Abraham A. Brody

Abstract

Context: Chronic kidney disease (CKD) disproportionately impacts lower socioeconomic groups and is associated with many symptoms and complex decisions. Integration of Kidney Supportive Care (KSC) with CKD care can address these needs. To our knowledge, this approach has not been described in an underserved population. Objectives: We describe our adaptation of an ambulatory integrated KSC and CKD clinic for implementation in a safety net hospital. We report our utilization metrics; characteristics of the population served; and visit activities. Methods: We considered modifications from the perspectives of people with CKD, their providers, and the health system. Modifications were informed by meeting notes with key participants (hospital administrators [n = 5], funders [n = 1], and content experts [n = 2]), as well as literature on palliative care program building, safety net hospitals, and KSC. We extracted utilization data for the first 15 months of the clinic's operations, demographics, clinical characteristics, unmet health related social needs, and symptom burden, measured by the Integrated Palliative Outcome Scale-Renal (total Score, and sub-scores of physical, psychological, and practical impact of CKD) from the electronic health record. Results are reported using descriptive statistics. Results: Adaptions were proactive and done by clinical and administrative leaders. Meetings identified challenges of the safety net setting including people presenting with advanced disease and having several social needs. Modifications to our base model were made in staffing, data collection, and work flow. Show rate was approximately 68%, with a majority of people identifying as Black or Hispanic, and uninsured or on Medicaid. Symptom burden was lower than previous reports, driven by a better psychological sub-score. Conclusions: We describe a feasible ambulatory care model of KSC in a safety net setting that can serve as a framework for the development of other noncancer palliative care ambulatory clinics. Future work will optimize our model.

Abstract

BACKGROUND AND OBJECTIVES: Goal-concordant transition to hospice is an important facet of end-of-life care for people living with dementia. The objective of this integrative review was to appraise existing evidence and gaps focused on interventions and predictors of transition to hospice and end-of-life care for persons living with dementia across healthcare to inform future research.RESEARCH DESIGN AND METHODS: Using integrative review methodology by Whittemore and Knafl, five databases were searched (PubMed, CINAHL, Web of Science, Google Scholar, Cochrane Database for Systematic Reviews) for articles between 2000 and 2023. The search focused on dementia, hospice care, transitions, care management and/or coordination, and intervention studies.RESULTS: Fourteen articles met inclusion criteria after critical appraisal. Most were cross-sectional in design and conducted in nursing homes and hospitals in the U.S. persons living with dementia had multiple chronic conditions including cancer, diabetes, heart disease, and stroke. Interventions included components of hospice decision-making delivered through advance care planning, checklist-based care management for hospice transition, and palliative care for those with severe dementia. Predictors included increasing severity of illness including functional decline, organ failure, intensive care use, and the receipt of palliative care. Other predictors were related to insurance status, race and ethnicity, and caregiver burden. Overall, despite moderate to high-quality evidence, the studies were limited in scope and sample and lacked racial and ethnic diversity.DISCUSSION AND IMPLICATIONS: Prospective, multisite randomized trials and population-based analyses including larger and diverse samples are needed for improved end-of-life dementia illness counseling and hospice care transitions for persons living with dementia and their caregivers.

Abstract

Context: Social determinants of health (SDOH) impacted the quality of home hospice care provided during the COVID-19 pandemic. Perspectives from professionals who provided care identify challenges and lessons learned from their experience. Objective: To examine hospice professionals’ perspectives of how SDOH affected the delivery of high-quality home hospice care in New York City (NYC) during the COVID-19 pandemic. Methods: We conducted semistructured interviews with 30 hospice professionals who delivered care to home hospice patients during the COVID-19 pandemic in NYC using a qualitative descriptive design. Purposive sampling was used to recruit professionals from a range of disciplines including physicians, advanced practice providers, nurses, social workers, chaplains, and hospice administration and management. Participants worked for one of two large NYC metro hospices and one outpatient palliative care practice serving the five boroughs of NYC and the surrounding suburbs. Rapid qualitative analysis was used to identify themes. Results: Thirty hospice professionals were interviewed, spanning a variety of clinical and administrative roles. Most (21 out of 30) reported that social determinants affected access and/or delivery of equitable hospice care. Two key themes emerged from interviews: (1) SDOH exist and affect the delivery of high-quality care and (2) disparities were exacerbated during the COVID-19 pandemic resulting in barriers to care. Subthemes outline barriers described by hospice professionals: decreased hospice enrollment, telehealth challenges, resulting in deficient patient/family education, shortages of nursing assistants in some neighborhoods, and diminished overall quality of hospice care for some patients. SDOH created barriers to hospice care through neighborhood factors, resource barriers, and system challenges. Conclusion: SDOH provide a context to understand disparity in the provision of hospice care. COVID-19 exacerbated these conditions. Addressing multidimensional barriers created by SDOH is key in creating high-quality and equitable hospice care, particularly during a crisis.

