HHS Research Awards: Use of Recovery Act and Patient Protection and Affordable Care Act Funds for Comparative Effectiveness Research
Bibliographic record
Abstract
Correspondence issued by the Government Accountability Office with an abstract that begins "Comparative effectiveness research (CER) is research comparing different interventions and strategies to prevent, diagnose, treat, and monitor health conditions. The American Recovery and Reinvestment Act of 2009 (Recovery Act) appropriated $1.1 billion to the Department of Health and Human Services (HHS) specifically for CER, including $400 million to the Secretary of HHS, $300 million to the Agency for Healthcare Research and Quality (AHRQ), and $400 million to the National Institutes of Health (NIH). The Recovery Act required that these funds be obligated by September 30, 2010. For grants and cooperative agreements, funds are drawn down by recipients on an as-needed basis in accordance with the objectives of the project. For contracts, as milestones are met, invoices are submitted to HHS for payments for goods and services provided under the contract. Additionally, the Patient Protection and Affordable Care Act (PPACA) directed AHRQ to disseminate the findings of CER published by the Patient-Centered Outcomes Research Institute (PCORI) and other related government-funded research in consultation with NIH. PPACA established a trust fund to support PCORI's mission and specified that percentages of this trust fund be provided to the Secretary of HHS and to AHRQ in each of fiscal years 2011 through 2019 for dissemination of CER findings, among other things. Specifically, AHRQ is to receive $8 million in fiscal year 2011 and $24 million in fiscal year 2012, representing 16 percent of the total amount appropriated to this trust fund in each of these fiscal years. Furthermore, the HHS Office of the Secretary is to receive $2 million in fiscal year 2011 and $6 million in fiscal year 2012, representing 4 percent of the total amount appropriated to this trust fund in each fiscal year. In subsequent fiscal years, AHRQ and the HHS Office of the Secretary will receive the same proportions from the trust fund, the total amounts of which will be based on the net revenues from fees on health insurance and self-insured plans, amounts transferred from the Medicare Trust Funds, and appropriations to the PCORI Trust Fund. The Department of Defense and Full-Year Continuing Appropriations Act, 2011 required that we report on HHS's funding of CER under the Recovery Act and PPACA. As required by this act, this report includes information on the expenditures HHS has made using these funds, the entities that have received such funding, and the purpose of the funding."
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 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 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".