trials.

Defining the Time-limited Trial for Patients with Critical Illness: An Official American Thoracic Society Workshop Report

In critical care, the specific, structured approach to patient care known as a "time-limited trial" has been promoted in the literature to help patients, surrogate decision makers, and clinicians navigate consequential decisions about life-sustaining therapy in the face of uncertainty. Despite promotion of the time-limited trial approach, a lack of consensus about its definition and essential elements prevents optimal clinical use and rigorous evaluation of its impact. The objectives of this American Thoracic Society Workshop Committee were to establish a consensus definition of a time-limited trial in critical care, identify the essential elements for conducting a time-limited trial, and prioritize directions for future work. We achieved these objectives through a structured search of the literature, a modified Delphi process with 100 interdisciplinary and interprofessional stakeholders, and iterative committee discussions. We conclude that a time-limited trial for patients with critical illness is a collaborative plan among clinicians and a patient and/or their surrogate decision makers to use life-sustaining therapy for a defined duration, after which the patient's response to therapy informs the decision to continue care directed toward recovery, transition to care focused exclusively on comfort, or extend the trial's duration. The plan's 16 essential elements follow four sequential phases: consider, plan, support, and reassess. We acknowledge considerable gaps in evidence about the impact of time-limited trials and highlight a concern that if inadequately implemented, time-limited trials may perpetuate unintended harm. Future work is needed to better implement this defined, specific approach to care in practice through a person-centered equity lens and to evaluate its impact on patients, surrogates, and clinicians.

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.

A vignette-based evaluation of ChatGPT's ability to provide appropriate and equitable medical advice across care contexts

ChatGPT is a large language model trained on text corpora and reinforced with human supervision. Because ChatGPT can provide human-like responses to complex questions, it could become an easily accessible source of medical advice for patients. However, its ability to answer medical questions appropriately and equitably remains unknown. We presented ChatGPT with 96 advice-seeking vignettes that varied across clinical contexts, medical histories, and social characteristics. We analyzed responses for clinical appropriateness by concordance with guidelines, recommendation type, and consideration of social factors. Ninety-three (97%) responses were appropriate and did not explicitly violate clinical guidelines. Recommendations in response to advice-seeking questions were completely absent (N = 34, 35%), general (N = 18, 18%), or specific (N = 44, 46%). 53 (55%) explicitly considered social factors like race or insurance status, which in some cases changed clinical recommendations. ChatGPT consistently provided background information in response to medical questions but did not reliably offer appropriate and personalized medical advice.

Using the Hospital Frailty Risk Score to assess mortality risk in older medical patients admitted to the intensive care unit

BACKGROUND

Prognostic information at the time of hospital discharge can help guide goals-of-care discussions for future care. We sought to assess the association between the Hospital Frailty Risk Score (HFRS), which may highlight patients' risk of adverse outcomes at the time of hospital discharge, and in-hospital death among patients admitted to the intensive care unit (ICU) within 12 months of a previous hospital discharge.

METHODS

We conducted a multicentre retrospective cohort study that included patients aged 75 years or older admitted at least twice over a 12-month period to the general medicine service at 7 academic centres and large community-based teaching hospitals in Toronto and Mississauga, Ontario, Canada, from Apr. 1, 2010, to Dec. 31, 2019. The HFRS (categorized as low, moderate or high frailty risk) was calculated at the time of discharge from the first hospital admission. Outcomes included ICU admission and death during the second hospital admission.

RESULTS

The cohort included 22 178 patients, of whom 1767 (8.0%) were categorized as having high frailty risk, 9464 (42.7%) as having moderate frailty risk, and 10 947 (49.4%) as having low frailty risk. One hundred patients (5.7%) with high frailty risk were admitted to the ICU, compared to 566 (6.0%) of those with moderate risk and 790 (7.2%) of those with low risk. After adjustment for age, sex, hospital, day of admission, time of admission and Laboratory-based Acute Physiology Score, the odds of ICU admission were not significantly different for patients with high (adjusted odds ratio [OR] 0.99, 95% confidence interval [CI] 0.78 to 1.23) or moderate (adjusted OR 0.97, 95% CI 0.86 to 1.09) frailty risk compared to those with low frailty risk. Among patients admitted to the ICU, 75 (75.0%) of those with high frailty risk died, compared to 317 (56.0%) of those with moderate risk and 416 (52.7%) of those with low risk. After multivariable adjustment, the risk of death after ICU admission was higher for patients with high frailty risk than for those with low frailty risk (adjusted OR 2.86, 95% CI 1.77 to 4.77).

