The use of error and uncertainty methods in the medical laboratory


Oosterhuis W. P., Bayat H., Armbruster D., COŞKUN A., Freeman K. P., Kallner A., ...Daha Fazla

CLINICAL CHEMISTRY AND LABORATORY MEDICINE, cilt.56, sa.2, ss.209-219, 2018 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 56 Sayı: 2
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1515/cclm-2017-0341
  • Dergi Adı: CLINICAL CHEMISTRY AND LABORATORY MEDICINE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.209-219
  • Anahtar Kelimeler: measurement uncertainty, performance specification, quality control, total error, EXTERNAL QUALITY ASSESSMENT, VS. MEASUREMENT UNCERTAINTY, CLINICAL-CHEMISTRY, ANALYTICAL GOALS, ANALYTICAL PERFORMANCE, PERMISSIBLE LIMITS, SIGMA SCALE, IMPRECISION, PRECISION, TRUENESS
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Evet

Özet

Error methods - compared with uncertainty methods - offer simpler, more intuitive and practical procedures for calculating measurement uncertainty and conducting quality assurance in laboratory medicine. However, uncertainty methods are preferred in other fields of science as reflected by the guide to the expression of uncertainty in measurement. When laboratory results are used for supporting medical diagnoses, the total uncertainty consists only partially of analytical variation. Biological variation, pre- and postanalytical variation all need to be included. Furthermore, all components of the measuring procedure need to be taken into account. Performance specifications for diagnostic tests should include the diagnostic uncertainty of the entire testing process. Uncertainty methods may be particularly useful for this purpose but have yet to show their strength in laboratory medicine. The purpose of this paper is to elucidate the pros and cons of error and uncertainty methods as groundwork for future consensus on their use in practical performance specifications. Error and uncertainty methods are complementary when evaluating measurement data.