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.

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.

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.

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.

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.

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.

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.

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.

Palliative Care in Advanced Dementia: Comparison of Strategies in Three Countries.

Palliative care including hospice care is appropriate for advanced dementia, but policy initiatives and implementation have lagged, while treatment may vary. We compare care for people with advanced dementia in the United States (US), The Netherlands, and Israel. We conducted a narrative literature review and expert physician consultation around a case scenario focusing on three domains in the care of people with advanced dementia: (1) place of residence, (2) access to palliative care, and (3) treatment. We found that most people with advanced dementia live in nursing homes in the US and The Netherlands, and in the community in Israel. Access to specialist palliative and hospice care is improving in the US but is limited in The Netherlands and Israel. The two data sources consistently showed that treatment varies considerably between countries with, for example, artificial nutrition and hydration differing by state in the US, strongly discouraged in The Netherlands, and widely used in Israel. We conclude that care in each country has positive elements: hospice availability in the US, the general palliative approach in The Netherlands, and home care in Israel. National Dementia Plans should include policy regarding palliative care, and public and professional awareness must be increased.

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.

Operationalizing needs-focused palliative care for older adults in intensive care units: Design of and rationale for the PCplanner randomized clinical trial.

INTRODUCTION: The number of older adults who receive life support in an intensive care unit (ICU), now 2 million per year, is increasing while survival remains unchanged. Because the quality of ICU-based palliative care is highly variable, we developed a mobile app intervention that integrates into the electronic health records (EHR) system called PCplanner (Palliative Care planner) with the goal of improving collaborative primary and specialist palliative care delivery in ICU settings. OBJECTIVE: To describe the methods of a randomized clinical trial (RCT) being conducted to compare PCplanner vs. usual care. METHODS AND ANALYSIS: The goal of this two-arm, parallel group mixed methods RCT is to determine the clinical impact of the PCplanner intervention on outcomes of interest to patients, family members, clinicians, and policymakers over a 3-month follow up period. The primary outcome is change in unmet palliative care needs measured by the NEST instrument between baseline and 1 week post-randomization. Secondary outcomes include goal concordance of care, patient-centeredness of care, and quality of communication at 1 week post-randomization; length of stay; as well as symptoms of depression, anxiety, and post-traumatic stress disorder at 3 months post-randomization. We will use general linear models for repeated measures to compare outcomes across the main effects and interactions of the factors. We hypothesize that compared to usual care, PCplanner will have a greater impact on the quality of ICU-based palliative care delivery across domains of core palliative care needs, psychological distress, patient-centeredness, and healthcare resource utilization.

Top Ten Tips Palliative Care Clinicians Should Know About Integrating Population Health Principles into Practice.

The field of palliative care (PC) has spent the past decade demonstrating that it improves outcomes for patients, clinicians, and health systems. Forward-thinking organizations preparing for a reimbursement system rooted in value have built robust inpatient PC programs and are rapidly moving toward the outpatient and community settings as well. As PC programs get larger and are increasingly tasked with leading a wide variety of diverse initiatives, population health principles can help to focus programs on high-value activities. This article, written by population health researchers and PC clinicians, seeks to provide PC teams nationally with a variety of population health strategies and tools to guide PC delivery throughout the health system and beyond.