Equity in waiting times for major joint arthroplasty.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To ascertain whether waiting lists are managed in an equitable fashion in a universal health system by examining demographic, socioeconomic and clinical factors, along with 2 health systems variables. DESIGN: A prospective survey by questionnaire. SETTING: The Capital Health Region of Edmonton, Alta. PATIENTS AND METHODS: A cohort of 553 patients, who were waiting for either total hip or total knee replacement surgery, seen between Dec. 18, 1995, and Jan. 24, 1997. INTERVENTIONS: A home visit was made when the patient was first placed on the waiting list and again just before surgery to complete the questionnaires. The Western Ontario and McMaster Universities (WOMAC) instrument and the Medication Quantification Score were administered at the time the patient was placed on the waiting list. MAIN OUTCOME MEASURE: The length of waiting time, defined as the date the patient was put on the waiting list to the date the patient was operated on. RESULTS: There were no biases in waiting time with respect to age, gender, education or work status. Although pain and function were not related to waiting time, multivariate analyses found that marital status, primary language, body mass index, pain medication use and the size of the surgeons' major joint replacement practice determined waiting time for surgery. However, this model explained only 10% of the variance in waiting time. CONCLUSION: Waiting lists were managed unfairly in terms of clinical equity (clinical severity) but managed fairly in terms of social equity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it