Patient Perceptions of Private Cataract Surgery in Ontario
Bibliographic record
Abstract
Prolonged wait times for elective procedures have led to the integration of private healthcare options into the Canadian healthcare system, with current legislation signalling further expansion. This study aimed to assess patient perspectives on being offered private cataract surgery options through a standardized telephone script, as well as patient attitudes towards the role of private healthcare options in cataract surgery and in general. This quality improvement study employed a survey-based approach, conducting both telephone and in-person questionnaires to patients referred for cataract surgery at the Ivey Eye Institute, London, Ontario. Patients with upcoming cataract consultations were contacted using a standardized telephone script on public and private cataract surgery options and later surveyed. Simultaneously, patients attending their consultations were surveyed in person. Chi-square tests and descriptive statistics were used for data analysis. Sixty-nine patients completed the surveys—20 via phone and 49 in person. Most phone respondents (95%) felt no pressure to choose private options, and all agreed it was appropriate to be informed. Overall, 66.7% of respondents supported private cataract surgery options, and 65.2% supported a role for private healthcare in general. No demographic factors were significantly associated with perceptions of private healthcare. Participants responded positively to the telephone script and showed general support for private options, demonstrating the need for additional research to ensure healthcare policy aligns with patient preferences. To our knowledge, this is the first study to examine patient perspectives on private healthcare within Canada.
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.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".