The Patient Satisfaction Survey: What does it mean to your bottom line?
Bibliographic record
Abstract
The primary objective of the Affordable Care Act (ACA) is to improve the health care delivery system for all Americans. In April 2011, a reward system initiative for hospitals was announced that focused enhanced reimbursement incentives to hospitals that improved overall care and maintained patient satisfaction. This initiative begins in fiscal year 2013 for Medicare insured patients and is anticipated that private insurers will soon follow this standard.Patient satisfaction has become one of the determinants of health care. Its measures include access, outcome, effectiveness of service provided, and other variables intended to improve population health. Important economic decisions are being influenced with this data. This study explores the impact of the patient satisfaction survey instrument with reimbursement and how this process has influenced care decisions of one large health system in the northeast. It identifies strengths and weaknesses within this health system that have affected the bottom line.Key Words: Patient satisfaction, quality of care, financing, Medicare reimbursement, Hospital Consumer Assessment of Healthcare Providers and Systems, Affordable Care Act, Partnership for Patients
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".