Correlation of Inpatient Experience Survey Items and Domains With Overall Hospital Rating
Bibliographic record
Abstract
OBJECTIVE: To determine which individual patient experience questions and domains were most correlated with overall inpatient hospital experience. METHODS: Within 42 days of discharge, 27 639 patients completed a telephone survey based upon the Hospital-Consumer Assessment of Healthcare Systems and Processes instrument. Patients rated their overall experience on a scale of 0 (worst care) to 10 (best care). Correlation coefficients were calculated to assess the relationships between individual survey questions and domains with overall experience. RESULTS: Questions on provider coordination and nursing care were most correlated with overall experience. Hospital cleanliness, quietness, and discharge information questions showed poor correlation. Correlation with overall experience was strongest for the "communication with nurses" domain. CONCLUSIONS: Our individual question results are novel, while the domain-based findings replicate those of US-based providers, results which had not yet been reported in the Canadian context-one with universal health care coverage. Our results suggest that our large health care organization may attain initial inpatient experience improvements by focusing upon personnel-based initiatives, rather than physical attributes of our hospitals.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".