Indian Health Service: Capping Payment Rates for Nonhospital Services Could Save Millions of Dollars for Contract Health Services
Bibliographic record
Abstract
A letter report issued by the Government Accountability Office with an abstract that begins "The Indian Health Service's (IHS) federal contract health services (CHS) programs primarily paid physicians at their billed charges, which were significantly higher than what Medicare and private insurers would have paid for the same services. IHS's policy states that federal CHS programs should purchase services from contracted providers at negotiated, reduced rates. However, of the almost $63 million that the federal CHS programs paid for physician services provided in 2010, they paid about $51 million (81 percent) to physicians at billed charges and about $12 million (19 percent) to physicians at negotiated, reduced rates. Payments for other types of nonhospital services followed similar trends, with about $40 million out of $52 million (77 percent) paid at billed charges. GAO estimated that IHS's federal CHS programs paid two times as much as what Medicare would have paid and about one and a quarter times as much as what private insurers would have paid for the same physician services provided in 2010. If federal CHS programs had paid Medicare rates for these services, they could have used an estimated $32 million in savings to pay for many of the services that IHS is unable to fund each year. Savings for the overall CHS program may be even higher, as this analysis does not include other types of nonhospital services or the CHS program funding that goes to tribal CHS programs, which the Department of Health and Human Services' (HHS) Office of Inspector General found also paid for nonhospital care above Medicare rates."
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.038 | 0.011 |
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".