Trajectories of Palliative Care Needs in the ICU and Long-Term Psychological Distress Symptoms.

OBJECTIVES: While palliative care needs are assumed to improve during ICU care, few empiric data exist on need trajectories or their impact on long-term outcomes. We aimed to describe trajectories of palliative care needs during ICU care and to determine if changes in needs over 1 week was associated with similar changes in psychological distress symptoms at 3 months. DESIGN: Prospective cohort study. SETTING: Six adult medical and surgical ICUs. PARTICIPANTS: Patients receiving mechanical ventilation for greater than or equal to 2 days and their family members. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the 13-item Needs at the End-of-Life Screening Tool (NEST; total score range 0-130) completed by family members at baseline, 3, and 7 days. The Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Post-Traumatic Stress Scale (PTSS) were completed at baseline and 3 months. General linear models were used to estimate differences in distress symptoms by change in need (NEST improvement ≥ 10 points or not). One-hundred fifty-nine family members participated (median age, 54.0 yr [interquartile range (IQR), 44.0-63.0 yr], 125 [78.6%] female, 54 [34.0%] African American). At 7 days, 53 (33%) a serious level of overall need and 35 (22%) ranked greater than or equal to 1 individual need at the highest severity level. NEST scores improved greater than or equal to 10 points in only 47 (30%). Median NEST scores were 22 (IQR, 12-40) at baseline and 19 (IQR, 9-37) at 7 days (change, -2.0; IQR, -11.0 to 5.0; p = 0.12). There were no differences in PHQ-9, GAD-7, or PTSS change scores by change in NEST score (all p > 0.15). CONCLUSIONS: Serious palliative care needs were common and persistent among families during ICU care. Improvement in needs was not associated with less psychological distress at 3 months. Serious needs may be commonly underrecognized in current practice.

Patient-reported distress as an early warning sign of unmet palliative care needs and increased healthcare utilization in patients with advanced cancer.

INTRODUCTION: Cancer patients' sources of distress are often unaddressed, and patient-reported distress data could be utilized to identify those with unmet and impending care needs. We explored the association between moderate/severe distress and healthcare utilization in a large sample of non-small cell lung cancer (NSCLC) and non-colorectal gastrointestinal cancer patients. METHODS AND MATERIALS: Adult patients treated between July 2013 and March 2019. Data from the NCCN Distress Thermometer (DT) and the accompanying "Problem List" were extracted from the EHR. A DT score of ≥ 4 indicates "actionable distress." Statistical analysis was performed using descriptive analysis for patient characteristics, clinical outcomes, and sources of distress. Generalized linear mixed models were fit to determine the relationship between distress and healthcare utilization (hospitalization, emergency department (ED) visit, or both). RESULTS: The ten most frequently reported problems were from the Physical and Emotional domains of the Problem List. Distress was mostly related to physical symptoms (pain, fatigue) and emotional issues (worry, fears, sadness, nervousness). Patients with actionable distress generally reported more problems across all their visits. Actionable distress was associated with higher odds of the composite outcome measure of hospitalization or visiting the ED, within both the next 3 months (OR = 1.37; 95% CI = 1.19, 1.58; p < 0.001) and 6 months (OR = 1.19; 95% CI = 1.03, 1.37; p = 0.019). CONCLUSION: Patients with significant distress had marked utilization of ED and inpatient services. DT scores are a source of untapped data in the EHR that can highlight patients in need of intervention, including palliative care and cancer support services.

Perceptions of hospitalized patients and their surrogate decision makers on dialysis initiation: a pilot study.

