Patients’ cancer care perceptions conceptualized through the Cancer Experience Measurement Framework
Bibliographic record
Abstract
BACKGROUND: Research on patients' perceptions of cancer care often documents sub-optimal experiences. Cancer care quality issues include restricted service access, lack of care coordination, gaps in follow-up and "generic" rather than person-centered care. Recent reports underscore that proactively and periodically seeking user feedback is crucial for timely care quality improvement. The present study aimed to analyze and thematically organize a large amount of feedback from patients who had been treated for cancer within the last 6 months. METHODS: Randomly selected participants (N = 3,278) from 3 University-affiliated cancer centres in Montreal, Quebec, Canada completed the Ambulatory Oncology Patient Satisfaction Survey (AOPSS) and an open-ended question on their perceptions of the care they received. 692 participants responded to the latter. Guided by the Cancer Experience Measurement Framework (CEMF), their feedback was analyzed using a qualitative thematic approach. RESULTS: Cancer care perceptions included sub-themes of care access and coordination, continuity/transition, and perceived appropriateness/personalisation of care. The most salient theme was captured by care access and coordination with 284 comments (44%) directly addressing these issues. The ways in which health care services were structured including setting, schedule, and location were often raised as cause for concerns. Issues surrounding cancer information/education, emotional support, and physical comfort were frequently reported as unmet needs. In addition, limited access to cancer services led patients to seek alternatives such as going to emergency departments and/or private care. CONCLUSIONS: These findings are timely as they show that most patients are well aware of quality issues in cancer care and are willing to report candidly on these. Patient feedback also underscore the importance for cancer care institutions to periodically gather patient-reported data so that systems can re-calibrate their service offerings according to these data. Ultimately, patient reports will translate into enhanced quality, personalization, and safer cancer care provision.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".