patient-panel-overview

Panel analytics from FHIR data are generated by querying condition-specific cohorts to aggregate panel size, at-goal rates, no recent lab or visit metrics, and risk stratification. This enables proactive population health management by summarizing cohort-level patient data.

Risk stratification categorizes chronic disease patients by clinical severity using standard FHIR data. It identifies high-risk individuals within condition cohorts to produce prioritized outreach lists, enabling targeted interventions for patients not at clinical goal.

Yes, multiple chronic conditions like diabetes, hypertension, CHF, COPD, CKD, and depression can be analyzed in a single panel overview. Multi-panel scenarios support querying several conditions simultaneously to aggregate distinct cohort metrics.

Care gaps and outreach priorities are identified by analyzing no recent lab and no recent visit metrics alongside at-goal rates for condition cohorts. The analysis produces a prioritized outreach list highlighting patients requiring follow-up actions.

FHIR data required includes condition records with standard clinical codes for cohort identification, plus lab result and encounter resources to calculate no recent lab and no recent visit metrics. This data drives the panel-level analytics and care gap detection.

Panel management supports common chronic disease panels including diabetes, hypertension, CHF, COPD, CKD, and depression. Custom condition support depends on available FHIR clinical codes and reference materials to inform cohort identification and care gap follow-up actions.