Substance use disorders in hospice palliative care: A narrative review of challenges and a case for physician intervention
Bibliographic record
Abstract
OBJECTIVES: Substance use disorders (SUDs) are frequently encountered in hospice palliative care (HPC) and pose substantial quality-of-life issues for patients. However, most HPC physicians do not directly treat their patients' SUDs due to several institutional and personal barriers. This review will expand upon arguments for the integration of SUD treatment into HPC, will elucidate challenges for HPC providers, and will provide recommendations that address these challenges. METHODS: A thorough review of the literature was conducted. Arguments for the treatment of SUDs and recommendations for physicians have been synthesized and expanded upon. RESULTS: Treating SUD in HPC has the potential to improve adherence to care, access to social support, and outcomes for pain, mental health, and physical health. Barriers to SUD treatment in HPC include difficulties with accurate assessment, insufficient training, attitudes and stigma, and compromised pain management regimens. Recommendations for physicians and training environments to address these challenges include developing familiarity with standardized SUD assessment tools and pain management practice guidelines, creating and disseminating visual campaigns to combat stigma, including SUD assessment and intervention as fellowship competencies, and obtaining additional training in psychosocial interventions. SIGNIFICANCE OF RESULTS: By following these recommendations, HPC physicians can improve their competence and confidence in working with individuals with SUDs, which will help meet the pressing needs of this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".