Waste Not, Want Not: Promoting Efficient Use of Health Care Resources
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Résumé
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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Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».