Building a Rational Clinical Information System for Older Adults in Acute Care: The Role of the interRAI Acute Care Suite
Bibliographic record
Abstract
Prior research has identified gaps in the ability of hospital systems to efficiently and meaningfully characterize older adults with complex health needs. We recruited community-dwelling older adults presenting to 10 Emergency Departments (EDs) across Ontario, Quebec, and Newfoundland, Canada, from April 2017 to July 2018. We deployed a staged assessment strategy based on the interRAI Acute Care Suite to identify and characterize older adults at high risk of Alternate Level of Care designation. More than 5,700 patients underwent the ED-Screener, 53.3% of whom were not self-reliant. Subsequent focused screening and assessment identified 457 patients, 93.3% of whom were not self-reliant, and who had significant impairments in function, mobility, and cognition, as well as social vulnerability. A staged assessment approach based upon the interRAI Acute Care Suite can efficiently identify older adults with risk factors for Alternative Level of Care designation.
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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 | 0.030 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".