Abstract
BACKGROUND: Transference of reference intervals (RIs) from multicentre studies are often verified by use of a small number of samples from reference individuals or by the use of one serum sample (Serum X for NORIP RI). Despite recommended and appropriate methods, both have inconveniencies and drawbacks. Several attempts have been made to develop an indirect method, which uses historical data from the laboratory. These methods are retrospective relying on older test results. A near prospective method would be preferable for the laboratories introducing new methods or changing analytical platforms.
METHODS: We performed a data mining experiment using results from our laboratory information system covering patients from a large geographic area. Request patterns for patients with assumed healthy characteristics were identified and used to extract laboratory results for calculation of new RI by an indirect method. Calculated RI and confidence intervals (CIs) were compared to transferred NORIP RI verified by NFKK Reference Serum X.
RESULTS: We found that our indirect method and NFKK Reference Serum X in general produced similar results when verifying transference of RI. The method produces results for all stratifications. Only single stratifications and one analyte showed unexplained incongruences to the NORIP RI.
CONCLUSIONS: Our results suggest using request patterns as a surrogate measure for good health status. This allows for a data mining method for validation of RI or validating their transference, which is likely to be applicable in countries with similar healthcare and laboratory information system.
Original language | English |
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Journal | Clinical Chemistry and Laboratory Medicine |
Volume | 56 |
Issue number | 3 |
Pages (from-to) | 463-470 |
Number of pages | 8 |
ISSN | 1434-6621 |
DOIs | |
Publication status | Published - 23 Feb 2018 |
Keywords
- Journal Article
- transference
- indirect
- data mining
- reference interval
- NORIP
- validation
- Humans
- Middle Aged
- Male
- Reference Values
- Healthy Volunteers
- Young Adult
- Clinical Laboratory Information Systems/standards
- Adolescent
- Adult
- Female
- Aged