Description of a Tertiary Swiss University Hospital Palliative Population Based on the International Classification of Disease (ICD): A Retrospective Pilot Study
Bibliographic record
Abstract
BACKGROUND: The factors for assessing the utilization rate of a palliative care service are various and complex. Several authors have described different methods to address this problem. McNamara and colleagues have proposed criteria to determine "minimal," "mid-range," and "maximal" palliative population estimates. In order to evaluate the utilization of our intrahospital palliative care consult team (PCT), it appeared necessary to better describe and define the population who dies in our institution, a Swiss university hospital. The goal of this pilot study was to determine what percentage of patients who died in our hospital over a 4-month period in 2007 was seen by the palliative care consult team (PCT), using "minimal" and "maximal" population estimates. METHODS: The hospital database was searched for all adult patients who died during that period and the "maximal" and "minimal" populations determined. The PCT's database was searched to identify those patients who had been seen by the PCT. The charts of a random sample of patients who did not initially meet the "minimal" criteria were hand searched. RESULTS: A total of 294 adult deaths were reported: 263 (89%) met the "maximal" criteria and 83 (28%) met the "minimal" criteria initially. The random search of 56 charts of the 180 patients who did not meet the "minimal" criteria revealed that 21 (38%) should have been included in the "minimal" population. The PCT saw 67/263 (25.5%) of the "maximal" palliative patient population and 56/151 (37.1%) of the "minimal" palliative population. CONCLUSION: This study highlights the usefulness of the method proposed by McNamara and colleagues to determine palliative populations. However, it also illustrates an important limitation of the "minimal" estimate and reliance on the accuracy of the cause of death as noted on the death certificate. A strategy to address this limitation is suggested. The "maximal" estimate suggests that the PCT is being underutilized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".