Palliative Care in the Community: A Systematic Review of Integrated Services Combining Radiation Therapy for Pain Relief, Home-Based Nursing, and Family Physician Support
Bibliographic record
Abstract
Background: Palliative care in the community is increasingly recognized as essential for improving quality of life in patients with advanced illnesses. Integrated services that combine medical, nursing, and psychosocial support aim to provide comprehensive symptom management, particularly for pain, which remains a major concern. Radiation therapy (RT) has a well-established role in alleviating cancer-related pain, yet its integration with home-based nursing and primary care remains underexplored. Objective: This systematic review aimed to evaluate the effectiveness, feasibility, and outcomes of community-based palliative care models that integrate RT for pain relief, home nursing, and family physician support. Methods: A systematic search was conducted across PubMed, Scopus, Web of Science, and Cochrane Library databases for studies published up to 2025. Inclusion criteria comprised studies describing community-based palliative care models that incorporated RT for pain, home nursing interventions, and primary care physician involvement. Outcomes assessed included pain reduction, patient satisfaction, quality of life, hospital admissions, and service feasibility. Data extraction and quality appraisal were performed independently by two reviewers, with discrepancies resolved by consensus. Results: The review included 21 studies encompassing a total of 3,150 patients. Evidence suggests that integrating RT into home-based palliative care, supported by nursing and family physicians, significantly improved pain management and overall patient comfort. Patients experienced reductions in opioid use, fewer emergency visits, and higher satisfaction with care. Home-based nursing facilitated adherence to care plans, monitoring of treatment side effects, and psychosocial support, while family physicians ensured continuity of care and coordination with oncology services. Barriers identified included logistical challenges for RT delivery, limited interdisciplinary communication, and resource constraints. Conclusion: Community-based integrated palliative care models that combine RT for pain relief with home nursing and family physician support are feasible and effective in improving patient-centered outcomes. These models reduce hospital dependency and enhance quality of life, highlighting the importance of multidisciplinary collaboration in community settings. Future research should focus on standardized protocols, cost-effectiveness, and strategies to overcome logistical barriers in delivering RT in the community.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".