Palliative care needs and health seeking behavior of people in two rural districts of nepal: a house-to-house survey
Bibliographic record
Abstract
BACKGROUND: Palliative care is integral to Universal Health Coverage. In Nepal 80% of the population live in rural often mountainous areas. Despite a national commitment to palliative care close to home, services in rural areas remain underdeveloped. We report on the palliative care needs and health seeking behaviour in two rural districts. METHODS: A cross-sectional house to house survey was conducted across four municipalities in two rural districts. People in need of palliative care were identified using the general indicators of Supportive and Palliative Care Indicators Tool for Low Income Settings (SPICT-LIS) and recruited. They were questioned about diagnosis and health seeking behaviour and also about symptoms and quality of life using the Nepali Palliative Care Outcome Scale (N-POS). For those unable to respond, the main carer was asked to provide data. Data were analyzed descriptively using MS Excel 2016. RESULTS: A total of 587 households with 2320 residents were surveyed. Fifty-eight (2.5%) were identified as needing palliative care, ranging from 0.8 to 3.4% between municipalities. Only one child was identified and excluded from this study because their needs are not comparable with adults. The median age of those requiring palliative care was 79 years (Range 21–98); 50% were female. Forty-four/58(76%) had a diagnosis of at least one chronic illness, including hypertension and diabetes, but in only 32/58 (55%) was this a condition potentially leading to palliative care need. Difficulty in walking (58/58;100%), weakness (56/58;97%) and pain (44/58;76%) were the most common physical complaints. Fifty-one/58(93%) reported at least one psychosocial or spiritual need. Of those with a chronic illness diagnosis, 25/44(57%) were receiving ongoing medical care: 16/25(64%) at tertiary hospitals and 5/25(20%) at a local community hospital. Although 41/58(71%) had enrolled in government health insurance, cost remained a commonly reported barrier to accessing health care. CONCLUSION: Significant numbers of adults with palliative need in rural Nepal exist with a high burden of physical, psychosocial and spiritual suffering. Those receiving follow up mainly travel to distant tertiary hospitals with local services being underutilized. Despite health insurance, costs prevented access to health care. Our findings are informing the development of a rural palliative care model for Nepal.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".