Validation of the Provincial Transfer Authorization Centre database: a comprehensive database containing records of all inter-facility patient transfers in the province of Ontario
Bibliographic record
Abstract
BACKGROUND: The Provincial Transfer Authorization Centre (PTAC) was established as a part of the emergency response in Ontario, Canada to the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003. Prior to 2003, data relating to inter-facility patient transfers were not collected in a systematic manner. Then, in an emergency setting, a comprehensive database with a complex data collection process was established. For the first time in Ontario, population-based data for patient movement between healthcare facilities for a population of twelve million are available. The PTAC database stores all patient transfer data in a large database. There are few population-based patient transfer databases and the PTAC database is believed to be the largest example to house this novel dataset. A patient transfer database has also never been validated. This paper presents the validation of the PTAC database. METHODS: A random sample of 100 patient inter-facility transfer records was compared to the corresponding institutional patient records from the sending healthcare facilities. Measures of agreement, including sensitivity, were calculated for the 12 common data variables. RESULTS: Of the 100 randomly selected patient transfer records, 95 (95%) of the corresponding institutional patient records were located. Data variables in the categories patient demographics, facility identification and timing of transfer and reason and urgency of transfer had strong agreement levels. The 10 most commonly used data variables had accuracy rates that ranged from 85.3% to 100% and error rates ranging from 0 to 12.6%. These same variables had sensitivity values ranging from 0.87 to 1.0. CONCLUSION: The very high level of agreement between institutional patient records and the PTAC data for fields compared in this study supports the validity of the PTAC database. For the first time, a population-based patient transfer database has been established. Although it was created during an emergency situation and data collection is dependent on front-line medical workers, the PTAC data has achieved a high level of validity, perhaps even higher than many purpose built databases created during non-emergency settings.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 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) | 0.002 | 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".