BACKGROUND: Dialysis is often initiated in the hospital during episodes of acute kidney injury and critical illness. Little is known about how patients or their surrogate decision makers feel about dialysis initiation in the inpatient setting. METHODS: We conducted a prospective cohort study at a large academic center in the United States. All patients who initiated dialysis during a 30-day period in 2016 were approached for enrollment. Study participants were defined as individuals who provided consent for dialysis initiation - either the patient or a surrogate decision-maker. Decisional satisfaction and the degree of shared decision-making were assessed using the decisional attitude scale and the control preferences scale, respectively. These scales were incorporated into a study questionnaire along with an exploratory structured interview. RESULTS: A total of 31 potential participants were eligible and 21 agreed to participate in the study. Continuous renal replacement therapy was used in 14 out of 21 cases (67%) and there was 33% in-hospital mortality in the study cohort. A majority (62%) of patients were unable to participate in the consent process for dialysis initiation and had to rely on a surrogate decision-maker. The mean score for the decisional attitude scale was 4.1 (95% CI 3.8-4.3) with a score of 5 corresponding to high decisional satisfaction. Most of the decisions were classified as shared and incorporated input from clinicians as well as patients or surrogates. Although 90% of participants agreed that they had a choice in making the decision, 81% were unable to mention any alternatives to dialysis initiation. CONCLUSIONS: Dialysis initiation was associated with high decisional satisfaction and most participants felt that the decision incorporated input from patients and providers. However, inpatient dialysis initiation was commonly associated with loss of decisional capacity and reliance on a surrogate decision-maker. This finding is likely driven by critical illness. Survivors of critical illness who remain dialysis dependent may need to revisit conversations about the rationale, risks, and benefits of dialysis.

Breast cancer survivors willingness to participate in an acupuncture clinical trial: a qualitative study.

PURPOSE: Acupuncture is a complementary and alternative medicine (CAM) modality that shows promise as a component of supportive breast cancer care. Lack of robust recruitment for clinical trial entry has limited the evidence base for acupuncture as a treatment modality among breast cancer survivors. The objective of this study is to identify key decision-making factors among breast cancer survivors considering entry into an acupuncture clinical trial for treatment of symptoms. METHODS: Semistructured interviews were conducted among African-American (n=12) and Caucasian (n=13) breast cancer survivors. Verbatim transcripts were made and analyzed by two or more independent coders using NVivo software. Major recurring themes were identified and a theoretical framework developed. RESULTS: Six themes emerged reflecting key attributes of the decision to enter a clinical trial: (1) symptom appraisal, (2) practical barriers (e.g., distance and travel), (3) beliefs about the interventions (e.g., fear of needles and dislike of medications), (4) comfort with elements of clinical trial design (e.g., randomization, the nature of the control intervention, and blinding), (5) trust, and (6) altruism. African-American and Caucasian women weighed similar attributes but differed in the information sources sought regarding clinical trial entry and in concerns regarding the use of a placebo in a clinical trial. CONCLUSIONS: Our findings contribute to the development of a theoretical model of decision making for breast cancer survivors considering participation in a CAM clinical trial. Insights regarding the decision making process can inform interventions to support informed decision making and robust recruitment to CAM trials among cancer survivors.

Randomized Comparison of Electronic Health Record Alert Types in Eliciting Responses about Prognosis in Gynecologic Oncology Patients.

OBJECTIVES: To compare the ability of different electronic health record alert types to elicit responses from users caring for cancer patients benefiting from goals of care (GOC) conversations. METHODS: A validated question asking if the user would be surprised by the patient's 6-month mortality was built as an Epic BestPractice Advisory (BPA) alert in three versions-(1) Required on Open chart (pop-up BPA), (2) Required on Close chart (navigator BPA), and (3) Optional Persistent (Storyboard BPA)-randomized using patient medical record number. Meaningful responses were defined as "Yes" or "No," rather than deferral. Data were extracted over 6 months. RESULTS: Alerts appeared for 685 patients during 1,786 outpatient encounters. Measuring encounters where a meaningful response was elicited, rates were highest for Required on Open (94.8% of encounters), compared with Required on Close (90.1%) and Optional Persistent (19.7%) (p < 0.001). Measuring individual alerts to which responses were given, they were most likely meaningful with Optional Persistent (98.3% of responses) and least likely with Required on Open (68.0%) (p < 0.001). Responses of "No," suggesting poor prognosis and prompting GOC, were more likely with Optional Persistent (13.6%) and Required on Open (10.3%) than with Required on Close (7.0%) (p = 0.028). CONCLUSION: Required alerts had response rates almost five times higher than optional alerts. Timing of alerts affects rates of meaningful responses and possibly the response itself. The alert with the most meaningful responses was also associated with the most interruptions and deferral responses. Considering tradeoffs in these metrics is important in designing clinical decision support to maximize success.

