Hospital satisfaction does not predict functional outcome one year after total shoulder arthroplasty
Bibliographic record
Abstract
Background: Healthcare is shifting to value-based payment models. Two percent of Medicare reimbursements are currently linked to value measures including the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) hospital satisfaction survey. The purpose of this study was to determine if HCAHPS survey results are correlated with validated legacy outcome measures after total shoulder arthroplasty. Methods: A prospective observational study was conducted in 84 patients undergoing elective total shoulder arthroplasty. Baseline 12-item Short-Form Health Survey (SF-12), American Shoulder and Elbow Surgeons (ASES), and Western Ontario Osteoarthritis of the Shoulder Index (WOOS) questionnaires were completed at the time of enrollment. ASES and WOOS scores were collected at 3-month and 1-year post-operatively. Patients were contacted to complete the HCAHPS survey postoperatively. HCAHPS results and baseline functional scores were evaluated for an association with improvements in legacy outcome measures after surgery. Results: HCAHPS scores were higher among males than females (P=0.04). Age, SF-12 physical component scores, SF-12 mental component scores, and pre-operative symptom severity were not associated with HCAHPS results. HCAHPS scores were not correlated with ASES (r=0.09, P=0.44) or WOOS scores (r=−0.17, P=0.13) at one year after surgery. HCAHPS was also not correlated with the absolute improvement in ASES (r=−0.02, P=0.85) or WOOS scores (r=−0.08, P=0.48) from pre- to one year post-operatively. Conclusions: The HCAHPS score, a measure of satisfaction and a determinant of Medicare quality-based reimbursement, showed no correlation with functional outcome measures at one year after total shoulder arthroplasty. Thus, HCAHPS patient satisfaction survey may not be aligned with functional outcomes valued by patients. Further consideration is warranted regarding the assessment of quality, and in turn reimbursements, with survey results.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".