INTERPRETATION

Among patients readmitted to hospital within 12 months, patients with high frailty risk were similarly likely as those with lower frailty risk to be admitted to the ICU but were more likely to die if admitted to ICU. The HFRS at hospital discharge can inform prognosis, which can help guide discussions for preferences for ICU care during future hospital stays.

"It's that invisible illness": Patient and clinician perspectives on outcomes in pulmonary arterial hypertension treatment

Knowledge of what outcomes are most meaningful to pulmonary arterial hypertension (PAH) stakeholders is limited. In this qualitative study, patients and clinicians endorsed personalized physical activity, symptoms, and psychosocial well-being as key outcomes to assess PAH treatment response, yet few are routinely measured in PAH clinical trials.

Performance drift in a mortality prediction algorithm among patients with cancer during the SARS-CoV-2 pandemic

Sudden changes in health care utilization during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic may have impacted the performance of clinical predictive models that were trained prior to the pandemic. In this study, we evaluated the performance over time of a machine learning, electronic health record-based mortality prediction algorithm currently used in clinical practice to identify patients with cancer who may benefit from early advance care planning conversations. We show that during the pandemic period, algorithm identification of high-risk patients had a substantial and sustained decline. Decreases in laboratory utilization during the peak of the pandemic may have contributed to drift. Calibration and overall discrimination did not markedly decline during the pandemic. This argues for careful attention to the performance and retraining of predictive algorithms that use inputs from the pandemic period.

Palliative Care Early in the Care Continuum among Patients with Serious Respiratory Illness: An Official ATS/AAHPM/HPNA/SWHPN Policy Statement

Background: Patients with serious respiratory illness and their caregivers suffer considerable burdens, and palliative care is a fundamental right for anyone who needs it. However, the overwhelming majority of patients do not receive timely palliative care before the end of life, despite robust evidence for improved outcomes. Goals: This policy statement by the American Thoracic Society (ATS) and partnering societies advocates for improved integration of high-quality palliative care early in the care continuum for patients with serious respiratory illness and their caregivers and provides clinicians and policymakers with a framework to accomplish this. Methods: An international and interprofessional expert committee, including patients and caregivers, achieved consensus across a diverse working group representing pulmonary-critical care, palliative care, bioethics, health law and policy, geriatrics, nursing, physiotherapy, social work, pharmacy, patient advocacy, psychology, and sociology. Results: The committee developed fundamental values, principles, and policy recommendations for integrating palliative care in serious respiratory illness care across seven domains: 1) delivery models, 2) comprehensive symptom assessment and management, 3) advance care planning and goals of care discussions, 4) caregiver support, 5) health disparities, 6) mass casualty events and emergency preparedness, and 7) research priorities. The recommendations encourage timely integration of palliative care, promote innovative primary and secondary or specialist palliative care delivery models, and advocate for research and policy initiatives to improve the availability and quality of palliative care for patients and their caregivers. Conclusions: This multisociety policy statement establishes a framework for early palliative care in serious respiratory illness and provides guidance for pulmonary-critical care clinicians and policymakers for its proactive integration.

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.

Performance Drift in a Mortality Prediction Algorithm during the SARS-CoV-2 Pandemic

Research Objective

Health systems use clinical predictive algorithms to allocate resources to high-risk patients. Such algorithms are trained using historical data and are later implemented in clinical settings. During this implementation period, predictive algorithms are prone to performance changes ("drift") due to exogenous shocks in utilization or shifts in patient characteristics. Our objective was to examine the impact of sudden utilization shifts during the SARS-CoV-2 pandemic on the performance of an electronic health record (EHR)-based prognostic algorithm.

Study Design

We studied changes in the performance of Conversation Connect, a validated machine learning algorithm that predicts 180-day mortality among outpatients with cancer receiving care at medical oncology practices within a large academic cancer center. Conversation Connect generates mortality risk predictions before each encounter using data from 159 EHR variables collected in the six months before the encounter. Since January 2019, Conversation Connect has been used as part of a behavioral intervention to prompt clinicians to consider early advance care planning conversations among patients with ≥10% mortality risk. First, we descriptively compared encounter-level characteristics in the following periods: January 2019-February 2020 ("pre-pandemic"), March-May 2020 ("early-pandemic"), and June-December 2020 ("later-pandemic"). Second, we quantified changes in high-risk patient encounters using interrupted time series analyses that controlled for pre-pandemic trends and demographic, clinical, and practice covariates. Our primary metric of performance drift was false negative rate (FNR). Third, we assessed contributors to performance drift by comparing distributions of key EHR inputs across periods and predicting later pandemic utilization using pre-pandemic inputs.

