Comparison of The Hospice Palliative Care Delivery Systems in Iran and Selected Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: There is an increasing demand for Hospice Palliative Care (HPC) due to the aging population, increased incidence of cancer, and other chronic diseases, as well as recent advances in care and treatment. Objectives: The present study was conducted to examine the nature and structure of HPC services and to describe and compare them in the United Kingdom (UK), Canada, Australia, Japan, India, Jordan, and Iran to extract general conclusions and suggestions for developing HPC systems in Iran. Methods: In the current descriptive-comparative study, from 2018 to 2019, HPC delivery systems in the selected countries and Iran were reviewed based on the World Health Organization (WHO) guideline, and the similarities and differences among them were explained. Results: Developing the National HPC Program and its integration into the health system are important activities. The most common source of financing is donation. The services are mainly provided to patients with cancer. Human resource development includes curriculum reform, creating specialty, subspecialty disciplines, and holding training courses. Other activities include designing national guidelines, the free access to opioids, research development, the establishment of the national information network, and the quality control programs. Iran lacks any formal structure and program of HPC services and they are provided in a scattered and very limited manner as part of general palliative services. Conclusions: HPC services are in a mediate and low level in developed countries and Iran, respectively. Before the establishment of the HPC delivery system, a complicated range of economic, social, cultural, and political factors must be considered.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it