Increasing comorbidity and health services utilization in older adults with prior stroke
Bibliographic record
Abstract
OBJECTIVE: To characterize comorbid chronic conditions, describe health services use, and estimate health care costs among community-dwelling older adults with prior stroke. METHODS: This is a retrospective cohort study using administrative data from Ontario, Canada. We identified all community-dwelling individuals aged 66 and over on April 1, 2008 (baseline), who had experienced a stroke at least 6 months prior. We estimated the prevalence of 14 comorbid conditions at baseline; we captured all physician visits, emergency department visits, hospital admissions, home care contacts, and associated costs over 5 years stratifying by number of comorbid conditions. Where possible, we distinguished between health services use for stroke- and non-stroke-related reasons. RESULTS: A total of 29,673 individuals met our criteria. Only 1% had no comorbid conditions, while 74.9% had 3 or more. The most common conditions were hypertension (89.8%) and arthritis (65.8%); 5 other conditions had a prevalence of 20% or more (ischemic heart disease, diabetes, chronic obstructive pulmonary disease, inflammatory bowel disease, and dementia). Use of all health services doubled with increasing comorbidity and was largely attributed to non-stroke-related reasons. Total and per-patient costs increased with comorbidity. Main cost drivers shifted from physician and home care visits to hospital admissions with greater comorbidity. CONCLUSIONS: Our findings demonstrate the importance of community-based patient-centered care strategies for stroke survivors that address their range of health needs and prevent more costly acute care use.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".