Process variation detection using missing data in a multihospital community practice anatomic pathology laboratory

In this brief journal article by Ochsner Health System's Gretchen Galliano, a case is made for a programmatic approach to analyzing missing data in various laboratory information systems (LIS) and determining potential correlations with procedural and systemic processes in the health system. Using the R programming language, homemade scripts, and existing R packages, Ochsner Health Systems visualized and analyzed data from more than 70,000 cases of missing timestamp data, splitting the various cases into five pools. Galliano concludes that the process of "evaluating cases with missing predefined process timestamps" has the potential for improving "the ability to detect other data variations and procedure noncompliance in the AP workflow in a prospective fashion." She added that as an additional benefit, "[p]eriodically evaluating data patterns can give AP LIS teams and operations teams insight into user–LIS interactions and may help identify areas that need focus or updating."

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