Implementing a provincial case mix adjusted funding model for inpatient rehabilitation activity: the impact on bed designations
Bibliographic record
Abstract
Data In the fall of 2002, the Ontario Ministry of Health and Long Term Care (MOHLTC) mandated the collection of National Rehabilitation Reporting System (NRS) data in all designated adult inpatient rehabilitation beds. From these data we developed a case mix grouping methodology with associated weights. Together these are being used to incorporate adult inpatient rehabilitation activity into the Integrated Population Based Allocation (IPBA) hospital funding formula. In Ontario, designated inpatient rehabilitation is typically provided in two sectors. Within the acute care sector, hospitals may or may not have designated rehabilitation beds. Even in hospitals that do not have designated rehabilitation beds, a patient may receive some rehabilitation while an inpatient, or on an outpatient basis. For example, a patient who has just had surgery may be visited by a physiotherapist to increase rangeof-motion and strength while recovering from surgery. Within the rehabilitation hospital sector, facilities typically have designated rehabilitation beds and are usually referred to as rehabilitation hospitals. The care in these facilities is often organized on a programmatic basis, time limited and goal oriented. For example, a facility may have a stroke rehabilitation program that is 6 to 8 weeks long for individuals following stroke. These programs are provided on an inpatient basis and may or may not have an outpatient component at the end. Rehabilitation is also provided in other sectors of the health care system, but not on a designated inpatient basis. Provincial Implementation:
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".