Abstract

Digital health implementations and investments continue to expand. As the reliance on digital health increases, it is imperative to implement technologies with inclusive and accessible approaches. A conceptual model can be used to guide equity-focused digital health implementations to improve suitability and uptake in diverse populations. The objective of this study is expand an implementation model with recommendations on the equitable implementation of new digital health technologies. The Digital Health Equity-Focused Implementation Research (DH-EquIR) conceptual model was developed based on a rigorous review of digital health implementation and health equity literature. The Equity-Focused Implementation Research for Health Programs (EquIR) model was used as a starting point and merged with digital equity and digital health implementation models. Existing theoretical frameworks and models were appraised as well as individual equity-sensitive implementation studies. Patient and program-related concepts related to digital equity, digital health implementation, and assessment of social/digital determinants of health were included. Sixty-two articles were analyzed to inform the adaption of the EquIR model for digital health. These articles included digital health equity models and frameworks, digital health implementation models and frameworks, research articles, guidelines, and concept analyses. Concepts were organized into EquIR conceptual groupings, including population health status, planning the program, designing the program, implementing the program, and equity-focused implementation outcomes. The adapted DH-EquIR conceptual model diagram was created as well as detailed tables displaying related equity concepts, evidence gaps in source articles, and analysis of existing equity-related models and tools. The DH-EquIR model serves to guide digital health developers and implementation specialists to promote the inclusion of health-equity planning in every phase of implementation. In addition, it can assist researchers and product developers to avoid repeating the mistakes that have led to inequities in the implementation of digital health across populations.

Abstract

Background: Home-based primary care (HBPC) is an important care delivery model for high-need older adults. Currently, target patient populations vary across HBPC programs, hindering expansion and large-scale evaluation. Objectives: Develop and validate criteria that identify appropriate HBPC target populations. Research Design: A modified Delphi process was used to achieve expert consensus on criteria for identifying HBPC target populations. All criteria were defined and validated using linked data from Medicare claims and the National Health and Aging Trends Study (NHATS) (cohort n=21,727). Construct validation involved assessing demographics and health outcomes/expenditures for selected criteria. Subjects: Delphi panelists (n=29) represented diverse professional perspectives. Criteria were validated on community-dwelling Medicare beneficiaries (age above 70) enrolled in NHATS. Measures: Criteria were selected via Delphi questionnaires. For construct validation, sociodemographic characteristics of Medicare beneficiaries were self-reported in NHATS, and annual health care expenditures and mortality were obtained via linked Medicare claims. Results: Panelists proposed an algorithm of criteria for HBPC target populations that included indicators for serious illness, functional impairment, and social isolation. The algorithm's Delphi-selected criteria applied to 16.8% of Medicare beneficiaries. These HBPC target populations had higher annual health care costs [Med (IQR): $10,851 (3316, 31,556) vs. $2830 (913, 9574)] and higher 12-month mortality [15% (95% CI: 14, 17) vs. 5% (95% CI: 4, 5)] compared with the total validation cohort. Conclusions: We developed and validated an algorithm to define target populations for HBPC, which suggests a need for increased HBPC availability. By enabling objective identification of unmet demands for HBPC access or resources, this algorithm can foster robust evaluation and equitable expansion of HBPC.

Abstract

Introduction: This study aimed to assess emergency nurses’ perceived barriers toward engaging patients in serious illness conversations. Methods: Using a mixed-method (quant + QUAL) convergent design, we pooled data on the emergency nurses who underwent the End-of-Life Nursing Education Consortium training across 33 emergency departments. Data were extracted from the End-of-Life Nursing Education Consortium post-training questionnaire, comprising a 5-item survey and 1 open-ended question. Our quantitative analysis employed a cross-sectional design to assess the proportion of emergency nurses who report that they will encounter barriers in engaging seriously ill patients in serious illness conversations in the emergency department. Our qualitative analysis used conceptual content analysis to generate themes and meaning units of the perceived barriers and possible solutions toward having serious illness conversations in the emergency department. Results: A total of 2176 emergency nurses responded to the survey. Results from the quantitative analysis showed that 1473 (67.7%) emergency nurses reported that they will encounter barriers while engaging in serious illness conversations. Three thematic barriers—human factors, time constraints, and challenges in the emergency department work environment—emerged from the content analysis. Some of the subthemes included the perceived difficulty of serious illness conversations, delay in daily throughput, and lack of privacy in the emergency department. The potential solutions extracted included the need for continued training, the provision of dedicated emergency nurses to handle serious illness conversations, and the creation of dedicated spaces for serious illness conversations. Discussion: Emergency nurses may encounter barriers while engaging in serious illness conversations. Institutional-level policies may be required in creating a palliative care-friendly emergency department work environment.

