CLG’s patented capability to define patient groups with sophisticated rules for temporal relationships (distance and direction in time) between clinical events allows users to apply a variety of inclusionary and exclusionary criteria to cohort definitions. CLG’s Event Canvas can associate events of any type that are available in the clinical data repository. Event Canvas cohort definitions also have logical operators and parenthetical sub-groupings. Patients who have clinical events that fit the definition of the group are included as cohort subjects. Each subject also has a singular index date, specific to that person's care, which is used in analysis the way a study enrollment date is used—it is the start point for observing outcome events.
Because a CLG cohort is essentially a collection of patient ID’s and index dates from groups sharing common characteristics, cohorts can also be uploaded to CLG from other sources. These include EMR's, registers, external reports, or patient work lists.
Some analysis requires non-uniqueness of patient identity. Encounters by department, for example, pose a throughput question requiring a collection of events rather than a cohort. CLG’s event collection capability addresses this question, defining a collection in the same way as a cohort except that multiple instances of a qualifying event(s) are defined for each patient. For example, a user could create an event collection of all CHF admissions in 2007 or all glucose readings for stroke patients in the ICU in the last week. CLG Analytic Methods such as List, Pivot, and Time to Outcome can then be applied to this collection.