Determinants of access of frail, community‐residing older adults to geriatricians in Ontario
Bibliographic record
Abstract
OBJECTIVES: Little is known about determinants of access to community-based geriatricians. The Geriatric 5Ms™ describe geriatricians' core competencies and inform referrals to specialists for older adults with complex needs. We explored the association of the Geriatric 5Ms™ and other characteristics with outpatient access to geriatricians by home care (HC) clients. METHODS: This was a population-based, retrospective cohort study of frail community-dwelling HC clients (≥60 years) with complex needs (n = 196,444). Health assessment information was linked to health services data in Ontario, Canada, 2012-2015. Multivariable generalized estimating equations were used to identify characteristics associated with geriatrician contact (≥1 visit in 90 days post-HC admission), including derived Geriatric 5Ms™ score, and predisposing, enabling, and need factors obtained from clinical assessments. RESULTS: Only 5.2% of the cohort had outpatient geriatrician contact in Ontario, Canada. Derived Geriatric 5Ms™ score was associated with higher odds of contact, but the model had modest discriminatory power (c-statistic = 0.67). In the broader multivariable model, based on empirically included factors and adjusted for regional differences, age, worsening of decision-making, dementia, hallucinations, Parkinsonism, osteoporosis, and caregiver distress/institutionalization risk were associated with higher odds of geriatrician contact. Female sex, difficulties accessing home, impaired locomotion, recovery potential, hemiplegia/hemiparesis, and cancer, were associated with lower odds of contact. This model had good discriminatory power (c-statistic = 0.77). CONCLUSIONS: Few frail, community-dwelling older adults receiving HC had any outpatient geriatrician contact. While the derived Geriatric 5Ms™ score was associated with contact, a broader empirical model performed better than the Geriatric 5Ms™ in predicting contact with an outpatient geriatrician. Contact was mainly driven by conditions common in older adults, but evidence suggests that geriatricians are not evaluating the most medically complex and unstable older adults in the community. These findings suggest a need to re-examine the referral process for geriatricians and the allocation of limited specialized resources.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".