The impact of Maryland’s payment reforms on hospital community benefit efforts
Bibliographic record
Abstract
BACKGROUND: In 2014, Maryland established a global budget policy for all hospitals in the state. Under this policy, hospitals are incentivized to not only provide clinical care services to individual patients but also address the health needs of their broader patient population through prevention efforts and investment in the upstream social and economic factors that determine health. PURPOSE: To better understand the incentives created for hospitals under this policy, our study assessed whether the implementation of global budgets changed the levels and patterns of Maryland hospitals' investments in community benefits. APPROACH: Data on hospital community benefit spending from the Internal Revenue Service Form 990 Schedule H for the years 2010-2016 were utilized for this study. RESULTS: We found that Maryland hospitals' total spending on community benefits decreased under the global budget policy. Unlike hospitals in similar states without a global budget policy, Maryland hospitals did not experience any increases in Medicaid shortfalls between 2014 and 2016. Although Maryland hospitals provided more subsidized health services, their investment in broader community health improvement activities remained unchanged. CONCLUSION: Our analysis suggests that Maryland hospitals have shifted strategies because of the implementation of the global budget policy. The ability to report community benefit in a way that accurately considers the context and constraints of a state's policies would provide hospitals better means of communicating these efforts to stakeholders. PRACTICE IMPLICATIONS: Our results suggest that global budgets impact the levels and patterns of hospitals' community benefit investments.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".