Population Studied

237,336 in-person and telemedicine medical oncology encounters.

Principal Findings

Age, race, average patient encounters per month, insurance type, comorbidity counts, laboratory values, and overall mortality were similar among encounters in the pre-, early-, and later-pandemic periods. Relative to the pre-pandemic period, the later-pandemic period was characterized by a 6.5-percentage-point decrease (28.2% vs. 34.7%) in high-risk encounters (p<0.001). FNR increased from 41.0% (95% CI 38.0-44.1%) in the pre-pandemic period to 57.5% (95% CI 51.9-63.0%) in the later pandemic period. Compared to the pre-pandemic period, the early and later pandemic periods had higher proportions of telemedicine encounters (0.01% pre-pandemic vs. 20.0% early-pandemic vs. 26.4% later-pandemic) and encounters with no preceding laboratory draws (17.7% pre-pandemic vs. 19.8% early-pandemic vs. 24.1% later-pandemic). In the later pandemic period, observed laboratory utilization was lower than predicted (76.0% vs 81.2%, p<0.001). In the later-pandemic period, mean 180-day mortality risk scores were lower for telemedicine encounters vs. in-person encounters (10.3% vs 11.2%, p<0.001) and encounters with no vs. any preceding laboratory draws (1.5% vs. 14.0%, p<0.001).

Conclusions

During the SARS-CoV-2 pandemic period, the performance of a machine learning prognostic algorithm used to prompt advance care planning declined substantially. Increases in telemedicine and declines in laboratory utilization contributed to lower performance.

Implications for Policy or Practice

This is the first study to show algorithm performance drift due to SARS-CoV-2 pandemic-related shifts in telemedicine and laboratory utilization. These mechanisms of performance drift could apply to other EHR clinical predictive algorithms. Pandemic-related decreases in care utilization may negatively impact the performance of clinical predictive algorithms and warrant assessment and possible retraining of such algorithms.

A systematic review and meta-analysis of enrollment into ARDS and sepsis trials published between 2009 and 2019 in major journals

BACKGROUND

Enrollment problems are common among randomized controlled trials conducted in the ICU. However, little is known about actual trial enrollment rates and influential factors. We set out to determine the overall enrollment rate in recent randomized controlled trials (RCTs) of patients with acute respiratory distress syndrome (ARDS), acute lung injury (ALI), or sepsis, and which factors influenced enrollment rate.

METHODS

We conducted a systematic review by searching Pubmed using predefined terms for ARDS/ALI and sepsis to identify individually RCTs published among the seven highest impact general medicine and seven highest impact critical care journals between 2009 and 2019. Cluster randomized trials were excluded. Data were extracted by two independent reviewers using an electronic database management system. We conducted a random-effects meta-analysis of the eligible trials for the primary outcome of enrollment rate by time and site.

RESULTS

Out of 457 articles identified, 94 trials met inclusion criteria. Trials most commonly evaluated pharmaceutical interventions (53%), were non-industry funded (78%), and required prospective informed consent (81%). The overall mean enrollment rate was 0.83 (95% confidence interval: 0.57-1.21) participants per month per site. Enrollment in ARDS/ALI and sepsis trials were 0.48 (95% CI 0.32-0.70) and 0.98 (95% CI 0.62-1.56) respectively. The enrollment rate was significantly higher for single-center trials (4.86; 95% CI 2.49-9.51) than multicenter trials (0.52; 95% CI 0.41-0.66). Of the 36 trials that enrolled < 95% of the target sample size, 8 (22%) reported slow enrollment as the reason.

CONCLUSIONS

In this systematic review and meta-analysis, recent ARDS/ALI and sepsis clinical trials had an overall enrollment rate of less than 1 participant per site per month. Novel approaches to improve critical care trial enrollment efficiency are needed to facilitate the translation of best evidence into practice.

Deficits in Identification of Goals and Goal-Concordant Care After Sepsis Hospitalization

In a recent study, identifying and supporting patients' care goals was named the highest priority in hospital medicine. Although sepsis is one of the leading causes of death and postdischarge morbidity among hospitalized patients, little is known about how frequently care goals are assessed prior to discharge and adhered to in the 90 days after sepsis hospitalization. Evaluating a cohort of 679 high-risk sepsis survivors enrolled in a clinical trial, we found that care goals were documented explicitly in a standardized tool in 130 patients; an additional 139 patients were identified using all available clinical documentation, resulting in only 269 (40%) patients with goals that could be ascertained from the electronic health record (EHR). Among those categorized, goals were classified as prioritizing longevity (35%), function (52%), and comfort (12%). Based on expert review of the care provided during the 90 days subsequent to discharge, goal-concordant care was identified in 184 (68%) cases for which goals were specified. Documentation of goals in a standardized EHR tool was associated with increased likelihood of receiving goal-concordant care (odds ratio, 3.6; 95% CI, 2.4-5.5). Hospitalization and peridischarge time points represent important opportunities to address deficits in the documentation of goals and provision of goal-concordant care for sepsis survivors.