Abstract

Ensuring reliability of Large Language Models (LLMs) in clinical tasks is crucial. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 notes remained, of which 765 underwent ChatGPT (GPT-4) and LlaMA-2, and 22 experts reviewed the responses. ChatGPT successfully extracted MMSE and CDR instances with dates from 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss’ Kappa), precision, recall, true/ false negative rates, and accuracy were calculated. Our study follows TRIPOD reporting guidelines for model validation. For MMSE information extraction, ChatGPT (vs. LlaMA-2) achieved accuracy of 83% (vs. 66.4%), sensitivity of 89.7% (vs. 69.9%), true-negative rates of 96% (vs 60.0%), and precision of 82.7% (vs 62.2%). For CDR the results were lower overall, with accuracy of 87.1% (vs. 74.5%), sensitivity of 84.3% (vs. 39.7%), true-negative rates of 99.8% (98.4%), and precision of 48.3% (vs. 16.1%). We qualitatively evaluated the MMSE errors of ChatGPT and LlaMA-2 on double-reviewed notes. LlaMA-2 errors included 27 cases of total hallucination, 19 cases of reporting other scores instead of MMSE, 25 missed scores, and 23 cases of reporting only the wrong date. In comparison, ChatGPT’s errors included only 3 cases of total hallucination, 17 cases of wrong test reported instead of MMSE, and 19 cases of reporting a wrong date. In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.

Abstract

The purpose of this article was to analyze the concept of "the fighter in the intensive care unit (ICU)"per the scientific literature and the impact this mentality has on care administered in the ICU. A literature review and a concept analysis based on Rodger's evolutionary method were performed to identify surrogate terms, antecedents, attributes, and consequences pertaining to the "fighter"in the ICU. Thirteen articles with a focus on "the fighter"were included in this analysis. There is a strong desire to remain optimistic and maintain high spirits as a coping mechanism in the face of extreme prognostic uncertainty. Themes that emerged from the literature were the need to find inner strength and persist in the face of adversity. The concept of "the fighter in the ICU"can serve as either adaptive or maladaptive coping, depending on the larger clinical picture. Patient experiences in the ICU are fraught with physical and psychological distress. How the patient and family unit cope during this anxiety-provoking time is based on the individual. Maintaining optimism and identifying as a fighter can be healthy ways to adapt to the circumstances. This concept analysis highlights the importance of holistic care and instilling hope particularly as patients may be nearing the end of life.

Abstract

Objectives: To describe the implementation of a mentored staff-delivered sleep program in nursing facilities. Design: Modified stepped-wedge unit-level intervention. Setting and Participants: This program was implemented in 2 New York City nursing facilities, with partial implementation (due to COVID-19) in a third facility. Methods: Expert mentors provided staff webinars, in-person workshops, and weekly sleep pearls via text messaging. We used the integrated Promoting Action on Research Implementation in Health Services (i-PARiHS) framework as a post hoc approach to describe key elements of the SLUMBER implementation. We measured staff participation in unit-level procedures and noted their commentary during unit workshops. Results: We completed SLUMBER within 5 units across 2 facilities and held 15 leadership meetings before and during program implementation. Sessions on each unit included 3 virtual webinar presentations and 4 in-person workshops for each nursing shift, held over a period of 3 to 4 months. Staff attendance averaged >3 sessions per individual staff member. Approximately 65% of staff present on each unit participated in any given session. Text messaging was useful for engagement, educational reinforcement, and encouraging attendance. We elevated staff as experts in the care of their residents as a strategy for staff engagement and behavior change and solicited challenging cases from staff during workshops to provide strategies to address resident behavior and encourage adoption when successful. Conclusions and Implications: Engaging staff, leadership, residents, and family of nursing facilities in implementing a multicomponent sleep quality improvement program is feasible for improving nursing facilities’ sleep environment. The program required gaining trust at multiple levels through presence and empathy, and reinforcement mechanisms (primarily text messages). To improve scalability, SLUMBER could evolve from an interdisciplinary investigator-based approach to internal coaches in a train-the-trainer model to effectively and sustainably implement this program to improve sleep quality for facility residents.