Strategic Pain Management: The Identification and Development of the IAHPC Opioid Essential Prescription Package
Bibliographic record
Abstract
The aim of this study was to determine by consensus the components of an opioid essential prescription package (OEPP) to be used when initiating a prescription for the control of moderate to severe chronic pain. Palliative care physicians (n=60) were sampled from the International Association for Hospice and Palliative Care (IAHPC) membership list to represent a range of countries of varying economic levels and diverse geographical regions. Using a Delphi study method, physicians were asked to rank preferences of drug and dosing schedule for first-line opioid, antiemetic, and laxative for the treatment of adults with chronic pain due to cancer and other life-threatening conditions. Overall response rates after two Delphi survey rounds were 95% (n=57) and 82% (n=49), respectively. A consensus (set at ≥75% agreement) was reached to include morphine as first-line opioid at a dose of 5 mg orally every 4 hours. Consensus was reached to include metoclopramide as a first-line antiemetic, but there was no consensus on "regular" or "as needed" administration. No consensus was reached regarding a first-line laxative, but a combination of senna and docusate secured 59% agreement. There was consensus (93% agreement) that laxatives should always be given regularly when opioid treatment is started. Further work is needed to establish a recommended dose of metoclopramide and a type and dose of laxative. The resulting OEPP is international in scope and is designed to ensure that opioids are better tolerated by reducing adverse effects of opioids, which could lead to more sustained improvements in pain management.
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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 | 0.028 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".