Identifying geographical regions serviced by hospitals to assess laboratory-based outcomes
Bibliographic record
Abstract
OBJECTIVE: To define geographical regions (forward sortation areas; FSAs) in Southwestern Ontario, Canada from which patients would reliably present to a hospital with linked laboratory data if they developed adverse events related to medications dispensed in outpatient pharmacies. DESIGN: Descriptive research. SETTING: Forty-five hospitals in Southwestern Ontario, Canada, from 2003 to 2009. PARTICIPANTS: Patients aged 66 years and older who received an outpatient prescription for any drug and presented to the emergency department in the subsequent 120 days. MAIN OUTCOME MEASURE: The proportion of patients in a given FSA presenting to an emergency department at a hospital with linked laboratory data versus a hospital without linked laboratory data. To be included in the catchment area at least 90% of emergency department visits in an FSA must have occurred at laboratory-linked hospitals in a given year. RESULTS: Over the study period, there were 649 713 emergency department visits by patients with recent prescription claims from pharmacies in 1 of 118 FSAs. In total, 141 302 of these patients presented to an emergency department at a laboratory-linked hospital. For the year 2003, 12 FSAs met our criteria to be in the catchment area and this number grew to 25 FSAs by the year 2009. CONCLUSIONS: The relevant geographical regions for hospitals with linked laboratory data have been successfully identified. Studies can now be conducted using these well-defined areas to obtain reliable information on the incidence and absolute risk of presenting to hospital with laboratory abnormalities in older adults dispensed commonly prescribed medications in outpatient pharmacies.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".