The Southwestern Ontario Joint Replacement Pilot Project: electronic point-of-care data collection. Southwestern Ontario Study Group.
Bibliographic record
Abstract
OBJECTIVE: To pilot a provincial joint replacement registry using electronic point-of-care data collection. DESIGN: Data collection study. SETTING: Southwestern Ontario, which has a population base of 3.5 million people. PARTICIPANTS: Eighteen orthopedic surgeons. METHOD: Information on total hip and knee replacements was obtained by the orthopedic surgeons over a 6-month period. Information was obtained in paper form and electronically on hand-held computers. MAIN OUTCOME MEASURES: Patient demographics, waiting times from referral to operation, patient satisfaction and relevance and value of electronic records compared with paper records. MAIN RESULTS: Data were collected on 815 total hip and knee arthroplasties. A slightly greater number of hips required revision than knees. The majority of patients were in the 60 to 90-year age range. With respect to the waiting time from referral to operation 10% of patients waited less than 5 weeks, 50% waited less than 30 weeks, and 90% waited less than 59 weeks. There was a high level of patient satisfaction with the operation and with hospital care received. Most surgeons found that the gathering and use of data electronically was relevant and easy. The electronic data were more timely, accurate and complete than paper records. CONCLUSION: Electronic point-of-care data collection is appropriate, particularly in high-volume, high-cost surgical interventions such as total joint replacements.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".