Factors Associated With Hospital Admission in the Last Month: A Retrospective Single Center Analysis.

CONTEXT: Driven by concerns about care quality, patient experience, and national metrics, health systems are increasingly focusing on identifying risk factors for patients who are hospitalized in the last month of life. OBJECTIVE: To evaluate patient factors associated with hospital admission in the last month (30 days). METHODS: We analyzed a retrospective cohort of 8488 patients with a primary care visit in a tertiary health system in the last year of life using a linked electronic health record and decedent dataset. We examined healthcare utilization (primary care, emergency, hospital, intensive care unit encounters) and end-of-life related outcomes (palliative care consultation, do-not-resuscitate orders, advance care planning documentation, hospice at hospital discharge, death in health system). Multivariable logistic regressions identified patient factors associated with admission in the last month. RESULTS: About 2202 (25.9%) patients had a hospital admission in the last month. Among the 1282 (15.1%) who died in a health system facility, most (1103/1282, 86.0%) were admitted to the hospital in the last month. Among patients with a hospital admission and discharged in the last month, 60.9% (686/1126) were discharged on hospice. Compared to those without these diseases, metastatic cancer, liver disease, or heart failure had the highest odds of admission in the last month (adjusted OR 2.36 95%CI 2.05-2.72; 2.28, 95%CI 1.98-2.62; and 2.17 95%CI 1.93-2.45 respectively). CONCLUSIONS: As patients with heart or liver disease or metastatic cancer had the highest odds of admission in the last month, collaborative interventions between primary, palliative, and specialty care may improve quality of care at the end of life.

Mobile Application-Based Communication Facilitation Platform for Family Members of Critically Ill Patients: A Randomized Clinical Trial.

Importance: Unmet and racially disparate palliative care needs are common in intensive care unit (ICU) settings. Objective: To test the effect of a primary palliative care intervention vs usual care control both overall and by family member race. Design, Setting, and Participants: This cluster randomized clinical trial was conducted at 6 adult medical and surgical ICUs in 2 academic and community hospitals in North Carolina between April 2019 and May 2022 with physician-level randomization and sequential clusters of 2 Black patient-family member dyads and 2 White patient-family member dyads enrolled under each physician. Eligible participants included consecutive patients receiving mechanical ventilation, their family members, and their attending ICU physicians. Data analysis was conducted from June 2022 to May 2023. Intervention: A mobile application (ICUconnect) that displayed family-reported needs over time and provided ICU attending physicians with automated timeline-driven communication advice on how to address individual needs. Main Outcomes and Measures: The primary outcome was change in the family-reported Needs at the End-of-Life Screening Tool (NEST; range 0-130, with higher scores reflecting greater need) score between study days 1 and 3. Secondary outcomes included family-reported quality of communication and symptoms of depression, anxiety, and posttraumatic stress disorder at 3 months. Results: A total of 111 (51% of those approached) family members (mean [SD] age, 51 [15] years; 96 women [86%]; 15 men [14%]; 47 Black family members [42%]; 64 White family members [58%]) and 111 patients (mean [SD] age, 55 [16] years; 66 male patients [59%]; 45 Black patients [41%]; 65 White patients [59%]; 1 American Indian or Alaska Native patient [1%]) were enrolled under 37 physicians randomized to intervention (19 physicians and 55 patient-family member dyads) or control (18 physicians and 56 patient-family member dyads). Compared with control, there was greater improvement in NEST scores among intervention recipients between baseline and both day 3 (estimated mean difference, -6.6 points; 95% CI, -11.9 to -1.3 points; P = .01) and day 7 (estimated mean difference, -5.4 points; 95% CI, -10.7 to 0.0 points; P = .05). There were no treatment group differences at 3 months in psychological distress symptoms. White family members experienced a greater reduction in NEST scores compared with Black family members at day 3 (estimated mean difference, -12.5 points; 95% CI, -18.9 to -6.1 points; P < .001 vs estimated mean difference, -0.3 points; 95% CI, -9.3 to 8.8 points; P = .96) and day 7 (estimated mean difference, -9.5 points; 95% CI, -16.1 to -3.0 points; P = .005 vs estimated mean difference, -1.4 points; 95% CI, -10.7 to 7.8; P = .76). Conclusions and Relevance: In this study of ICU patients and family members, a primary palliative care intervention using a mobile application reduced unmet palliative care needs compared with usual care without an effect on psychological distress symptoms at 3 months; there was a greater intervention effect among White family members compared with Black family members. These findings suggest that a mobile application-based intervention is a promising primary palliative care intervention for ICU clinicians that directly addresses the limited supply of palliative care specialists. Trial Registration: ClinicalTrials.gov Identifier: NCT03506438.

