Journal of palliative medicine最新文献

Background: Pediatric home hospice allows children with life-limiting illnesses to receive end-of-life care in familiar surroundings, supported by interprofessional teams. Despite recognized benefits, utilization remained limited in many countries, and few studies evaluated national programs outside of Europe and North America. Objectives: To describe the characteristics, service utilization patterns, and end-of-life outcomes of children enrolled in Israel's largest pediatric home hospice program over a 12-year period. Methods: This retrospective cohort study included all patients aged 0-21 years enrolled in the Sabar Health pediatric home hospice program between 2012 and 2023. Data were extracted from clinical and administrative records and included age, sex, diagnosis, ethnicity, length of stay (LOS), place of death, and discharge status. Descriptive statistics and group comparisons were performed using chi-square and Mann-Whitney U tests. Results: The cohort included 277 patients, of whom 221 (79.8%) had cancer and 56 (20.2%) had non-cancer diagnoses. The median LOS was 40 days (interquartile range [IQR]: 12-89) for cancer patients (p = 0.012) and 84 days (IQR: 20-173) for non-cancer patients. Among the 201 patients who died on hospice, 96 of 221 had cancer (43.4%), and 17 of 56 had non-cancer diagnoses (30.4%). Live discharge occurred in 50 of 221 cancer patients (22.6%) and in 26 of 56 non-cancer patients (46.4%). Most patients were older than five years (n = 228, 82.3%). Conclusions: This study highlights that pediatric home hospice in Israel primarily serves older children and those with cancer diagnoses, while younger children and those with non-cancer diagnoses are less likely to access these services. They are also less likely to die at home. These findings emphasize the need for flexible, diagnosis, and age-sensitive hospice models with early recognition of relevant patients. System-level investment is essential to align pediatric hospice care with clinical realities and family preferences.

Background: Nonpharmacological methods to manage symptoms of cancer and its treatment sequelae, including receptive music-based interventions (rMBIs), have gained traction due to their limited adverse effects and beneficial impact. Despite these benefits, implementation and analysis of personalized rMBIs in the infusion setting remain limited. Objectives: This study provided patients with a personalized rMBI during their infusion session and assessed changes in symptom burden and vitals to evaluate intervention efficacy. Design: The rMBI involved listening to a personalized playlist on Spotify on an iPad for 30 minutes and was assessed both qualitatively and quantitatively. Outcomes include vitals and symptom burden (measured with the Edmonton Symptom Assessment Scale, ESAS) pre- and post-rMBI; changes were analyzed with paired t-tests. Post-rMBI, patient reflections were collected and analyzed with a rapid qualitative analysis approach. Settings/Subjects: This is a self-controlled case series among adult patients receiving infusion therapy at a single academic community hospital in the United States. Measurements/Results: A total of 50 participants were recruited. From the ESAS, rMBI led to significant decreases in pain (p = 0.011), tiredness (p < 0.0001), nausea (p = 0.014), anxiety (p = 0.005), and shortness of breath (p = 0.002), as well as a significant increase in feelings of well-being (p < 0.0001). Heart rate (p < 0.0001) and systolic blood pressure (p = 0.0234) also decreased post-rMBI. Patient narratives demonstrated common themes of escape, reflection/nostalgia, comfort/peace, hope, and rejuvenation. Conclusions: Personalized rMBIs are effective in managing symptoms and enhancing overall well-being in patients receiving infusions. These results support incorporating rMBIs as part of the patient experience and standard of care at infusion centers (NCT06450626).

Background: A novel written exposure-based coping intervention (EASE) for distressed adults with advanced cancer focused on their cancer-related worst-case scenario and showed promise for reducing cancer-related trauma symptoms and fear of cancer progression (FoP). This study examines potential mechanisms of change, specifically linguistic features of participants' writing. Methods: Adults (N = 28) with advanced solid tumor (n = 23) or high-risk blood cancer (n = 5) reporting elevated trauma or FoP participated. Writing was collected during five weekly intervention sessions (three exposure, two coping) and analyzed using linguistic software (LIWC-22). Outcomes were assessed pre-intervention and one-week post-intervention. Results: More positive (trauma: ηp² = 0.64, p < 0.001; FoP: ηp² = 0.34, p = 0.011) and negative (FoP: ηp² = 0.38, p = 0.007) emotion words during exposure writing sessions predicted worse outcomes, while more death-related words predicted reduced FoP (ηp² = 0.22, p = 0.023). Positive tone in coping writing sessions predicted reduced FoP (ηp² = 0.31, p = 0.009), while negative tone predicted worse FoP (ηp² = 0.22, p = 0.026). Conclusions: Findings offer preliminary support for several proposed mechanisms of this novel written exposure intervention.

Context: Artificial intelligence (AI), particularly large language models (LLMs), offers the potential to augment clinical decision-making, including in palliative care pharmacy, where personalized treatment and assessments are important. Despite the growing interest in AI, its role in clinical reasoning within specialized fields such as palliative care remains uncertain. Objectives: This study examines the performance of four commercial-grade LLMs on a Script Concordance Test (SCT) designed for pharmacy students in a pain and palliative care elective, comparing AI outputs with human learners' performance at baseline. Methods: Pharmacy students from 2018 to 2023 completed an SCT consisting of 16 clinical questions. Four LLMs (ChatGPT 3.5, ChatGPT 4.0, Gemini, and Gemini Advanced) were tested using the same SCT, with their responses compared to student performance. Results: The average score for LLMs (0.43) was slightly lower than that of students (0.47), but this difference was not statistically significant (p = 0.55). ChatGPT 4.0 achieved the highest score (0.57). Conclusions: While LLMs show potential for augmenting clinical decision-making, their limitations in patient-centered care highlight the necessity of human oversight and reinforce that they cannot replace human expertise in palliative care. This study was conducted in a controlled research setting, where LLMs were prompted to answer clinical reasoning questions despite default safety restrictions. However, this does not imply that such prompts should be used in practice. Future research should explore alternative methods for assessing AI decision-making without overriding safety mechanisms and focus on refining AI to better align with complex clinical reasoning. In addition, further studies are needed to confirm AI's comparative effectiveness, given the sample size limitations.

