Evidence-based risk assessment in noninvasive imaging

L. J. Shaw, A. E. Iskandrian, R. Hachamovitch, G. Germano, H. C. Lewin, T. M. Bateman, D. S. Berman

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Assessment of important clinical and economic outcomes has become central to the evaluation of patient care. Outcome research is deeply rooted in epidemiology, including the use of multivariable, risk-adjusted regression analysis. In our current health care environment, these methods are increasingly being used to assess the quality of care and to profile physicians and laboratories. Nuclear medicine physicians therefore need to better understand outcome methodologies in order to evaluate patient outcomes, develop guidelines, and decide on patient management. Methods: This review describes the methods of assessing the diagnostic and prognostic value of nuclear medicine techniques and, briefly, the methodologic limitations of sample size, frequency and type of events, and follow-up periods and the incremental value of imaging. Also described are logistic regression and Cox proportional hazards modeling. Models for risk assessment are designed to identify whether patients require conservative (i.e., low-risk) or aggressive (i.e., high-risk) treatment. Treatment selection is currently based on risk assessment and the formation of an integrated, empiric risk stratification algorithm of care. This review also includes the methods of assessing economic effectiveness and quality-of-life issues for patients examined with nuclear medicine techniques. Conclusion: In this era of constrained resources, low-cost outpatient-based care may be of increasing importance. High-quality evidence of the clinical and economic outcome of nuclear imaging is essential for helping health care providers and payers assess its value.

Original languageEnglish
Pages (from-to)1424-1436
Number of pages13
JournalJournal of Nuclear Medicine
Volume42
Issue number9
StatePublished - 2001
Externally publishedYes

Keywords

  • Cost-effectiveness
  • Prognosis outcomes
  • Quality of life
  • Risk stratification

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