Measuring the frequency and variation of unnecessary care across Canada
Bibliographic record
Abstract
Abstract Background Through the Choosing Wisely Canada (CWC) campaign, national medical specialty societies have released hundreds of recommendations against health care services that are unnecessary, i.e. present little to no benefit or cause avoidable harm. Despite growing interest in unnecessary care both within Canada and internationally, prior research has typically avoided taking a national or even multi-jurisdictional approach in measuring the extent of the issue. This study estimates use of three unnecessary services identified by CWC recommendations across multiple Canadian jurisdictions. Methods Two retrospective cohort studies were conducted using administrative health care data collected between fiscal years 2011/12 and 2012/13 to respectively quantify use of 1) diagnostic imaging (spinal X-ray, CT or MRI) among Albertan patients following a visit for lower back pain and 2) cardiac tests (electrocardiogram, chest X-ray, stress test, or transthoracic echocardiogram) prior to low-risk surgical procedures in Alberta, Saskatchewan, and Ontario. A cross-sectional study of the 2012 Canadian Community Health Survey was also conducted to estimate 3) the proportion of females aged 40–49 that reported having a routine mammogram in the past two years. Results Use of unnecessary care was relatively frequent across all three services and jurisdiction measured: 30.7% of Albertan patients had diagnostic imaging within six months of their initial visit for lower back pain; a cardiac test preceded 17.9 to 35.5% of low-risk surgical procedures across Alberta, Saskatchewan, and Ontario; and 22.2% of Canadian women aged 40–49 at average-risk for breast cancer reported having a routine screening mammogram in the past two years. Conclusions The use of potentially unnecessary care appears to be common in Canada. This investigation provides methodology to facilitate future measurement efforts that may incorporate additional jurisdictions and/or unnecessary services.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 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".