Medicare Beneficiaries’ Perspectives on the Quality of Hospital Care and Their Implications for Value-Based Payment
Bibliographic record
Abstract
Importance: Medicare's Hospital Value-Based Purchasing (HVBP) program adjusts hospital payments according to performance on 4 equally weighted quality domains: clinical outcomes, safety, patient experience, and efficiency. The assumption that performance on each domain is equally important may not reflect the preferences of Medicare beneficiaries. Objective: To estimate the relative importance (ie, weight) of the 4 quality domains in the HVBP program from the perspective of Medicare beneficiaries and the impact of using beneficiary value weights on incentive payments for hospitals enrolled in fiscal year 2019. Design, Setting, and Participants: An online survey was conducted in March 2022. A nationally representative sample of Medicare beneficiaries was recruited through Ipsos KnowledgePanel. Value weights were estimated using a discrete choice experiment that asked respondents to choose between 2 hospitals and indicate which they preferred. Hospitals were described using 6 attributes, including (1) clinical outcomes, (2) patient experience, (3) safety, (4) Medicare spending per patient, (5) distance, and (6) out-of-pocket cost. Data analysis was performed from April to November 2022. Main Outcomes and Measures: An effects-coded mixed logit regression model was used to estimate the relative importance of quality domains. HVBP program performance was linked to Medicare payment data in the Medicare Inpatient Hospitals by Provider and Service data set and hospital characteristics from the American Hospital Association Annual Survey data set, and the estimated impact of using beneficiary value weights on hospital payments was estimated. Results: A total of 1025 Medicare beneficiaries (518 women [51%]; 879 individuals [86%] aged ≥65 years; 717 White individuals [70%]) responded to the survey. A hospital's performance on clinical outcomes was most highly valued by beneficiaries (49%), followed by safety (22%), patient experience (21%), and efficiency (8%). Nearly twice as many hospitals would see a payment reduction when using beneficiary value weights than would see an increase (1830 vs 922 hospitals); however, the average net decrease was smaller (mean [SD], -$46 978 [$71 211]; median [IQR], -$24 628 [-$53 507 to -$9562]) than the comparable increase (mean [SD], $93 243 [$190 654]; median [IQR], $35 358 [$9906 to $97 348]). Hospitals seeing a net reduction with beneficiary value weights were more likely to be smaller, lower volume, nonteaching, and non-safety-net hospitals located in more deprived areas that served less complex patients. Conclusions and Relevance: This survey study of Medicare beneficiaries found that current HVBP program value weights do not reflect beneficiary preferences, suggesting that the use of beneficiary value weights may exacerbate disparities by rewarding larger, high-volume 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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".