Provision of Palliative Care in Low- and Middle-Income Countries: Overcoming Obstacles for Effective Treatment Delivery
Bibliographic record
Abstract
Despite being declared a basic human right, access to adult and pediatric palliative care for millions of individuals in need in low- and middle-income countries (LMICs) continues to be limited or absent. The requirement to make palliative care available to patients with cancer is increasingly urgent because global cancer case prevalence is anticipated to double over the next two decades. Fifty percent of these cancers are expected to occur in LMICs, where mortality figures are disproportionately greater as a result of late detection of disease and insufficient access to appropriate treatment options. Notable initiatives in many LMICs have greatly improved access to palliative care. These can serve as development models for service scale-up in these regions, based on rigorous evaluation in the context of specific health systems. However, a multipronged public health approach is needed to fulfill the humane and ethical obligation to make palliative care universally available. This includes health policy that supports the integration of palliative care and investment in systems of health care delivery; changes in legislation and regulation that inappropriately restrict access to opioid medications for individuals with life-limiting illnesses; education and training of health professionals; development of a methodologically rigorous data and research base specific to LMICs that encompasses health systems and clinical care; and shifts in societal and health professional attitudes to palliative and end-of-life care. International partnerships are valuable to achieve these goals, particularly in education and research, but leadership and health systems stewardship within LMICs are critical factors that will drive and implement change.
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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 | 0.022 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".