Affirming the Value of the Resident Assessment Instrument: Minimum Data Set Version 2.0 for Nursing Home Decision-Making and Quality Improvement
Bibliographic record
Abstract
BACKGROUND: We examined the agreement over time of the physical functioning domains of the Resident Assessment Instrument: Minimum Data Set Version 2.0 (RAI-MDS) and the Functional Independence Measure (FIM) in nursing home residents with dementia. METHODS: We completed a secondary analysis of data from a longitudinal quasi-experimental study of residents who could transfer independently or with the assistance of one person. FIM assessments were completed at up to three time points by researchers using interviews. RAI-MDS assessments, completed by nursing home staff, were matched to the FIM assessment by nearest time. FIM and RAI-MDS assessments were correlated based on time between assessments using Pearson's correlation. Items for activities of daily living (ADL) from the RAI-MDS were rescaled using two previously published crosswalks. Motor and ADL subscales were also used, containing eight and six items, respectively. RESULTS: A total of 362 paired interviews and assessments were collected from 130 residents. The mean scores and standard deviations were as follows: FIM: 19.64 (7.60); William's RAI-MDS crosswalk: 18.04 (5.25); and Velozo's RAI-MDS crosswalk: 18.09 (6.50). Using both crosswalks, most items showed medium (r > 0.3) or large (r > 0.5) correlations, even at greater than 41 days between assessments. Subscales showed large correlations for all time intervals for both crosswalks. CONCLUSIONS: The RAI-MDS remains stable when data are collected greater than 41 days from the FIM assessment. These findings should add confidence in the RAI-MDS data and its clinical utility.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".