What can a learning healthcare system teach us about improving outcomes?

PURPOSE OF REVIEW

This review describes the learning healthcare system paradigm, recent examples, and future directions. Patients, clinicians, and health systems frequently encounter decisions between available treatments, technologies, and healthcare delivery methods with little or no evidence about the comparative effectiveness and safety of the available options. Learning healthcare systems endeavor to recognize such knowledge gaps, integrate comparative effectiveness research - including clinical trials - into clinical care to address the knowledge gaps, and seamlessly implement the results into practice to improve care and patient outcomes.

RECENT FINDINGS

Recent studies comparing the effectiveness of diagnostic tests and treatments, using information technology to identify patients likely to experience an outcome or benefit from an intervention, and evaluating models of healthcare delivery have demonstrated how a learning healthcare system approach can reduce arbitrary variation in care, decrease cost, and improve patient outcomes.

SUMMARY

Learning healthcare systems have the potential to answer questions of importance to patients, clinicians, and health system leaders, improve efficiency of healthcare delivery, and improve patient outcomes. Achieving this goal will require realignment of the culture around clinical care, institutional and federal investment, expanded stakeholder engagement, tailored ethical and regulatory guidance, and methodologic advances in information technology and biostatistics.

Hospital-free Days: A Pragmatic and Patient-centered Outcome for Trials Among Critically and Seriously Ill Patients

Hospital-free days (HFDs), alternatively known as "days alive and outside the hospital," is increasingly used as a primary or secondary outcome in randomized trials among critically and seriously ill patients. This novel outcome measure addresses an existing gap in the availability of patient-centered, reliably obtained outcome measures among patients with acute respiratory failure, advanced lung diseases, lung transplantation, and other serious and critical illnesses. Traditional outcomes such as mortality, organ-failure-free days, and longitudinal patient-reported measures have distinct drawbacks that limit their suitability as endpoints in trials of patients with serious illness, particularly those trials with pragmatic designs. By contrast, HFDs provides a summary measure of important health events and is easily calculated from administrative or electronic health record data, thereby balancing the goals of patient-centeredness and pragmatic measurement. However, before HFDs can be widely adopted as an endpoint in trials of patients with respiratory and critical illnesses, several questions must be addressed regarding the optimal definition, measurement, and analysis of HFDs. In this perspective, we outline important considerations relevant to the use of HFDs as a trial endpoint and suggest directions for further development of the measure.

Characteristics, Outcomes, and Trends of Patients With COVID-19-Related Critical Illness at a Learning Health System in the United States

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic continues to surge in the United States and globally.

OBJECTIVE

To describe the epidemiology of COVID-19-related critical illness, including trends in outcomes and care delivery.

DESIGN

Single-health system, multihospital retrospective cohort study.

SETTING

5 hospitals within the University of Pennsylvania Health System.

PATIENTS

Adults with COVID-19-related critical illness who were admitted to an intensive care unit (ICU) with acute respiratory failure or shock during the initial surge of the pandemic.

MEASUREMENTS

The primary exposure for outcomes and care delivery trend analyses was longitudinal time during the pandemic. The primary outcome was all-cause 28-day in-hospital mortality. Secondary outcomes were all-cause death at any time, receipt of mechanical ventilation (MV), and readmissions.

RESULTS

Among 468 patients with COVID-19-related critical illness, 319 (68.2%) were treated with MV and 121 (25.9%) with vasopressors. Outcomes were notable for an all-cause 28-day in-hospital mortality rate of 29.9%, a median ICU stay of 8 days (interquartile range [IQR], 3 to 17 days), a median hospital stay of 13 days (IQR, 7 to 25 days), and an all-cause 30-day readmission rate (among nonhospice survivors) of 10.8%. Mortality decreased over time, from 43.5% (95% CI, 31.3% to 53.8%) to 19.2% (CI, 11.6% to 26.7%) between the first and last 15-day periods in the core adjusted model, whereas patient acuity and other factors did not change.

