An Integrated Health Care System’s Approach to Development of a Process to Collect Patient Functional Outcomes on Total Joint Replacement Procedures
Bibliographic record
Abstract
Health care organizations are challenged to find ways to measure not only process of care but also outcomes of care. Gundersen Health System's Orthopaedic Surgery Department in the La Crosse, Wisconsin area developed a process to collect outcomes of care for patients having hip or knee arthroplasty procedures and planned to use these data to determine impact on patients' lives. The Hip Osteoarthritis Outcomes Score and Knee Osteoarthritis Outcomes Score, adapted from the widely used Western Ontario and McMaster Universities Osteoarthritis Index, were collected preoperatively and at 1 year postoperatively. From these data, the health system determined that patients were experiencing significant improvement in 4 of 5 scales. Further recommendations include evaluating the impact of patients' age, sex, and preoperative body mass index on outcomes, as well as evaluating the impact of more patient involvement in goal setting on recovery time and functional outcomes.
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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 | 0.123 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.001 | 0.005 |
| 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".