Patient-Level Stroke Outcomes Following Linkage of a Statewide Stroke Registry to Administrative Claims Data
Bibliographic record
Abstract
Background Collection of patient-level outcomes data following hospital discharge is challenging for stroke registries. Data linkage to administrative claims data is a potential solution to obtain outcomes data. We aimed to generate data on 30-day, 90-day and 1-year outcome events following hospitalization for stroke using linked data in Michigan. Methods We probabilistically linked clinical data from a 5-year cohort (2016-2020) of all index acute stroke discharges (ICD-10 I61-I63) from 31 hospitals participating in Michigan’s Acute Stroke program (MiSP) to a representative statewide multi-payer claims database. We used the linked data to generate data on 30-day, 90-day, and 1-year event rates including hospital readmissions, stroke recurrence, post-acute care services (i.e., facility-based rehabilitation and home health), and out-patient visits. Mortality data was only available for Medicare fee-for-service beneficiaries. Outcomes were stratified by age, race, stroke type, and stroke severity. Results Of the 46,330 MiSP stroke discharges, 23,918 (51.6%) were linked to the claims database. Readmission and stroke recurrence rates were 14.1% and 3.3%, respectively, at 30 days, increasing to 42.2% and 8.3% at one year. By 30 days about a quarter of subjects had used facility-based rehab and another quarter had used home health; home health utilization increased to 44.7% by one year. At all time points Black patients had significantly higher readmission rates compared to whites, but higher stroke recurrence rates were only observed at the 1-year mark. At 30 days, utilization of post-acute care services did not differ by race, but utilization rates were significantly higher in Blacks at 90 days and one year. In contrast utilization of outpatient services was significantly higher among White patients at all time points. Conclusions Linkage between acute stroke registry and claims data provides an important source of surveillance data for stroke outcomes up to 1-year post discharge. This data allows for real-time monitoring of healthcare outcomes and potentially leads to interventions to improve stroke care.
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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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".