LIMITATIONS

Single-health system study; use of, or highly dynamic trends in, other clinical interventions were not evaluated, nor were complications.

CONCLUSION

Among patients with COVID-19-related critical illness admitted to ICUs of a learning health system in the United States, mortality seemed to decrease over time despite stable patient characteristics. Further studies are necessary to confirm this result and to investigate causal mechanisms.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality.

Palliative Care Team Perceptions of Standardized Palliative Care Referral Criteria Implementation in Hospital Settings

Background: Standardized referral criteria can aid in identifying patients who would benefit from palliative care consultation. Little is known, however, on palliative care team members' perceptions of these criteria. Objective: Describe palliative care programs' reasons for referral criteria implementation and their perception of the benefits or disadvantages of its use. Design: Online survey of National Palliative Care Registry™ participants who use standardized referral criteria. Results: Fifty-three programs participated. Late referrals (64.2%) were the most commonly cited reason for referral criteria implementation. The majority (77.4%) felt that referral criteria lead to positive outcomes, including earlier referrals for palliative care-appropriate patients (71.7%). Increases in staff workload and inappropriate referrals were identified as disadvantages of referral criteria use.* Conclusion: Palliative care program members identified both benefits and disadvantages of referral criteria use, but felt they had mostly productive results. *Correction added on March 18, 2021 after first online publication of December 18, 2020: In the Results section of the abstract, the third sentence was changed from "Increases in clinical volume and inappropriate referrals were identified as disadvantages of referral criteria use." to "Increases in staff workload and inappropriate referrals were identified as disadvantages of referral criteria use."

The palliative care needs of lung transplant candidates

BACKGROUND

Little is known about the palliative care needs of patients awaiting lung transplantation. The aim of this study was to describe these needs in patients undergoing evaluation for or awaiting lung transplantation.

METHODS

Cross-sectional survey using an adapted version of the Needs at the End-of-life Screening Tool (NEST-13) at a US-based transplant program.

RESULTS

Among the 111 participants, 83.5% were White, 60.0% were female, and almost three-quarters had either restrictive or obstructive lung disease. The greatest palliative care needs included difficulty being physically active (mean: 7.9/10; SD: 2.6; median: 9.0), physical symptoms (mean: 7.4/10; SD: 2.6; median: 8.0), missing work due to illness (mean: 6.2/10; SD: 4.0; median: 8.0), and concerns that life might end (mean: 5.1/10; SD: 3.6; median: 5.0). Participants reported that religious/spiritual beliefs contribute to their sense of purpose (mean: 4.1/10; SD: 3.9) but had few unmet needs in this area (mean: 0.9/10; median: 0.0). Only 6.4% reported seeing a palliative care specialist, and 48.2% were unsure what a palliative care specialist is.

CONCLUSION

There are substantial palliative care needs among lung transplant candidates, particularly physical symptoms and end-of-life concerns. These findings support integrating palliative care and end-of-life discussions in the management of lung transplant candidates.

"I Don't Have Time to Sit and Talk with Them": Hospitalists' Perspectives on Palliative Care Consultation for Patients with Dementia

BACKGROUND/OBJECTIVES

Specialty palliative care for hospitalized patients with dementia is widely recommended and may improve outcomes, yet rates of consultation remain low. We sought to describe hospitalists' decision-making regarding palliative care consultation for patients with dementia.

DESIGN

Descriptive qualitative study.

SETTING

Seven hospitals within a national nonprofit health system.

PARTICIPANTS

Hospitalist physicians.

MEASUREMENTS

Individual semistructured interviews. We used thematic analysis to explore factors that influence hospitalists' decision to consult palliative care for patients with dementia.

RESULTS

A total of 171 hospitalists were eligible to participate, and 28 (16%) were interviewed; 17 (61%) were male, 16 (57%) were white, and 18 (64%) were in practice less than 10 years. Overall, hospitalists' decisions to consult palliative care for patients with dementia were influenced by multiple factors across four themes: patient, family caregiver, hospitalist, and organization. Consultation was typically only considered for patients with advanced disease, particularly those receiving aggressive care or with family communication needs (navigating conflicts around goals of care and improving disease and prognostic understanding). Hospitalists' limited time and, for some, a lack of confidence in palliative care skills were strong drivers of consultation. Palliative care needs notwithstanding, most hospitalists would not request consultation if they perceived families would be resistant to it or had limited availability or involvement in caregiving. Additional barriers to referral at the organization level included a hospital culture that conflated palliative and end-of-life care and busy palliative care teams at some hospitals.

