Do Hospital Rankings Mislead Patients? Variability Among National Rating Systems for Orthopaedic Surgery
Bibliographic record
Abstract
INTRODUCTION: A growing number of online hospital rating systems for orthopaedic surgery are found. Although the accuracy and consistency of these systems have been questioned in other fields of medicine, no formal analysis of these systems in orthopaedics has been found. METHODS: Five hospital rating systems (US News, HealthGrades, CareChex, Women's Choice, and Hospital Compare) were examined which designate "high-performing" and "low-performing" hospitals for orthopaedic surgery. Descriptive analysis was conducted for all hospitals defined as high- or low-performing in any of the five rating systems, and assessment for agreement/disagreement between ratings was done. A subsample of hospitals ranked by all systems was then created, and agreement between rating systems was investigated using a Cohen's kappa. Each hospital was included in a multinomial logistic regression model investigating which hospital characteristics increased the odds of being favorably/unfavorably rated by each system. RESULTS: One thousand six hundred forty hospitals were evaluated by every rating system. Six hundred thirty-eight unique hospitals were identified as high-performing by at least 1 rating system; however, no hospital was ranked as high-performing by all five rating systems. Four hundred fifty-two unique hospitals were identified as low-performing; however, no hospital was ranked as low-performing by all the three rating systems which define low-performing hospitals. Within the study subsample of hospitals evaluated by each system, little agreement between any combination of rating systems (κ < 0.10) regarding top-tier or bottom-tier performance was found. It was more likely for a hospital to be considered high-performing by one system and low-performing by another (10.66%) than for the majority of the five rating systems to consider a hospital high-performing (3.76%). CONCLUSION: Little agreement between hospital quality rating systems for orthopaedic surgery is found. Publicly available hospital ratings for performance in orthopaedic surgery offer conflicting results and provide little guidance to patients, providers, or payers when selecting a hospital for orthopaedic surgery. LEVEL OF EVIDENCE: Level 1 economic study.
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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 | 0.051 | 0.192 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".