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Rutter CM, Knudsen AB, Pandharipande PV. Computer disease simulation models: integrating evidence for health policy. Acad Radiol. 2011;18(9):1077-86doi: 10.1016/j.acra.2011.02.004.
Rutter, C. M., Knudsen, A. B., & Pandharipande, P. V. (2011). Computer disease simulation models: integrating evidence for health policy. Academic radiology, 18(9), 1077-86. https://doi.org/10.1016/j.acra.2011.02.004
Rutter, Carolyn M, et al. "Computer disease simulation models: integrating evidence for health policy." Academic radiology vol. 18,9 (2011): 1077-86. doi: https://doi.org/10.1016/j.acra.2011.02.004
Rutter CM, Knudsen AB, Pandharipande PV. Computer disease simulation models: integrating evidence for health policy. Acad Radiol. 2011 Sep;18(9):1077-86. doi: 10.1016/j.acra.2011.02.004. Epub 2011 Mar 23. PMID: 21435924; PMCID: PMC3125421.
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Acad Radiol. 2011 Sep;18(9):1077-86. doi: 10.1016/j.acra.2011.02.004. Epub 2011 Mar 23.

Computer disease simulation models: integrating evidence for health policy.

Academic radiology

Carolyn M Rutter, Amy B Knudsen, Pari V Pandharipande

Affiliations

  1. Biostatistics Unit, Group Health Research Institute, Seattle, WA 98101, USA. [email protected]

PMID: 21435924 PMCID: PMC3125421 DOI: 10.1016/j.acra.2011.02.004

Abstract

Computer disease simulation models are increasingly being used to evaluate and inform health care decisions across medical disciplines. The aim of researchers who develop these models is to integrate and synthesize short-term outcomes and results from multiple sources to predict the long-term clinical outcomes and costs of different health care strategies. Policy makers, in turn, can use the predictions generated by disease models together with other evidence to make decisions related to health care practices and resource utilization. Models are particularly useful when the existing evidence does not yield obvious answers or does not provide answers to the questions of greatest interest, such as questions about the relative cost-effectiveness of different practices. This review focuses on models used to inform decisions about imaging technology, discussing the role of disease models for health policy development and providing a foundation for understanding the basic principles of disease modeling. This manuscript draws from the collective computed tomographic colonography modeling experience, reviewing 10 published investigations of the clinical effectiveness and cost-effectiveness of computed tomographic colonography relative to colonoscopy. The discussion focuses on implications of different modeling assumptions and difficulties that may be encountered when evaluating the quality of models. This underscores the importance of forging stronger collaborations between researchers who develop disease models and radiologists, to ensure that policy-level models accurately represent the experience of everyday clinical practices.

Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.

References

  1. Radiology. 2009 Dec;253(3):745-52 - PubMed
  2. Stat Med. 2010 Aug 30;29(19):1985-8; discussion 1996-7 - PubMed
  3. Obstet Gynecol. 2009 Apr;113(4):775-782 - PubMed
  4. Aliment Pharmacol Ther. 2008 Feb 15;27(4):366-74 - PubMed
  5. Br J Surg. 2002 Jul;89(7):845-60 - PubMed
  6. Am J Gastroenterol. 1999 Aug;94(8):2268-74 - PubMed
  7. J Natl Cancer Inst. 2006 Jun 7;98(11):774-82 - PubMed
  8. N Engl J Med. 2008 Sep 18;359(12):1207-17 - PubMed
  9. Value Health. 2009 Nov-Dec;12(8):1044-52 - PubMed
  10. Dig Liver Dis. 2007 Mar;39(3):242-50 - PubMed
  11. Health Aff (Millwood). 2010 Oct;29(10):1826-33 - PubMed
  12. N Engl J Med. 2005 Oct 27;353(17):1773-83 - PubMed
  13. Ann Intern Med. 2008 Jan 1;148(1):1-10 - PubMed
  14. Radiology. 2009 Dec;253(3):641-51 - PubMed
  15. Cancer Causes Control. 2008 Mar;19(2):175-81 - PubMed
  16. Clin Gastroenterol Hepatol. 2004 Jul;2(7):554-63 - PubMed
  17. Med Decis Making. 1983;3(4):419-458 - PubMed
  18. Ann Intern Med. 2000 Oct 17;133(8):573-84 - PubMed
  19. Arch Intern Med. 2008 Apr 14;168(7):696-705 - PubMed
  20. Stat Med. 2007 Jan 15;26(1):98-109 - PubMed
  21. Ann Intern Med. 2009 Nov 17;151(10):738-47 - PubMed
  22. J Natl Cancer Inst. 2010 May 19;102(10):722-31 - PubMed
  23. J Natl Cancer Inst. 2009 Mar 18;101(6):374-83 - PubMed
  24. Radiology. 2009 Feb;250(2):488-97 - PubMed
  25. Int J Cancer. 2009 Mar 1;124(5):1161-8 - PubMed
  26. Radiology. 2010 Mar;254(3):793-800 - PubMed
  27. Med Decis Making. 2011 Jan-Feb;31(1):10-8 - PubMed
  28. Value Health. 2009 Nov-Dec;12(8):1053-61 - PubMed
  29. Stat Med. 2010 Aug 30;29(19):1977-81; discussion 1996-7 - PubMed
  30. Cancer. 1975 Dec;36(6):2251-70 - PubMed
  31. Ann Intern Med. 2008 Nov 4;149(9):659-69 - PubMed
  32. JAMA. 1996 Oct 16;276(15):1253-8 - PubMed
  33. Appl Health Econ Health Policy. 2010;8(3):141-54 - PubMed
  34. Am J Gastroenterol. 2007 Feb;102(2):380-90 - PubMed
  35. CA Cancer J Clin. 2010 Sep-Oct;60(5):277-300 - PubMed
  36. Ann Intern Med. 2008 Nov 4;149(9):638-58 - PubMed
  37. JACC Cardiovasc Imaging. 2008 May;1(3):398-403 - PubMed
  38. Radiology. 2008 Jul;248(1):278-87 - PubMed
  39. Cancer. 2007 Jun 1;109(11):2213-21 - PubMed
  40. CMAJ. 2010 Sep 7;182(12):1307-13 - PubMed
  41. Gastroenterology. 2005 Oct;129(4):1151-62 - PubMed
  42. N Engl J Med. 1977 Mar 31;296(13):716-21 - PubMed
  43. Med Decis Making. 2010 Jul-Aug;30(4):474-83 - PubMed
  44. Med Decis Making. 1997 Apr-Jun;17(2):123-5 - PubMed
  45. Value Health. 2009 Nov-Dec;12(8):1062-73 - PubMed
  46. CMAJ. 2005 Oct 11;173(8):877-81 - PubMed
  47. N Engl J Med. 2005 Oct 27;353(17):1784-92 - PubMed
  48. J Natl Cancer Inst. 2010 Aug 18;102(16):1238-52 - PubMed
  49. Pharmacoeconomics. 2006;24(11):1055-68 - PubMed
  50. Ann Intern Med. 2010 Sep 21;153(6):368-77 - PubMed
  51. AJR Am J Roentgenol. 2009 May;192(5):1332-40 - PubMed
  52. Cancer Epidemiol Biomarkers Prev. 2010 Aug;19(8):1992-2002 - PubMed
  53. Gastroenterol Clin North Am. 2007 Dec;36(4):947-68, viii - PubMed

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