CONCLUSION

Hospitalists described a complex consultation decision process for involving palliative care specialists in the care of patients with dementia. Systematic identification of hospitalized patients with dementia most likely to benefit from palliative care consultation and strategies to overcome modifiable family and organization barriers are needed. J Am Geriatr Soc 68:2365-2372, 2020.

Family-Centered Care During the COVID-19 Era

Family support is more, not less, important during crisis. However, during the COVID-19 pandemic, maintaining public safety necessitates restricting the physical presence of families for hospitalized patients. In response, health systems must rapidly adapt family-centric procedures and tools to circumvent restrictions on physical presence. Strategies for maintaining family integrity must acknowledge clinicians' limited time and attention to devote to learning new skills. Internet-based solutions can facilitate the routine, predictable, and structured communication, which is central to family-centered care. But the reliance on technology may compromise patient privacy and exacerbate racial, socioeconomic, and geographic disparities for populations that lack access to reliable internet access, devices, or technological literacy. We provide a toolbox of strategies for supporting family-centered inpatient care during physical distancing responsive to the current clinical climate. Innovations in the implementation of family involvement during hospitalizations may lead to long-term progress in the delivery of family-centered care.

Preferences for Predictive Model Characteristics among People Living with Chronic Lung Disease: A Discrete Choice Experiment

Background. Patients may find clinical prediction models more useful if those models accounted for preferences for false-positive and false-negative predictive errors and for other model characteristics. Methods. We conducted a discrete choice experiment to compare preferences for characteristics of a hypothetical mortality prediction model among community-dwelling patients with chronic lung disease recruited from 3 clinics in Philadelphia. This design was chosen to allow us to quantify "exchange rates" between different characteristics of a prediction model. We provided previously validated educational modules to explain model attributes of sensitivity, specificity, confidence intervals (CI), and time horizons. Patients reported their interest in using prediction models themselves or having their physicians use them. Patients then chose between 2 hypothetical prediction models each containing varying levels of the 4 attributes across 12 tasks. Results. We completed interviews with 200 patients, among whom 95% correctly chose a strictly dominant model in an internal validity check. Patients' interest in predictive information was high for use by themselves (n = 169, 85%) and by their physicians (n = 184, 92%). Interest in maximizing sensitivity and specificity were similar (0.88 percentage points of specificity equivalent to 1 point of sensitivity, 95% CI 0.72 to 1.05). Patients were willing to accept a reduction of 6.10 months (95% CI 3.66 to 8.54) in the predictive time horizon for a 1% increase in specificity. Discussion. Patients with chronic lung disease can articulate their preferences for the characteristics of hypothetical mortality prediction models and are highly interested in using such models as part of their care. Just as clinical care should become more patient centered, so should the characteristics of predictive models used to guide that care.

Risk Factors for Long-term Mortality and Patterns of End-of-Life Care Among Medicare Sepsis Survivors Discharged to Home Health Care

IMPORTANCE

Despite a growing recognition of the increased mortality risk among sepsis survivors, little is known about the patterns of end-of-life care among this population.

OBJECTIVE

To describe patterns of end-of-life care among a national sample of sepsis survivors and identify factors associated with long-term mortality risk and hospice use.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study assessed sepsis survivors who were Medicare fee-for-service beneficiaries discharged to home health care using national Medicare administrative, claims, and home health assessment data from 2013 to 2014. The initial and final primary analyses were conducted in July 2017 and from July to August 2019, respectively.

EXPOSURES

Sepsis hospital discharge and 1 or more home health assessments within 1 week.

MAIN OUTCOMES AND MEASURES

Outcomes were 1-year mortality among all sepsis survivors and hospitalization in the last 30 days of life, death in an acute care hospital, and hospice use among decedents. Multivariate logistic regression was used to identify factors associated with 1-year mortality and hospice use.

