Geographic Disparities in the Surgical Management of Hemifacial Spasm in Canada
Bibliographic record
Abstract
BACKGROUND: We aimed to interrogate the Canadian Institute for Health Information (CIHI) database in order to determine the geographic distribution and outcomes of microvascular decompression (MVD) for the treatment of hemifacial spasm (HFS). METHODS: The CIHI database was searched from 2004 to 2017 for relevant diagnostic and procedure codes. A new database was populated with the following categories: year, institution, province, number of interventions per year, and mean length of stay. Descriptive statistics were generated. Provincial utilization rates of MVD for HFS were calculated. RESULTS: During the period 2004-17, we identified 671 MVDs performed for HFS at 20 centers across Canada. During the study period, 286 MVDs (42.6%) were performed at one center in Manitoba. Another 131 (19.5%) and 72 (10.7%) were performed at one center in British Columbia and Ontario, respectively. The remaining 182 (27.1%) MVDs for HFS were performed at 17 centers across the rest of Canada where the mean number of cases performed per year was 1.1 (SD=0.9, range 0.2-2.9). When out-of-province cases were re-allocated to place of residence, the adjusted provincial utilization of MVD for HFS ranged between 0.5 and 6.1 patients per million per year. CONCLUSIONS: Microvascular decompression for HFS is performed relatively rarely and there is a tremendous geographic variation in utilization across Canada. Although most of these surgeries are performed by a few surgeons, more than half of Canadian centers perform an average of less than 1 case per year. Further examination of the impact of these discrepancies appears warranted.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".