Temporal abstraction-based clinical phenotyping with Eureka!

Abstract

Temporal abstraction, a method for specifying and detecting temporal patterns in clinical databases, is very expressive and performs well, but it is difficult for clinical investigators and data analysts to understand. Such patterns are critical in phenotyping patients using their medical records in research and quality improvement. We have previously developed the Analytic Information Warehouse (AIW), which computes such phenotypes using temporal abstraction but requires software engineers to use. We have extended the AIW's web user interface, Eureka! Clinical Analytics, to support specifying phenotypes using an alternative model that we developed with clinical stakeholders. The software converts phenotypes from this model to that of temporal abstraction prior to data processing. The model can represent all phenotypes in a quality improvement project and a growing set of phenotypes in a multi-site research study. Phenotyping that is accessible to investigators and IT personnel may enable its broader adoption.

Figure 1:

Package diagram of the Eureka architecture.

Figure 2:

Data element editing wizard showing the four types of data elements that may be created. A value threshold type has been selected.

Figure 3:

Category data element editing screen showing a custom grouping of data elements found in the System tab that represent disease conditions.

Figure 4:

Data element editing screen showing a value threshold data element being created: high blood pressure, defined as systolic blood pressure >= 140 or diastolic blood pressure >= 90, or systolic blood pressure >= 130 or diastolic blood pressure >= 80 with a diabetes (ERATDiabetes) or chronic kidney disease (ERATCKD) discharge diagnosis code.

Figure 5:

Data element editing screen showing a frequency data element being created: 2 consecutive high blood pressure values within 180 days of each other (consecutive means with no intervening not-high values).

Figure 6:

Data element screen showing a sequence data element being created: two inpatient encounters with the second encounter before the first by at most 30 days.

Figure 7:

Flow chart showing the process of converting Eureka! data elements into temporal abstraction definitions. This occurs in the services layer (Phenotypes component in Figure 1). Example phenotypes and how they would go through this workflow are illustrated on the right.