Using Design Thinking to Promote Goals of Care Conversations With Seriously Ill Patients.

BACKGROUND: Goals of care (GOC) conversations can improve serious illness outcomes such as pain and symptom management and patient satisfaction. PROBLEM: However, we recognized that very few Duke Health patients who died had a GOC conversation documented in the designated electronic health record (EHR) tab. Therefore, in 2020, we set a target that all Duke Health patients who died should have had a GOC conversation documented in a designated EHR tab in the last 6 months of life. INTERVENTION: In developing a strategy to promote GOC conversations, we used two interwoven approaches. The first was RE-AIM, a model for designing, reporting and evaluating health behavior research. The second was less of a model than a way of approaching problems, known as "design thinking." OUTCOMES: We employed both of these approaches in a system-wide effort that achieved a 50% prevalence of GOC conversations in the last 6 months of life. KEY MESSAGE: In combination, simple interventions can have a significant impact on behavior change in an academic health system. LESSONS LEARNED: We found that design thinking techniques offered a useful bridge between RE-AIM strategy and clinical.

Machine learning functional impairment classification with electronic health record data.

BACKGROUND: Poor functional status is a key marker of morbidity, yet is not routinely captured in clinical encounters. We developed and evaluated the accuracy of a machine learning algorithm that leveraged electronic health record (EHR) data to provide a scalable process for identification of functional impairment. METHODS: We identified a cohort of patients with an electronically captured screening measure of functional status (Older Americans Resources and Services ADL/IADL) between 2018 and 2020 (N = 6484). Patients were classified using unsupervised learning K means and t-distributed Stochastic Neighbor Embedding into normal function (NF), mild to moderate functional impairment (MFI), and severe functional impairment (SFI) states. Using 11 EHR clinical variable domains (832 variable input features), we trained an Extreme Gradient Boosting supervised machine learning algorithm to distinguish functional status states, and measured prediction accuracies. Data were randomly split into training (80%) and test (20%) sets. The SHapley Additive Explanations (SHAP) feature importance analysis was used to list the EHR features in rank order of their contribution to the outcome. RESULTS: Median age was 75.3 years, 62% female, 60% White. Patients were classified as 53% NF (n = 3453), 30% MFI (n = 1947), and 17% SFI (n = 1084). Summary of model performance for identifying functional status state (NF, MFI, SFI) was AUROC (area under the receiving operating characteristic curve) 0.92, 0.89, and 0.87, respectively. Age, falls, hospitalization, home health use, labs (e.g., albumin), comorbidities (e.g., dementia, heart failure, chronic kidney disease, chronic pain), and social determinants of health (e.g., alcohol use) were highly ranked features in predicting functional status states. CONCLUSION: A machine learning algorithm run on EHR clinical data has potential utility for differentiating functional status in the clinical setting. Through further validation and refinement, such algorithms can complement traditional screening methods and result in a population-based strategy for identifying patients with poor functional status who need additional health resources.

The Use of Templates for Documenting Advance Care Planning Conversations: A Descriptive Analysis.

