Annals of Laboratory Medicine

Korean Society for Laboratory Medicine (대한진단검사의학회)
권호 표지
DOI QR코드

DOI QR Code

New Decision Criteria for Selecting Delta Check Methods Based on the Ratio of the Delta Difference to the Width of the Reference Range Can Be Generally Applicable for Each Clinical Chemistry Test Item

  • Park, Sang Hyuk (Department of Laboratory Medicine, Asan Medical Center and University of Ulsan College of Medicine) ;
  • Kim, So-Young (Department of Laboratory Medicine, Asan Medical Center and University of Ulsan College of Medicine) ;
  • Lee, Woochang (Department of Laboratory Medicine, Asan Medical Center and University of Ulsan College of Medicine) ;
  • Chun, Sail (Department of Laboratory Medicine, Asan Medical Center and University of Ulsan College of Medicine) ;
  • Min, Won-Ki (Department of Laboratory Medicine, Asan Medical Center and University of Ulsan College of Medicine)
  • Published : 2012.09.01
⟨ Previous Next ⟩

Abstract

Background: Many laboratories use 4 delta check methods: delta difference, delta percent change, rate difference, and rate percent change. However, guidelines regarding decision criteria for selecting delta check methods have not yet been provided. We present new decision criteria for selecting delta check methods for each clinical chemistry test item. Methods: We collected 811,920 and 669,750 paired (present and previous) test results for 27 clinical chemistry test items from inpatients and outpatients, respectively. We devised new decision criteria for the selection of delta check methods based on the ratio of the delta difference to the width of the reference range (DD/RR). Delta check methods based on these criteria were compared with those based on the CV% of the absolute delta difference (ADD) as well as those reported in 2 previous studies. Results: The delta check methods suggested by new decision criteria based on the DD/RR ratio corresponded well with those based on the CV% of the ADD except for only 2 items each in inpatients and outpatients. Delta check methods based on the DD/RR ratio also corresponded with those suggested in the 2 previous studies, except for 1 and 7 items in inpatients and outpatients, respectively. Conclusions: The DD/RR method appears to yield more feasible and intuitive selection criteria and can easily explain changes in the results by reflecting both the biological variation of the test item and the clinical characteristics of patients in each laboratory. We suggest this as a measure to determine delta check methods.

Keywords

References

  1. Whitehurst P, Di Silvio TV, Boyadjian G. Evaluation of discrepancies in patients' results--an aspect of computer-assisted quality control. Clin Chem 1975;21:87-92.
  2. Ladenson JH. Patients as their own controls: use of the computer to identify "laboratory error." Clin Chem 1975;21:1648-53.
  3. Wheeler LA and Sheiner LB. Delta check tables for the Technicon SMA 6 continuous-flow analyzer. Clin Chem 1977;23:216-9.
  4. Sheiner LB, Wheeler LA, Moore JK. The performance of delta check methods. Clin Chem 1979;25:2034-7.
  5. Nosanchuk JS and Gottmann AW. CUMS and delta checks. A systematic approach to quality control. Am J Clin Pathol 1974;62:707-12. https://doi.org/10.1093/ajcp/62.5.707
  6. Wheeler LA and Sheiner LB. A clinical evaluation of various delta check methods. Clin Chem 1981;27:5-9.
  7. Lee DH, Kim JQ, Oh WI, Min WK, Kim SI. Evaluation of the results in clinical chemistry using delta and panic value check. Korean J Lab Med 1988;8:237-50.
  8. Kim JW, Kim JQ, Kim SI. Differential application of rate and delta check on selected clinical chemistry tests. J Korean Med Sci 1990;5:189-95. https://doi.org/10.3346/jkms.1990.5.4.189
  9. Lacher DA and Connelly DP. Rate and delta checks compared for selected chemistry tests. Clin Chem 1988;34:1966-70.
  10. Min WK and Lee JO. The development of online delta check system using the workstation. J Clin Pathol Qual Control 1996;18:133-42. (Available at the website http://lab-qa.org/sub/catalog.php?boardid=board_journal&mode=view&no=479&start=310&val=&CatNo=44)
  11. Dighe AS, Rao A, Coakley AB, Lewandrowski KB. Analysis of laboratory critical value reporting at a large academic medical center. Am J Clin Pathol 2006;125:758-64. https://doi.org/10.1309/R53XVC2U5CH6TNG8

Cited by

  1. Autoverification in a core clinical chemistry laboratory at an academic medical center vol.5, pp.None, 2012, https://doi.org/10.4103/2153-3539.129450
  2. Autoverification of routine coagulation assays in a multi-center laboratory vol.76, pp.6, 2012, https://doi.org/10.1080/00365513.2016.1200135
  3. Delta Check Practices and Outcomes: A Q-Probes Study Involving 49 Health Care Facilities and 6541 Delta Check Alerts vol.141, pp.6, 2012, https://doi.org/10.5858/arpa.2016-0161-cp
  4. Implementation of biological variation-based analytical performance specifications in the laboratory: Stringent evaluation of Improvacutor blood collection tubes vol.12, pp.12, 2017, https://doi.org/10.1371/journal.pone.0189882
  5. Strategy for 90% autoverification of clinical chemistry and immunoassay test results using six sigma process improvement vol.18, pp.None, 2012, https://doi.org/10.1016/j.dib.2018.04.080
  6. Using Machine Learning-Based Multianalyte Delta Checks to Detect Wrong Blood in Tube Errors vol.150, pp.6, 2012, https://doi.org/10.1093/ajcp/aqy085
  7. Delta Checks in the clinical laboratory vol.56, pp.2, 2012, https://doi.org/10.1080/10408363.2018.1540536
  8. Post-analytical laboratory work: national recommendations from the Working Group for Post-analytics on behalf of the Croatian Society of Medical Biochemistry and Laboratory Medicine vol.29, pp.2, 2019, https://doi.org/10.11613/bm.2019.020502
  9. Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory vol.19, pp.1, 2012, https://doi.org/10.1186/s12911-019-0848-2
  10. Clinical validation of a delta check model in haematology automated counting improves data validation vol.42, pp.1, 2012, https://doi.org/10.1111/ijlh.13143
  11. National survey on delta checks in clinical laboratories in China vol.58, pp.4, 2012, https://doi.org/10.1515/cclm-2019-1131
  12. Application and optimization of reference change values for Delta Checks in clinical laboratory vol.34, pp.12, 2012, https://doi.org/10.1002/jcla.23550
  13. Biological variation: Understanding why it is so important? vol.23, pp.None, 2012, https://doi.org/10.1016/j.plabm.2020.e00199
  14. Evidence-based approach to setting delta check rules vol.58, pp.1, 2021, https://doi.org/10.1080/10408363.2020.1800585