Literature DB >> 1583551

Technology assessment of anesthesia monitors.

N L Pace1.   

Abstract

This essay argues that optimal utilization of anesthesia monitors requires careful technology assessment. This careful assessment is important because monitors may produce spurious or uninterpretable values, or they may damage patients. In addition, resources should be spent only for truly beneficial devices. The types of evidence that this essay describes for use in technology assessment include questions concerning data reliability, data interpretability, and data outcome. Considerable evidence bearing on technology assessment has already been amassed. I propose synthesizing this evidence by meta-analysis. Additional primary studies of technology assessment are also needed.

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Mesh:

Year:  1992        PMID: 1583551     DOI: 10.1007/bf01617435

Source DB:  PubMed          Journal:  J Clin Monit        ISSN: 0748-1977


  28 in total

1.  Failure of lower esophageal contractility to predict patient movement in children anesthetized with halothane and nitrous oxide.

Authors:  M F Watcha; P F White
Journal:  Anesthesiology       Date:  1989-11       Impact factor: 7.892

2.  Anesthesia mortality in perspective.

Authors:  A S Keats
Journal:  Anesth Analg       Date:  1990-08       Impact factor: 5.108

3.  Blood pressure monitoring: automated oscillometric devices.

Authors:  M Ramsey
Journal:  J Clin Monit       Date:  1991-01

Review 4.  Effectiveness research and assessment of clinical outcome: a review of Federal Government and medical community involvement.

Authors:  G D Berman; T E Kottke; D J Ballard
Journal:  Mayo Clin Proc       Date:  1990-05       Impact factor: 7.616

5.  Biases in the assessment of diagnostic tests.

Authors:  C B Begg
Journal:  Stat Med       Date:  1987-06       Impact factor: 2.373

6.  A proposed standard for monitoring equipment: what equipment should be included?

Authors:  F E Block
Journal:  J Clin Monit       Date:  1988-01

7.  A Bayesian method for synthesizing evidence. The Confidence Profile Method.

Authors:  D M Eddy; V Hasselblad; R Shachter
Journal:  Int J Technol Assess Health Care       Date:  1990       Impact factor: 2.188

8.  Selection and evaluation of empirical research in technology assessment.

Authors:  T C Chalmers; P Hewett; D Reitman; H S Sacks
Journal:  Int J Technol Assess Health Care       Date:  1989       Impact factor: 2.188

9.  Medical measurement perils.

Authors:  A D Forbes
Journal:  J Clin Monit       Date:  1988-04

10.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

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