CONTEXT: While professional societies and expert panels have recommended quality indicators related to advance care planning (ACP) documentation, including using structured documentation templates, it is unclear how clinicians document these conversations. OBJECTIVE: To explore how clinicians document ACP, specifically, which components of these conversations are documented. METHODS: A codebook was developed based on existing frameworks for ACP conversations and documentation. ACP documentation from a hospital medicine quality improvement project conducted from November 2019 to April 2021 were included and assessed. Documentation was examined for the presence or absence of each component within the coding schema. Clinician documented ACP using three different note types: template (only template prompts were used), template plus (authors added additional text to the template), and free text only. ACP note components were analyzed by note type and author department. RESULTS: A total of 182 ACP notes were identified and reviewed. The most common note type was template plus (58%), followed by free text (28%) and template (14%). The most frequent components across all note types were: important relationships to patient (92%), and discussion of life-sustaining treatment preferences (87%). There was considerable heterogeneity in the components across note types. The presence of components focused on treatment decisions and legal paperwork differed significantly between note types (P < 0.05). Components on preference for medical information, emotional state, or spiritual support were rarely included across all note types. CONCLUSION: This study provides a preliminary exploration of ACP documentation and found that templates may influence what information is documented after an ACP conversation.

Is public communication about end-of-life care helping to inform all? Cancer news coverage in African American versus mainstream media.

BACKGROUND: Because cancers are a leading cause of death, these diseases receive a great deal of news attention. However, because news media frequently target specific racial or ethnic audiences, some populations may receive different information, and it is unknown whether reporting equally informs all audiences about the options for care at the end of life. This study of news reporting compared "mainstream" (general market) media with African American media, which serves the largest minority group. The specific goal of this study was to determine whether these news media communicate differently about cure-directed cancer treatment and end-of-life alternatives. METHODS: This content analysis included 660 cancer news stories from online and print media that targeted either African American or mainstream audiences. The main outcome measures included whether reporting discussed adverse events of cancer treatment, cancer treatment failure, cancer death/dying, and end-of-life palliative or hospice care. RESULTS: Unadjusted and adjusted analyses indicated that the news stories in the African American media are less likely than those in mainstream media to discuss each of the topics studied. Comparing the proportions of news stories in mainstream versus African American media, 31.6% versus 13.6% discussed adverse events (odds ratio [OR], 2.92; 95% confidence interval [CI], 1.51-5.66; P = .001); 14.1% versus 4.2% mentioned treatment failure (OR, 3.79; 95% CI, 1.45-9.88; P = .006); and 11.9% versus 3.8% focused on death/dying (OR, 3.42; 95% CI, 1.39-8.38; P = .007). Finally, although very few news stories discussed end-of-life hospice or palliative care, all were found in mainstream media (7/396 vs 0/264). CONCLUSION: The African American news media sampled are less likely than mainstream news media to portray negative cancer outcomes and end-of-life care. Given media's segmented audiences, these findings raise concerns that not all audiences are being informed equally well. Because media content is modifiable, there may be opportunities to improve public cancer communication.

Assessment of Clinical Palliative Care Trigger Status vs Actual Needs Among Critically Ill Patients and Their Family Members.

Importance: Palliative care consultations in intensive care units (ICUs) are increasingly prompted by clinical characteristics associated with mortality or resource utilization. However, it is not known whether these triggers reflect actual palliative care needs. Objective: To compare unmet needs by clinical palliative care trigger status (present vs absent). Design, Setting, and Participants: This prospective cohort study was conducted in 6 adult medical and surgical ICUs in academic and community hospitals in North Carolina between January 2019 and September 2020. Participants were consecutive patients receiving mechanical ventilation and their family members. Exposure: Presence of any of 9 common clinical palliative care triggers. Main Outcomes and Measures: The primary outcome was the Needs at the End-of-Life Screening Tool (NEST) score (range, 0-130, with higher scores reflecting greater need), which was completed after 3 days of ICU care. Trigger status performance in identifying serious need (NEST score ≥30) was assessed using sensitivity, specificity, positive and negative likelihood ratios, and C statistics. Results: Surveys were completed by 257 of 360 family members of patients (71.4% of the potentially eligible patient-family member dyads approached) with a median age of 54.0 years (IQR, 44-62 years); 197 family members (76.7%) were female, and 83 (32.3%) were Black. The median age of patients was 58.0 years (IQR, 46-68 years); 126 patients (49.0%) were female, and 88 (33.5%) were Black. There was no difference in median NEST score between participants with a trigger present (45%) and those with a trigger absent (55%) (21.0; IQR, 12.0-37.0 vs 22.5; IQR, 12.0-39.0; P = .52). Trigger presence was associated with poor sensitivity (45%; 95% CI, 34%-55%), specificity (55%; 95% CI, 48%-63%), positive likelihood ratio (1.0; 95% CI, 0.7-1.3), negative likelihood ratio (1.0; 95% CI, 0.8-1.2), and C statistic (0.50; 95% CI, 0.44-0.57). Conclusions and Relevance: In this cohort study, clinical palliative care trigger status was not associated with palliative care needs and no better than chance at identifying the most serious needs, which raises questions about an increasingly common clinical practice. Focusing care delivery on directly measured needs may represent a more person-centered alternative.

