Bibliographic record
Abstract
The increase of public expenses in the hospital sector has become an issue of great concern in Canada today. This study1 focuses on future requirements for hospital care for the period ranging from 1976 to 2031. It takes into consideration the changing composition of the population as well as the different consuming profiles of various age groups and sex. It further provides alternatives to hospitalisation and illustrates the savings that could be incurred in the process. Finally it does warn against some of the potential dangers of implementing certain alternatives to meet the future increase in demand for hospital services. Main findings: • Demand by the elderly for hospital services will likely more than triple within the next half century. • If the projected need is met by providing new hospital space, annual operating spending on hospitals could more than double to $11 billion. • By 2031, patient-days for the Canadian population as a whole are expected almost to double, from the present 43 million to 84 million. But in the same period, those for persons of 65 or over will multiply by over three times, from 16 million (38% of the current total) to 55 million (65%) of the projected 2031 total). • Greater use of present hospital capacity and the substitution of lower-care facilities like nursing homes or non-institutional care could delay the provision of hospital beds until the mid 1990s. • Establishing more lower-care facilities implies a potential saving on hospital operating costs of $27 billion over the next 50 years. 1. "A Prognosis for Hospitals: The effects of population change on the demand for hospital space, 1967 to 2031", by L.A. Lefebvre, Z. Zsigmond and M.S. Devereaux. Statistique Canada, catalogue 83-520E, 1979.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.160 | 0.020 |
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".