Journal:Use of middleware data to dissect and optimize hematology autoverification

From LIMSWiki
Revision as of 18:03, 18 October 2021 by Shawndouglas (talk | contribs) (Created stub. Saving and adding more.)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigationJump to search
Full article title Use of middleware data to dissect and optimize hematology autoverification
Journal Journal of Pathology Informatics
Author(s) Starks, Rachel D.; Merrill, Anna E.; Davis, Scott R.; Voss, Dena R.; Goldsmith, Pamela, J.; Brown, Bonnie S.; Kulhavy, Jeff; Krasowski, Matthew D.
Author affiliation(s) University of Iowa Hospitals and Clinics
Primary contact Log-in required
Year published 2021
Volume and issue 12
Page(s) 19
DOI 10.4103/jpi.jpi_89_20
ISSN 2153-3539
Distribution license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Website https://www.jpathinformatics.org/text.asp?2021/12/1/19/313145
Download https://www.jpathinformatics.org/temp/JPatholInform12119-643471_175227.pdf (PDF)

Abstract

Background: Hematology analysis comprises some of the highest volume tests run in clinical laboratories. Autoverification of hematology results using computer-based rules reduces turnaround time for many specimens, while strategically targeting specimen review by technologist or pathologist.

Methods: Autoverification rules had been developed over a decade at an 800-bed tertiary/quarternary care academic medical central laboratory serving both adult and pediatric populations. In the process of migrating to newer hematology instruments, we analyzed the rates of the autoverification rules/flags most commonly associated with triggering manual review. We were particularly interested in rules that on their own often led to manual review in the absence of other flags. Prior to the study, autoverification rates were 87.8% (out of 16,073 orders) for complete blood count (CBC) if ordered as a panel and 85.8% (out of 1,940 orders) for CBC components ordered individually (not as the panel).

Results: Detailed analysis of rules/flags that frequently triggered indicated that the immature granulocyte (IG) flag (an instrument parameter) and rules that reflexed platelet by impedance method (PLT-I) to platelet by fluorescent method (PLT-F) represented the two biggest opportunities to increase autoverification. The IG flag threshold had previously been validated at 2%, a setting that resulted in this flag alone preventing autoverification in 6.0% of all samples. The IG flag threshold was raised to 5% after detailed chart review; this was also the instrument vendor's default recommendation for the newer hematology analyzers. Analysis also supported switching to PLT-F for all platelet analysis. Autoverification rates increased to 93.5% (out of 91,692 orders) for CBC as a panel and 89.8% (out of 11,982 orders) for individual components after changes in rules and laboratory practice.

Conclusions: Detailed analysis of autoverification of hematology testing at an academic medical center clinical laboratory that had been using a set of autoverification rules for over a decade revealed opportunities to optimize the parameters. The data analysis was challenging and time-consuming, highlighting opportunities for improvement in software tools that allow for more rapid and routine evaluation of autoverification parameters.

Keywords: algorithms, clinical laboratory information system, hematology, informatics, middleware

Introduction

References

Notes

This presentation is faithful to the original, with only a few minor changes to presentation, spelling, and grammar. We also added PMCID and DOI when they were missing from the original reference.