Palliative care phenotypes among critically ill patients and family members: intensive care unit prospective cohort study.

OBJECTIVE: Because the heterogeneity of patients in intensive care units (ICUs) and family members represents a challenge to palliative care delivery, we aimed to determine if distinct phenotypes of palliative care needs exist. METHODS: Prospective cohort study conducted among family members of adult patients undergoing mechanical ventilation in six medical and surgical ICUs. The primary outcome was palliative care need measured by the Needs at the End-of-Life Screening Tool (NEST, range from 0 (no need) to 130 (highest need)) completed 3 days after ICU admission. We also assessed quality of communication, clinician-family relationship and patient centredness of care. Latent class analysis of the NEST's 13 items was used to identify groups with similar patterns of serious palliative care needs. RESULTS: Among 257 family members, latent class analysis yielded a four-class model including complex communication needs (n=26, 10%; median NEST score 68.0), family spiritual and cultural needs (n=21, 8%; 40.0) and patient and family stress needs (n=43, 31%; 31.0), as well as a fourth group with fewer serious needs (n=167, 65%; 14.0). Interclass differences existed in quality of communication (median range 4.0-10.0, p<0.001), favourable clinician-family relationship (range 34.6%-98.2%, p<0.001) and both the patient centredness of care Eliciting Concerns (median range 4.0-5.0, p<0.001) and Decision-Making (median range 2.3-4.5, p<0.001) scales. CONCLUSIONS: Four novel phenotypes of palliative care need were identified among ICU family members with distinct differences in the severity of needs and perceived quality of the clinician-family interaction. Knowledge of need class may help to inform the development of more person-centred models of ICU-based palliative care.

Facilitating hospice discussions: a six-step roadmap.

Hospice programs provide comprehensive, compassionate care to dying patients and their families. However, many patients do not enroll in hospice, and those who do generally receive hospice care only in the last weeks of life. Although patients and families rely on their physicians to discuss hospice, there is often inadequate communication between patients and physicians about end-of-life issues. We describe a Six-Step Roadmap for navigating discussions about hospice adapted from the SPIKES protocol for delivering bad news: setting up the discussion, assessing the patient's perception, inviting a patient to discuss individual goals and needs, sharing knowledge, empathizing with the patient's emotions, and summarizing and strategizing the next steps.

Combining Multiple Decedent Data Sources for a Population-Based Picture of End-of-Life Healthcare Utilization.

CONTEXT: Although health systems need to track utilization and mortality, it can be difficult to obtain reliable information on patients who die outside of the health system. This leads to missing data and introduces the potential for bias. OBJECTIVES: To evaluate the linkage of patient death data sources with a tertiary health system electronic health record (EHR) to increase the accuracy of health system end-of-life healthcare utilization data in the last month and six months of life. METHODS: The federal Death Master File (DMF) and North Carolina Department of Health and Human Services (NC DHHS) decedent files from 2017 and 2018 were linked to a health system EHR. Descriptive statistics and chi-square tests were utilized to define impact of additional data sources with demographic data and end-of-life utilization. RESULTS: A total of 65,935 patient deaths were identified through our multi-step data integration process. Approximately a quarter of patients (28.3%) had at least one inpatient or outpatient health system encounter in the last six months of life. Of these, patient deaths identified only in the NC DHHS file were less likely (OR 0.45 [95%CI 0.39-0.52]) to be hospitalized in the last month of life. CONCLUSION: We describe a method to supplement EHR data with decedent information across data sources. While additional decedent data improves the accuracy of death data in the health system, patient healthcare utilization is biased towards those who use the health system at the end of life.