Literature DB >> 1563415

Technology assessment--an American view.

J R Thornbury1, D G Fryback.   

Abstract

Technology assessment of an imaging method such as magnetic resonance (MR) is a complicated concept that includes aspects of epidemiology, biostatistics, clinical efficacy determination, outcomes assessment, and knowledge of the technical and medical bases of the imaging method under study. To enhance understanding of the interrelations of the different aspects of technology assessment, a hierarchical model is proposed. This extends from the basic imaging physics domain through clinical applications in diagnosis and treatment decisions to patient outcomes and ultimately societal considerations. This overview paper presents the conceptual continuum of the hierarchical model, and then describes the interrelationships among efficacy, cost effectiveness, and outcomes research as components embedded within the context of technology assessment. It also points out how scientific quality of research in MR imaging assessment can be enhanced through improved research design that takes into account basic concepts of the model.

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Year:  1992        PMID: 1563415     DOI: 10.1016/0720-048x(92)90228-2

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  3 in total

1.  Comments on "MRI of the tectorial and posterior atlanto-occipital membranes in the late stage of whiplash injury" ( Neuroradiology, 2003, 45:585-591).

Authors:  Eivind Pape
Journal:  Neuroradiology       Date:  2004-05-05       Impact factor: 2.804

2.  Optimizing the use of expert panel reference diagnoses in diagnostic studies of multidimensional syndromes.

Authors:  Ron L H Handels; Claire A G Wolfs; Pauline Aalten; Patrick M M Bossuyt; Manuela A Joore; Albert F G Leentjens; Johan L Severens; Frans R J Verhey
Journal:  BMC Neurol       Date:  2014-10-04       Impact factor: 2.474

Review 3.  Effectiveness of Practices to Support Appropriate Laboratory Test Utilization: A Laboratory Medicine Best Practices Systematic Review and Meta-Analysis.

Authors:  Matthew Rubinstein; Robert Hirsch; Kakali Bandyopadhyay; Bereneice Madison; Thomas Taylor; Anne Ranne; Millie Linville; Keri Donaldson; Felicitas Lacbawan; Nancy Cornish
Journal:  Am J Clin Pathol       Date:  2018-02-17       Impact factor: 2.493

  3 in total

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