Learning Health System (LHS) Virtuous Cycle Domain Analysis Model (Jira PSS-2598)

To facilitate information flow and data reuse activities across the LHS virtuous cycle (evidence to knowledge to action to data and back to evidence), we propose developing a Learning Health System domain analysis model (DAM). The goal is to identify concepts, relationships and behaviors that are common across the LHS virtuous cycle (e.g., in various FHIR IGs) and align and harmonize them to reduce 'profiliferation' through a few high priority clinical scenarios.

For example, a 'cohort definition' or 'patient population' or 'denominator population' each define specific inclusion and exclusion criteria across different quadrants of the LHS. The LHS DAM will follow definitions for several clinical scenarios such as Opioid Use Disorder (OUD), Hypertension (HTN), or Chronic Kidney Disease (CKD) and why they might differ in each quadrant - e.g., (1) subjects enrolled in a HTN clinical trial meeting inclusion/exclusion criteria, (2) trial findings then get translated to evidence incorporated into HTN clinical guideline recommendations for a specific patient population definition, (3) these recommendations are applied in clinical workflows as clinical decision support for a particular HTN pathway, then (4) data documented in the patient record is used as the denominator population in HTN quality measures reported for regulatory purposes, to medical society registries or for public health disease surveillance, and finally (5) information from surveillance or quality reporting systems can support recommendations for improved workflow documentation which subsequently supports more effective outcomes research... and the cycle begins anew.