Global Consensus-Based Essential and Expanded Packages for Palliative Care and Pain Relief for Adults and Children: A Delphi Study
Bibliographic record
Abstract
BACKGROUND: In 2018, the Lancet Commission on Global Access to Palliative Care and Pain Relief introduced the concept of serious health-related suffering (SHS) to quantify the need for palliative care and proposed an essential package of palliative care and pain relief (PCPR) to address it. However, this package did not account for complex and specialized needs, and its global implementation has been limited. OBJECTIVES: We conducted a multistage, modified Delphi study to update and expand the initial Essential Package for children and adults METHODS: Two international panels -adult and pediatric- representing diverse geographical regions and income levels participated in two Delphi rounds. External validation was conducted by global experts in palliative care. RESULTS: Retention rates for the Delphi rounds were 79.5% for adults and 64.0% for children. Consensus was achieved on the updated Essential Packages for both adults and children, with minor modifications. Expanded Packages were developed, including additional medications, equipment, and human resources to address broader needs. The study also revealed persistent inequities in medicine availability, particularly in low- and middle-income countries, and limited awareness of the Lancet Commission's Essential Package among health professionals. CONCLUSION: These globally validated Essential and Expanded Packages for adults and children offer a practical adaptable framework to guide national health strategies, strengthen palliative care services, and reduce SHS. Their adoption can meaningfully contribute to achieving Universal Health Coverage.
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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 | 0.177 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".