Mobile App-Facilitated Collaborative Palliative Care Intervention for Critically Ill Older Adults: A Randomized Clinical Trial.

Importance: Few person-centered, scalable models of collaborative intensive care unit (ICU) clinician-palliative care specialist care exist.

Objective: To evaluate the effect of a collaborative palliative care intervention compared to usual care among family members of patients in the ICU.

Design, Setting, And Participants: This parallel-group randomized clinical trial with patient-level randomization was conducted between April 2021 and September 2023.

Use of Cannabis-Based Medical Products for Pediatric Health Conditions: A Systematic Review of the Recent Literature.

Introduction: Cannabis policy is rapidly changing in the USA and across the globe, with 24 states legalizing cannabis for adult use and 38 states making medical cannabis available for those with qualified conditions. Building on prior evidence, we reviewed the recently published literature (from the past 5 years) focused on the treatment effects of naturally derived medical cannabis products within the pediatric population.

Methods: We conducted a systematic literature review of three electronic databases using MeSH terms and free-text.

Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use.

Objectives: This study aims to improve the ethical use of machine learning (ML)-based clinical prediction models (CPMs) in shared decision-making for patients with kidney failure on dialysis. We explore factors that inform acceptability, interpretability, and implementation of ML-based CPMs among multiple constituent groups.

Materials And Methods: We collected and analyzed qualitative data from focus groups with varied end users, including: dialysis support providers (clinical providers and additional dialysis support providers such as dialysis clinic staff and social workers); patients; patients' caregivers (n = 52).

Machine Learning for Targeted Advance Care Planning in Cancer Patients: A Quality Improvement Study.

Context: Prognostication challenges contribute to delays in advance care planning (ACP) for patients with cancer near the end of life (EOL).

Objectives: Examine a quality improvement mortality prediction algorithm intervention's impact on ACP documentation and EOL care.

Methods: We implemented a validated mortality risk prediction machine learning model for solid malignancy patients admitted from the emergency department (ED) to a dedicated solid malignancy unit at Duke University Hospital.

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.

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.

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.

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).

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

Standards, Guidelines, and Quality Measures for Successful Specialty Palliative Care Integration Into Oncology: Current Approaches and Future Directions.

Although robust evidence demonstrates that specialty palliative care integrated into oncology care improves patient and health system outcomes, few clinicians are familiar with the standards, guidelines, and quality measures related to integration. These types of guidance outline principles of best practice and provide a framework for assessing the fidelity of their implementation. Significant advances in the understanding of effective methods and procedures to guide integration of specialty palliative care into oncology have led to a proliferation of guidance documents around the world, with several areas of commonality but also some key differences.