Optimizing the InterRAI Assessment Tool in Care Planning Processes for Long-Term Residents: A Scoping Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this review was to chart and report on existing literature that discusses how the interRAI assessment tool drives care-planning processes for residents in long-term-care settings. This scoping review was informed by the Joanna Briggs Institute guidelines for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guideline. Relevant studies were obtained from databases search of CINAHL (EBSCO), MEDLINE (Ovid), PsycINFO (EBSCO), Academic Search Premier (EBSCO), Embase (Elsevier), ProQuest Nursing and Allied Health Database (ProQuest), Sociological Abstracts (ProQuest), and Social Services Abstracts (ProQuest). Of the 17 included studies, five (29.4%) addressed interRAI's minimum dataset component as a clinical data-collection tool; five (29.4%) addressed interRAI's assessment scales and its clinical-assessment protocols as viable health-assessment tools; four (23.5%) considered interRAI's assessment scales in terms of whether this tool is capable of predicting residents' health risks; one (5.9%) addressed the effects of interRAI's care plans on residents' health outcomes; and the remaining two studies (11.8%) used interRAI's quality-indicator function for both the performance of and improvements in the quality of care. The scoping review finds that there is no substantial evidence that supports the implementation of interRAI care plans for consistent health outcomes.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.006 |
| 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 it