A Framework for Assessing the Value of Diagnostic Imaging in the Era of Comparative Effectiveness Research
Abstract
The key challenge for the imaging community is to develop methods and processes for developing and using outcomes data in a manner that is consistent, transparent, participatory, and fair, and that addresses the unique features of the technology.
In June 2009, the Federal Coordinating Council for Comparative Effectiveness Research submitted a report to the President and Congress in which the Council described the purpose of comparative effectiveness research (CER) as developing evidence-based information for interventions and determining under what circumstances an intervention is effective (1). With the enactment of the Patient Protection and Affordable Care Act, a Patient-centered Outcomes Research Institute (PCORI) was established to assist decision makers in making evidence-based health decisions through synthesis and dissemination of clinical CER of health interventions (2). Its founding has underscored a heightened need for health policy makers to consider the impact of health care technologies on final outcomes of interest—for example, functional status, quality of life, disability, major clinical events, and mortality (3–5).
© RSNA, 2011
References
- 1 . Report to the President and Congress. U.S. Department of Health and Human Services. http://www.hhs.gov/recovery/programs/cer/cerannualrpt.pdf. Published 2009. Accessed March 31, 2010. Google Scholar
- 2 . Summary of Patient-Centered Outcomes Research Provisions. Association of American Medical Colleges. https://www.aamc.org/download/131994/data/pcorsummary04022010.pdf. Published 2010. Accessed September 13, 2010. Google Scholar
- 3 . Legislating against use of cost-effectiveness information. N Engl J Med 2010;363(16):1495–1497. Crossref, Medline, Google Scholar
- 4 . US healthcare reform: implications for health economics and outcomes research. Expert Rev Pharmacoecon Outcomes Res 2010;10(3):215–216. Crossref, Medline, Google Scholar
- 5 . Medicare and medical technology—the growing demand for relevant outcomes. N Engl J Med 2010;362(5):377–379. Crossref, Medline, Google Scholar
- 6 . Evaluation of computed tomography: achievement and challenge. AJR Am J Roentgenol 1978;131(1):1–4. Crossref, Medline, Google Scholar
- 7 . Computerized cranial tomography. Effect on diagnostic and therapeutic plans. JAMA 1977;238(3):224–227. Crossref, Medline, Google Scholar
- 8 . The efficacy of diagnostic imaging. Med Decis Making 1991;11(2):88–94. Crossref, Medline, Google Scholar
- 9 . Proposals for a phased evaluation of medical tests. Med Decis Making 2009;29(5):E13–E21. Crossref, Medline, Google Scholar
- 10 . Assessing the comparative effectiveness of a diagnostic technology: CT colonography. Health Aff (Millwood) 2008;27(6):1503–1514. Crossref, Medline, Google Scholar
- 11 . Technology assessment in radiology: putting the evidence in evidence-based radiology. Radiology 2007;244(1):31–38. Link, Google Scholar
- 12 . Understanding the medical and nonmedical value of diagnostic testing. Value Health 2010;13(2):310–314. Crossref, Medline, Google Scholar
- 13 . The new technology assessment. N Engl J Med 1990;323(10):673–677. Crossref, Medline, Google Scholar
- 14 . Economic evaluation in radiology: reviewing the literature and examples in oncology. Acad Radiol 2010;17(9):1090–1095. Crossref, Medline, Google Scholar
- 15 . Economic evaluation for devices and drugs—same or different? Value Health 2009;12(4):402–404. Crossref, Medline, Google Scholar
- 16 . Does Medicare have an implicit cost-effectiveness threshold? Med Decis Making 2010;30(4):E14–E27. Crossref, Medline, Google Scholar
- 17 . Principles of good practice for budget impact analysis: report of the ISPOR Task Force on good research practices—budget impact analysis. Value Health 2007;10(5):336–347. Crossref, Medline, Google Scholar
- 18 . Survival of patients with stage I lung cancer detected on CT screening. N Engl J Med 2006;355(17):1763–1771. Crossref, Medline, Google Scholar
- 19 . Computed tomography screening and lung cancer outcomes. JAMA 2007;297(9):953–961. Crossref, Medline, Google Scholar
- 20 . Lung cancer trial results show mortality benefit with low-dose CT: Twenty percent fewer lung cancer deaths seen among those who were screened with low-dose spiral CT than with chest X-ray. National Cancer Institute. http://www.cancer.gov/newscenter/pressreleases/NLSTresultsRelease. Published 2010. Accessed November 30, 2010. Google Scholar
- 21 . Using cost-effectiveness analysis to improve health care: opportunities and barriers. New York, NY: Oxford University Press, 2005. Google Scholar
- 22 . Colorectal cancer screening rates still fall far short of recommended levels. JAMA 2008;299(6):622. Crossref, Medline, Google Scholar
- 23 . CT colonography to screen for colorectal cancer and aortic aneurysm in the Medicare population: cost-effectiveness analysis. AJR Am J Roentgenol 2009;192(5):1332–1340. Crossref, Medline, Google Scholar
- 24 . Cost-effectiveness of computed tomographic colonography screening for colorectal cancer in the medicare population. J Natl Cancer Inst 2010;102(16):1238–1252. Crossref, Medline, Google Scholar
- 25
Centers for Medicare and Medicaid Services . Decision memo for screening computed tomographic colonography (CTC) for colorectal cancer (CAG-00396N). Centers for Medicare and Medicaid Services. http://www.cms.gov/mcd/viewdecisionmemo.asp?from2=viewdecisionmemo.asp&id=220&. Published 2009. Accessed July 27, 2010. Google Scholar - 26 . CMS’s landmark decision on CT colonography—examining the relevant data. N Engl J Med 2009;360(26):2699–2701. Crossref, Medline, Google Scholar
- 27 . Cancer statistics, 2009. CA Cancer J Clin 2009;59(4):225–249. Crossref, Medline, Google Scholar
- 28 . Decision memo for positron emission tomography (FDG) for cervical cancer (CAG-00181R2). Centers for Medicare and Medicaid Services. http://www.cms.gov/mcd/viewnca.asp?from=basket&where=&what=&nca_id=232&basket=nca:00181R2:232:Positron+Emission+Tomography+%28FDG%29+for+Cervical+Cancer:Closed:2nd+Recon:13. Published 2009. Accessed July 28, 2010. Google Scholar
- 29 . The role of 18F-FDG PET in assessing therapy response in cancer of the cervix and ovaries. J Nucl Med 2009;50(Suppl 1):64S–73S. Crossref, Medline, Google Scholar
Article History
Received February 3, 2011; revision requested March 11; revision received May 26; accepted June 17; final version accepted August 2. Supported by GE Healthcare.Published online: Dec 2011
Published in print: Dec 2011