RESULTS

Among 87 581 sepsis survivors who were Medicare fee-for-service beneficiaries discharged to home health care, 49 323 (56.3%) were aged 75 years or older, 69 499 (79.4%) were non-Hispanic white, and 48 472 (55.3%) were female. Among the total survivors, 24 423 (27.9%) people died within 1 year of discharge, with a median (interquartile range) survival time of 119 (51-220) days. Among these decedents, 16 684 (68.2%) were hospitalized in the last 30 days of life, 6560 (26.8%) died in an acute care hospital, and 12 573 (51.4%) were enrolled in hospice, with 5729 (45.6%) using hospice for 7 or fewer days. Several factors were associated with 1-year mortality, including a cancer diagnosis (odds ratio [OR], 3.66; 95% CI, 3.50-3.83; P < .001), multiple dependencies of activities of daily living or instrumental activities of daily living (OR, 2.80; 95% CI, 2.57-3.05; P < .001), and an overall poor health status (OR, 2.21; 95% CI, 2.01-2.44; P < .001) documented on home health assessment. Among the decedents, cancer was associated with hospice use (OR, 2.25; 95% CI, 2.11-2.41; P < .001), patients aged 85 years or older (OR, 1.49; 95% CI, 1.37-1.61; P < .001), and living in an assisted living setting (OR, 1.93; 95% CI, 1.69-2.19; P < .001).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that death within 1 year after sepsis discharge may be common among Medicare beneficiaries discharged to home health care. Although 1 in 2 decedents used hospice, aggressive care near the end of life and late hospice referral were common. Readily identifiable risk factors suggest opportunities to target efforts to improve palliative and end-of-life care among high-risk sepsis survivors.

A pilot randomized trial of five financial incentive strategies to increase study enrollment and retention rates

Background

Enrollment and retention difficulties remain major barriers to conducting clinical trials. Financial incentives may promote clinical trial enrollment, however delivery methods to maximize enrollment, maximize retention, and minimize cost remains uncertain.

Methods

We conducted a single-blind, web-based randomized controlled trial of five financial incentive strategies on enrollment and retention rates in a longitudinal study of advance directives among community-dwelling older adults. Participants were eligible to receive a fixed total financial incentive, but the disbursement amounts at each study timepoint (baseline, 2-weeks, 4-weeks, and 6-weeks) differed between study arms. At each timepoint, participants completed a different advance directive. We conducted an intention-to-treat analysis for the primary and secondary outcomes of enrollment and retention.

Results

1803 adults were randomized to one of five incentive strategies: constant n = 361; increasing n = 357; U-shaped n = 361; surprise n = 360; self-select n = 364. Overall, 989 (54.9%) participants elected to enroll in the advance directive study. There were no differences in enrollment rates between the control (constant 53.5%) and any of the four intervention study arms (increasing 54.3%, p = 0.81; U-shaped 57.3%, p = 0.30; surprise 56.9%, p = 0.35; and self-select 52.2%, p = 0.73). There were no differences in retention rates between the control (constant 2.1%) and any of the four intervention study arms (increasing 5.2%, p = 0.09; U-shaped 3.9%, p = 0.23; surprise 2.4%, p = 0.54; self-select 2.1%, p = 0.63).

Conclusions

Financial incentive programs for trial enrollment informed by behavioral economic insights were no more effective than a constant-payment approach in this web-based pilot study.

Construct validity of six sentiment analysis methods in the text of encounter notes of patients with critical illness

Sentiment analysis may offer insights into patient outcomes through the subjective expressions made by clinicians in the text of encounter notes. We analyzed the predictive, concurrent, convergent, and content validity of six sentiment methods in a sample of 793,725 multidisciplinary clinical notes among 41,283 hospitalizations associated with an intensive care unit stay. None of these approaches improved early prediction of in-hospital mortality using logistic regression models, but did improve both discrimination and calibration when using random forests. Additionally, positive sentiment measured by the CoreNLP (OR 0.04, 95% CI 0.002-0.55), Pattern (OR 0.09, 95% CI 0.04-0.17), sentimentr (OR 0.37, 95% CI 0.25-0.63), and Opinion (OR 0.25, 95% CI 0.07-0.89) methods were inversely associated with death on the concurrent day after adjustment for demographic characteristics and illness severity. Median daily lexical coverage ranged from 5.4% to 20.1%. While sentiment between all methods was positively correlated, their agreement was weak. Sentiment analysis holds promise for clinical applications but will require a novel domain-specific method applicable to clinical text.

Numeracy and Understanding of Quantitative Aspects of Predictive Models: A Pilot Study

BACKGROUND

The assessment of user preferences for performance characteristics of patient-oriented clinical prediction models is lacking. It is unknown if complex statistical aspects of prediction models are readily understandable by a general audience.

OBJECTIVE

A pilot study was conducted among nonclinical audiences to determine the feasibility of interpreting statistical concepts that describe the performance of prediction models.

METHODS

We conducted a cross-sectional electronic survey using the Amazon Mechanical Turk platform. The survey instrument included educational modules about predictive models, sensitivity, specificity, and confidence intervals (CIs). Follow-up questions tested participants' abilities to interpret these characteristics with both verbatim and gist knowledge. Objective and subjective numeracy were assessed using previously validated instruments. We also tested understanding of these concepts when embedded in a sample discrete choice experiment task to establish feasibility for future elicitation of preferences using a discrete choice experiment design. Multivariable linear regression was used to identify factors associated with correct interpretation of statistical concepts.

