Importance of Pricing for Hospitals’ Expenses from Financial and Social Perspectives
Bibliographic record
Abstract
This paper analyzes the importance of health care services’ charging applied by hospitals in USA. The subject is examined from financial and sociological perspective. In the first step, US hospitals’ situation is described. After that, a comprehensive literature review on Pricing Theories is presented. In the next step, problems of health care sector are investigated from a sociological perspective. In the third part of the study, pricing applications of hospitals in USA are considered. The paper has shown that strong positioned interest groups in the US health care sector pay much less than the weak positioned. As a result of weak positioning 1.7 million people in 2014 filed for bankruptcy and 35 million people were contacted by agencies for uncovered bills. Furthermore, more than 15 million people spent all their savings to cover medical bills. On the other side, 1.1 trillion USD is spent by US federal and governmental states on health issues. Moreover, hospitals are complaining about underpayment. As a solution proposal to this problem, all actors in U.S. health sector must come together to find solutions to pricing of health care services and regulations required for better organization.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".