Background: The Affordable Care Act (ACA) aimed to expand insurance coverage, improve health outcomes, and reduce costs. We assessed the impact of the ACA on hospice or palliative care utilization among patients with stage IV gastrointestinal (GI) cancer. Methods: Individuals diagnosed with stage IV GI cancer between 2007 and 2019 were identified from the Medicare database. An interrupted time series analysis (ITS) examined the impact of ACA on palliative care utilization. Entropy balancing and gamma regression were used to assess the cost implications of not utilizing palliative care. Results: Among the 26,227 stage IV GI cancer Medicare beneficiaries, approximately half (53.9%) were male. Overall, 80.5% of patients used palliative care before death. Utilization increased from 54.3% in 2007 to 84% in 2013 pre-ACA (slope: +0.009; 95% confidence interval [CI]: 0.005-0.012) and from 84.5% in Q1 2014 to 89.7% in Q4 2019 post-ACA (slope: +0.004; 95% CI: 0.0007-0.007), indicating slow progress in palliative care uptake. The ITS model demonstrated that ACA implementation did not affect palliative care utilization (slope: -0.006; 95% CI: -0.017 to +0.004). Patients from minority racial groups (odds ratio [OR]: 0.79; 95% CI: 0.74-0.86) and those in moderate (OR: 0.86; 95% CI: 0.80-0.94) and high (OR: 0.68; 95% CI: 0.62-0.74) Social Vulnerability Index (SVI) counties were less likely to use palliative care in both pre- and post-ACA eras. Palliative care use was associated with $2,633 lower total expenditure. Conclusion: ACA implementation did not improve palliative care utilization for racial minorities and high SVI groups. Targeted efforts are needed to improve access to equitable end-of-life care.

Background: Palliative sedation has major clinical, social and ethical implications. Vicariously witnessing suffering in others is known to be distressing. However, little is understood about how palliative sedation is experienced by relatives and health care professionals. Objectives: To explore the experiences of relatives and health care professionals with palliative sedation. Design: A qualitative design with thematic framework analysis of data collected in semistructured interviews. Setting/participants: Research was conducted in seven specialist in-patient palliative care services in Belgium, Germany, Italy, the Netherlands, and Spain. A bereaved relative and health care provider linked to a deceased patient with cancer who had palliative sedation was recruited. Measurements: We coded transcripts and characterized factors that arose during the process of palliative sedation. Results: We interviewed 66 people (33 relatives and 33 health care professionals) linked to 33 deceased patients. Three main themes were identified: (1) Understanding the aim of palliative sedation among relatives and health care professionals such as to alleviate suffering, dying with dignity, (2) Palliative sedation is a complex process, accompanied by many uncertainties, which can cause distress for both relatives and health care providers such as eligibility of the patient, when to start or the effectiveness of palliative sedation, (3) Sedation involves a period of intense family communication, collaboration, and caregiving with heightened mixed emotions. Opportunities to say goodbye before starting palliative sedation were important. Conclusion: Relatives and health care professionals focused on the effectiveness of palliative sedation in alleviating suffering and offering a dignified death. It was described as complex, with mixed experiences of relief and distress.

Background: Patient-provider interactions could inform care quality and communication but are rarely leveraged because collecting and analyzing them is both time-consuming and methodologically complex. The growing availability of large language models (LLMs) makes these analyses more feasible, though their accuracy remains uncertain. Objectives: Assess an LLM's ability to analyze patient-provider interactions. Design: Compare a human's and an LLM's codings of clinical encounter transcripts. Setting/Subjects: Two hundred and thirty-six potential symptom discussions from transcripts of clinical encounters with 92 patients living with cancer in the mid-Atlantic United States. Transcripts were analyzed by GPT4DFCI in our hospital's Health Insurance Portability and Accountability Act compliant infrastructure instance of GPT-4 (OpenAI). Measurements: Human and an LLM-coded transcripts to determine whether a patient's reported symptom(s) were discussed, who initiated the discussion, and any resulting recommendation. We calculated Cohen's κ to assess interrater agreement between the LLM and human and qualitatively classified disagreements about recommendations. Results: Interrater reliability indicated "strong" and "moderate" agreement levels across measures: Agreement was strongest for whether the symptom was discussed (k = 0.89), followed by who initiated the discussion (k = 0.82), and the recommendation provided (k = 0.78). The human and LLM disagreed on the presence and/or content of the recommendation in 16% of potential discussions, which we categorized into nine types of disagreements. Conclusions: Our results suggest that LLMs' abilities to analyze clinical encounters are equivalent to humans. Thus, using LLMs as a research tool may make it more feasible to analyze patient-provider interactions, which could have broader implications for assessing and improving care quality, care inequities, and provider communication.