Referral patterns of stroke rehabilitation inpatients to a model system of outpatient services in Ontario, Canada: a 7-year retrospective analysis
Bibliographic record
Abstract
BACKGROUND: While several studies have tracked the care paths of patients in the early phases of stroke recovery, studies examining the transition from inpatient to outpatient rehabilitation are lacking. Examining this transition allows for improved understanding and refinement of the process whereby patients are referred and admitted to programs. The objective of this study was to examine the referral patterns of stroke rehabilitation inpatients to outpatient stroke therapy services, their demographics, and clinical profile. METHODS: This study examined patients who: (1) were admitted to an inpatient stroke rehabilitation unit between January 1, 2009 and March 1, 2016, (2) had a stroke diagnosis, (3) had an inpatient length of stay of > 1 day, and (4) lived within the geographical boundaries of the South West Local Health Integration Network which allowed them access to both hospital-based and home-based stroke rehabilitation outpatient programs. Patient data was collected from the National Rehabilitation Reporting System, as well as three hospital outpatient administrative databases. These databases were cross-referenced to determine each patient's pathway. Those referred to an outpatient therapy program, and those who attended the outpatient programs, were compared to those who were not, and did not, respectively. RESULTS: 1497 inpatients were included in the analysis. Upon discharge, 1037 (69.3%) of patients had an outpatient clinic, follow-up appointment scheduled; of those, 902 (87.0%) patients attended at least one outpatient clinic visit. 891 (59.5%) were referred to one of the interdisciplinary outpatient stroke rehabilitation programs; of those, an outpatient therapy program was attended by 80.9% of patients (n = 721). Of those receiving outpatient therapy services, the number of patients attending the in-hospital versus home-based program were equal, 360 and 361 individuals, respectively. CONCLUSION: This study allows for a better understanding of the transition between inpatient and outpatient stroke care. There is a paucity of this type of information in stroke rehabilitation literature to date. This study acts as a starting point in improving rehabilitation planning across the continuum of 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".