Revenue in U.S. hospital based outpatient wound centers: Implications for creating accountable care organizations
Bibliographic record
Abstract
Background: One of the experimental health care payment and delivery programs proposed under the auspices of the U.S. Center for Medicare and Medicaid Innovation is the Accountable Care Organization (ACO). An example of this is the physician hospital organization (PHO), an association of one or more hospitals and a group of physicians which would “bundle” their payments for an episode of care. However, as potential PHO members consider such joint ventures, they require real-world revenue data from which to determine the relative contribution of the physician and the facility to the collective bill in order to make decisions about the contract structure. In the past, physicians and hospitals have not shared cost and charge data with each other. Methods: Using sophisticated electronic medical record software, real-world billing data were obtained from 3 hospital-based outpatient wound centers and the physicians practicing in them (1 full time equivalent each) in order to establish the relative contribution of each entity to a potential PHO. Results: A total of 6,762 patient visits occurred, comprising 887 initial consultations and 5,875 follow-up visits. Based upon Medicare-allowable reimbursement rates, mean physician revenues represented approximately one quarter of total revenue while procedures provided almost three quarters of the global revenue, on average. Conclusions: Among hospital-based wound centers our results confirm that procedures represent the majority of revenue for both the facility and the physician. Our results represent a starting point for hospitals and physicians to negotiate bundled payments as they attempt to transition to a value- and quality-based model of care. A sophisticated EHR designed specifically for the purpose of capturing charge data, provides the mechanism for future cost effectiveness studies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".