RESULTS

Among 534 respondents who answered all nine questions, the mean correct responses was 95.9% (95% CI, 93.8-97.4) for sensitivity, 93.1% (95% CI, 90.5-95.0) for specificity, and 86.6% (95% CI, 83.3-89.3) for CIs. Verbatim interpretation was high for all concepts, but significantly higher than gist only for CIs (p < 0.001). Scores on each discrete choice experiment tasks were slightly lower in each category. Both objective and subjective numeracy were positively associated with an increased proportion of correct responses (p < 0.001).

CONCLUSION

These results suggest that a nonclinical audience can interpret quantitative performance measures of predictive models with very high accuracy. Future development of patient-facing clinical prediction models can feasibly incorporate patient preferences for model features into their development.

Willingness to participate in pragmatic dialysis trials: the importance of physician decisional autonomy and consent approach

BACKGROUND

Pragmatic clinical trials embedded in routine delivery of clinical care can lead to improvements in quality of care, but often have design features that raise ethical concerns.

METHODS

We performed a discrete choice experiment and used conjoint analysis to assess how specific attributes of pragmatic dialysis trials influenced patients' and physicians' willingness to have their dialysis facility participate in a hypothetical trial of hypertension management. Electronic survey data were collected from 200 patients enrolled from 11 outpatient hemodialysis units and from 203 nephrologists. The three attributes studied were physicians' treatment autonomy, participants' research burden, and the approach to consent. The influence of each attribute was quantified using mixed-effects logistic regression.

RESULTS

Similar proportions of patients were willing to have their facilities participate in a trial with high vs. low physician autonomy (77% vs. 79%; p = 0.13) and research burden (76% vs. 80%; p = 0.06). Opt-in, opt-out, and notification-only consent approaches were acceptable to most patients (84%, 82%, and 81%, respectively), but compared to each of these consent approaches, fewer patients (66%) were willing to have their facility participate in a trial that used no notification (p < 0.001 for each 2-way comparison). Among the physicians, similar proportions were willing to participate in trials with high and low physician autonomy (61% and 61%, respectively, p = 0.96) or with low and high burden (60 and 61%, respectively, p = 0.79). However, as for the patients, the consent approach influenced trial acceptability with 77%, 69%, and 62% willing to participate using opt-in, opt-out, and notification-only, respectively, compared to no notification (36%) (p < 0.001 for each 2-way comparison).

CONCLUSIONS

Curtailing physician's treatment autonomy and increasing the burden associated with participation did not influence patients' or physicians' willingness to participate in the hypothetical research, suggesting that pragmatic dialysis trials are generally acceptable to patients and physicians. Both patients and physicians preferred consent approaches that include at least some level of patient notification, but the majority of patients were still willing to participate in trials that did not notify patients of the research.

A Randomized Trial of Expanding Choice Sets to Motivate Advance Directive Completion

BACKGROUND

Evidence suggests that advance directives may improve end-of-life care among seriously ill patients, but improving completion rates remains a challenge.

OBJECTIVE

This study tested the influence of increasing the number of options for completing an advance directive among seriously ill patients.

METHODOLOGY

Outpatients ( N = 316) receiving hemodialysis across 15 dialysis centers in the Philadelphia region between July 2014 and July 2015 were randomized to receive either the option to complete a brief advance directive form or expanded options including a brief, expanded, or comprehensive form. Patients in both groups could decline to complete an advance directive or take their selected version home. The primary outcome was a returned, completed advance directive. Secondary outcomes included whether patients wanted to complete an advance directive, decision satisfaction, quality of life at 3 months, and patient factors associated with advance directive completion.

RESULTS

Although offering more advance directive options was not significantly associated with increased rates of completion (13.1% in the standard group v. 12.2% in the expanded group, P = 0.80), it did significantly increase the proportion of patients who wanted to complete an advance directive and took one home (71.9% in standard v. 85.3% in expanded, P = 0.004). There was no difference in satisfaction ( P = 0.65) or change in quality of life between groups ( P = 0.63). A higher baseline quality of life was independently associated with advance directive completion ( P = 0.006).

CONCLUSIONS AND RELEVANCE

These results suggest that although an expanded choice set may initially nudge patients toward completing advance directives without restricting choice, increasing actual completion requires additional interventions that overcome downstream barriers.