Primary Care Provider Density and Elective Total Joint Replacement Outcomes.
Bibliographic record
Abstract
BACKGROUND: Primary care physicians (PCPs) are often gatekeepers to specialist care. This study assessed the relationship between PCP density and total knee (TKA) and total hip arthroplasty (THA) outcomes. METHODS: We obtained patient-level data from an institutional registry on patients undergoing elective primary TKA and THA for osteoarthritis, including Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function scores at baseline and 2 years. Using geocoding, we identified the number of PCPs in the patient's census tract (communities). We used Augmented Inverse Probability Weighting and Cross-validated Targeted Minimum Loss-Based Estimation to compare provider density and outcomes adjusting for potential confounders. RESULTS: Our sample included 3606 TKA and 4295 THA cases. The median number of PCPs in each community was similar for both procedures: TKA 2 (interquartile range 1, 6) and for THA 2 (interquartile range 1, 7). Baseline and 2-year follow-up WOMAC pain, function, and stiffness scores were not statistically significantly different comparing communities with more than median number of PCPs to those with less than median number of PCPs. In sensitivity analyses, adding 1 PCP to a community with zero PCPs would not have statistically significantly improved baseline or 2-year follow-up WOMAC pain, function, and stiffness scores. CONCLUSIONS: In this sample of patients who underwent elective TKA or THA for osteoarthritis, we found no statistically significant association between PCP density and pain, function, or stiffness outcomes at baseline or 2 years. Further studies should examine what other provider factors affect access and outcomes in THA and TKA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".