Is quality important to our patients? The relationship between surgical outcomes and patient satisfaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: With greater transparency in health system reporting and increased reliance on patient-centred outcomes, patient satisfaction has become a priority in delivering quality care. We sought to explore the relationship between patient satisfaction and short-term outcomes in patients undergoing general surgical procedures. METHODS: Satisfaction surveys were distributed to patients following discharge from the general surgery service at an academic hospital between June 2012 and March 2015. Short-term clinical outcomes were obtained from the American College of Surgeons National Surgical Quality Improvement Program database. Patients rated their level of satisfaction on a 5-point Likert scale, and ordered logistic regression model was used to determine predictors of high patient satisfaction. RESULTS: 757 patient satisfaction surveys were completed. The mean age of patients surveyed was 52.2 years; 60.0% of patients were female. The majority of patients underwent a laparoscopic procedure (85.9%) and were admitted as inpatients following surgery (72%). 91.5% of patients rated satisfaction of 4-5, and 95.0% said they would recommend the service. The odds of overall satisfaction were lower in patients who had complications (OR: 0.52, 95% CI 0.31 to 0.87) and 30-day readmission (OR: 0.35, 95% CI 0.17 to 0.70). Having elective surgery was associated with higher odds of satisfaction (OR: 1.62, 95% CI 1.07 to 2.47). CONCLUSIONS: We found a significant association between patient satisfaction and both 30-day readmission and the occurrence of postoperative surgical complications. Given this association, further study is warranted to evaluate patient satisfaction as a healthcare quality indicator.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it