Waste Not, Want Not: Promoting Efficient Use of Health Care Resources
Bibliographic record
Abstract
Editorials1 January 2013Waste Not, Want Not: Promoting Efficient Use of Health Care ResourcesAlyna T. Chien, MD, MS and Meredith B. Rosenthal, PhDAlyna T. Chien, MD, MSFrom Harvard Medical School, Boston Children's Hospital, and Harvard School of Public Health, Boston, Massachusetts.Search for more papers by this author and Meredith B. Rosenthal, PhDFrom Harvard Medical School, Boston Children's Hospital, and Harvard School of Public Health, Boston, Massachusetts.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-158-1-201301010-00014 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail The pressure to control health care costs in the United States is at an all-time high. In the governmental sector, Medicare and Medicaid consume approximately one quarter of the federal budget and are growing more rapidly than revenues; the commercial sector is no different (1). Despite these exceptional levels of health care spending, Americans do not live any longer or better than their counterparts in other industrialized countries (2). Indeed, many experts believe that a significant proportion (as much as 30%) of the excess health care spending in the United States generates little or no health benefit. These facts and ...References1. Elmendorf DW. Letter from Douglas W. Elmendorf, Director of the Congressional Budget Office, to Senator Daniel K. Inouye. 5 March 2010. Accessed at www.cbo.gov/sites/default/files/cbofiles/attachments/03-05-apb.pdf on 19 November 2012. Google Scholar2. The Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2011-2012: Economic, Environmental and Social Statistics. Paris, France: OECD Publishing; 2011. Google Scholar3. Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA. 2012;307:1513-6. [PMID: 22419800] CrossrefMedlineGoogle Scholar4. Chernew ME, Mechanic RE, Landon BE, Safran DG. Private-payer innovation in Massachusetts: the ‘alternative quality contract’. Health Aff (Millwood). 2011;30:51-61. [PMID: 21209437] CrossrefMedlineGoogle Scholar5. Prendergast C. The provision of incentives in firms. J Econ Lit. 1999;37:7-63. CrossrefGoogle Scholar6. Shojania KG, Grimshaw JM. Evidence-based quality improvement: the state of the science. Health Aff (Millwood). 2005;24:138-50. [PMID: 15647225] CrossrefMedlineGoogle Scholar7. Tierney WM, Miller ME, McDonald CJ. The effect on test ordering of informing physicians of the charges for outpatient diagnostic tests. N Engl J Med. 1990;322:1499-504. [PMID: 2186274] CrossrefMedlineGoogle Scholar8. Chandra A, Jena AB, Skinner JS. The pragmatist's guide to comparative effectiveness research. J Econ Perspect. 2011;25:27-46. [PMID: 21595324] CrossrefMedlineGoogle Scholar9. Huang ES, Zhang Q, Brown SE, Drum ML, Meltzer DO, Chin MH. The cost-effectiveness of improving diabetes care in U.S. federally qualified community health centers. Health Serv Res. 2007;42:2174-93. [PMID: 17995559] CrossrefMedlineGoogle Scholar10. Hussey PS, Wertheimer S, Mehrotra A. The association between health care quality and cost. A systematic review. Ann Intern Med. 2013;158:27-34. LinkGoogle Scholar11. Weeks WB, Rauh SS, Wadsworth EB, Weinstein JN. The unintended consequences of bundled payments. Ann Intern Med. 2013;158:62-4. LinkGoogle Scholar12. Baker DW, Qaseem A, Reynolds PP, Gardner LA, Schneider EC; American College of Physicians Performance Measurement Committee. Design and use of performance measures to decrease low-value services and achieve cost-conscious care. Ann Intern Med. 2013;158:55-9. LinkGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From Harvard Medical School, Boston Children's Hospital, and Harvard School of Public Health, Boston, Massachusetts.Disclosures: None disclosed. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-2866.Corresponding Author: Alyna T. Chien, MD, MS, Assistant Professor of Pediatrics, Division of General Pediatrics, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115-5737; e-mail, [email protected].Current Author Addresses: Dr. Chien: Assistant Professor of Pediatrics, Division of General Pediatrics, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115-5737.Dr. Rosenthal: Professor of Health Economics and Policy, Department of Health Policy and Management, 677 Huntington Avenue, Kresge Building Room 405, Boston, MA 02115. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoThe Association Between Health Care Quality and Cost Peter S. Hussey , Samuel Wertheimer , and Ateev Mehrotra The Unintended Consequences of Bundled Payments William B. Weeks , Stephen S. Rauh , Eric B. Wadsworth , and James N. Weinstein Metrics Cited byA Randomized Trial of Displaying Paid Price Information on Imaging Study and Procedure Ordering RatesHow Primary Care Physicians Integrate Price Information into Clinical Decision-MakingGiving formulary and drug cost information to providers and impact on medication cost and use: a longitudinal non-randomized studyChoosing WiselyDevelopment of a hospital-based program focused on improving healthcare valueAn Official American Thoracic Society/American Association of Critical-Care Nurses/American College of Chest Physicians/Society of Critical Care Medicine Policy Statement: The Choosing Wisely® Top 5 List in Critical Care Medicine 1 January 2013Volume 158, Issue 1Page: 67-68KeywordsChildrenHealth careHealth care providersHealth care qualityHealth economicsHealth information technologyMotivationPediatricsResearch quality assessmentSystematic reviews ePublished: 1 January 2013 Issue Published: 1 January 2013 Copyright & PermissionsCopyright © 2013 by American College of Physicians. 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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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".