Ann Lab Med.  2019 Nov;39(6):552-560. 10.3343/alm.2019.39.6.552.

Development of Statistical Software for the Korean Laboratory Accreditation Program Using R Language: LaboStats

• Kim Y
• Park HI
• Lee HK
• Nam HS
• Lee YW
• Lee SG
• Park Y
• Lee W
• Nam MH
• Song SH
• Chung JW
• Lee J

• KMID: 2450950
• DOI: http://doi.org/10.3343/alm.2019.39.6.552

Abstract

BACKGROUND
In Korea, the Korean Laboratory Accreditation Program (KLAP) has set minimum standards for verification of clinical test performance. This verification process is time-consuming and labor-intensive when performed manually. We developed a free, statistical software program for KLAP, using the R language (R Foundation for Statistical Computing, Vienna, Austria).
METHODS
We used CLSI guidelines for the algorithm. We built graphic user interfaces, including data input, with Embarcadero Delphi EX4 (Embarcadero Technologies, Inc., Texas, USA). The R Base Package and MCR Package for Method Comparison Regression were used to implement statistical and graphical procedures.
RESULTS
Our program LaboStats has six modules: parallel test, linearity, method comparison, precision, reference interval, and cutoff. Data can be entered into the field either manually or by copying and pasting from an MS Excel worksheet. Users can print out precise reports.
CONCLUSIONS
LaboStats can be useful for evaluating clinical test performance characteristics and preparing documents requested by KLAP.

Keyword

Statistical software; Korean Laboratory Accreditation Program; R language; CLSI; LaboStats

MeSH Terms

Accreditation*
Korea
Mathematical Computing
Methods
Texas

Figure

• 

  Fig. 1 Flow chart for computerizing the statistical process for clinical test performance verification.

• 

  Fig. 2 Data entry user interface of the parallel test module.

• 

  Fig. 3 Linearity test report.

• 

  Fig. 4 Method comparison report.Abbreviation: CI, confidence interval.

• 

  Fig. 5 Data entry user interface of the precision module.

• 

  Fig. 6 Data entry user interface of the cutoff module.

Reference

1. Guzel O, Guner EI. ISO 15189 accreditation: requirements for quality and competence of medical laboratories, experience of a laboratory I. Clin Biochem. 2009; 42:274–278. PMID: 19863920.

2. Linden JV. Errors in transfusion medicine. Scope of the problem. Arch Pathol Lab Med. 1999; 123:563–565. PMID: 10388907.

3. Campbell CA, Horvath AR. Harmonization of critical result management in laboratory medicine. Clin Chim Acta. 2014; 432:135–147. PMID: 24246790.

4. Ehrmeyer SS. Satisfying regulatory and accreditation requirements for quality control. Clin Lab Med. 2013; 33:27–40. PMID: 23331727.

5. Ehrmeyer SS, Laessig RH. Has compliance with CLIA requirements really improved quality in US clinical laboratories? Clin Chim Acta. 2004; 346:37–43. PMID: 15234634.

6. Jang MA, Yoon YA, Song J, Kim JH, Min WK, Lee JS, et al. Effect of accreditation on accuracy of diagnostic tests in medical laboratories. Ann Lab Med. 2017; 37:213–222. PMID: 28224767.

7. Health Care Financing Administration and Department of Health and Human Services. CFR 493.1255 - standard: calibration and calibration verification procedures. Code of Federal Regulations. Particuology. 2009; 493:42.

8. CLSI. User evaluation of between-reagent lot variation. Approved guideline EP26-A. Wayne, PA: Clinical and Laboratory Standards Institute;2013.

9. CLSI. Evaluation of the linearity of quantitative measurement procedure: A statistical approach. Approved guideline EP06-A. Wayne, PA: Clinical and Laboratory Standards Institute;2003.

10. CLSI. Measurement procedure comparison and bias estimation using patient samples. Approved guideline EP09-A3. Wayne, PA: Clinical and Laboratory Standards Institute;2013.

11. CLSI. User verification of precision and estimation of bias. Approved guideline EP15-A3. Wayne, PA: Clinical and Laboratory Standards Institute;2014.

12. CLSI. Defining, establishing, and verifying reference intervals in the clinical laboratory. Approved guideline EP28-A3c. Wayne, PA: Clinical and Laboratory Standards Institute;2010.

13. CLSI. User protocol for evaluation of qualitative test performance. Approved guideline EP12-A2. Wayne, PA: Clinical and Laboratory Standards Institute;2008.

14. Wikipedia. Delphi (IDE). Updated on April 2019. https://en.wikipedia.org/wiki/Delphi_(IDE).

15. Rej R, Norton-Wenzel CS. EP evaluator-CLIA (EE-CLIA) for evaluating clinical laboratory methods (Consultant's version with rapid results entry). Clin Chem. 2001; 47:2075–2076.

16. Martindale RA, Cembrowski GS, Journault LJ, Crawford JL, Tran C, Hofer TL, et al. Validating new reagents: roadmaps through the wilderness. Lab Med. 2006; 37:347–351.

17. Don-Wauchope AC. Lot change for reagents and calibrators. Clin Biochem. 2016; 49:1211–1212. PMID: 27161481.

18. Katzman BM, Ness KM, Algeciras-Schimnich A. Evaluation of the CLSI EP26-A protocol for detection of reagent lot-to-lot differences. Clin Biochem. 2017; 50:768–771. PMID: 28322754.

19. Algeciras-Schimnich A, Bruns DE, Boyd JC, Bryant SC, La Fortune KA, Grebe SK. Failure of current laboratory protocols to detect lot-to-lot reagent differences: findings and possible solutions. Clin Chem. 2013; 59:1187–1194. PMID: 23592508.

20. Glatz JF, Storch J. Unravelling the significance of cellular fatty acid-binding proteins. Curr Opin Lipidol. 2001; 12:267–274. PMID: 11353329.

21. Brüggemann L, Quapp W, Wennrich R. Test for non-linearity concerning linear calibrated chemical measurements. Accred Qual Assur. 2006; 11:625–631.