Increasing Complexity of New Nursing Home Residents in Ontario, Canada: A Serial Cross‐Sectional Study
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Bibliographic record
Abstract
OBJECTIVES: The main objective of the study was to investigate annual changes in the sociodemographic characteristics, morbidity, and functional status of new nursing home residents in Ontario, Canada, between 2000 and 2015. A secondary objective was to develop and assess the quality of an algorithm for ascertaining admissions into publicly funded nursing homes in Ontario using a combination of health administrative data sources that indirectly identifies the residential status of new nursing home residents. DESIGN: Population-based serial cross-sectional study with an accompanying quality assessment study of algorithms. SETTING: Publicly funded nursing care homes in Ontario, Canada. PARTICIPANTS: The reference standard for the assessment of algorithm performance was 21 544 newly admitted nursing home residents identified from the Resident Assessment Instrument-Minimum Data Set in 2012. The selected algorithm was then used to identify serial cross-sectional cohorts of newly admitted residents between 2000 and 2015 that ranged in size between 14 651 and 23 630 residents. MEASUREMENTS: Sociodemographic characteristics, morbidity, and functional status of new residents were determined upon admission to examine patterns in the cohorts' profiles. RESULTS: The proportion of residents aged 85 years and older increased from 45.1% to 53.8% over 16 years. The proportions of individuals with seven or more chronic conditions (from 14.1% to 22.1%) and with nine or more prescription medications (from 44.9% to 64.2%) have also increased in parallel over time. Hypertension, osteoarthritis, and dementia were the most prevalent conditions captured, with the proportion of incoming residents with dementia increasing from 42.3% to 54.1% between 2000 and 2015. Newly admitted residents were more likely to have extensive physical and cognitive impairments upon admission. CONCLUSION: Admission trends show that new residents were older and had greater multimorbidity and limitations in physical functioning over time. J Am Geriatr Soc 68:1293-1300, 2020.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it