Arcadia

Step 1: Arcadia aggregates EHR data from hospitals and primary care offices.

Step 2: The platform identifies high-risk patients based on claims, diagnoses, and medication history.

Step 3: Care coordinators receive alerts about high-risk patients discharged from the hospital.

Step 4: Care coordinators use Arcadia to develop and track personalized care plans, coordinating follow-up appointments and medication reconciliation.

Step 1: Arcadia aggregates data from all participating providers in the ACO.

Step 2: The platform tracks key performance indicators (KPIs) related to quality, cost, and patient experience.

Step 3: Care managers use Arcadia to identify patients with unmet needs and provide targeted interventions.

Step 4: The ACO uses Arcadia's reporting tools to monitor progress, identify areas for improvement, and maximize shared savings.

Step 1: Arcadia aggregates data on patient discharges, including diagnosis, procedures, and medications.

Step 2: Machine learning models predict the likelihood of readmission based on patient characteristics.

Step 3: Care teams are alerted to high-risk patients and can proactively intervene.

Step 4: Post-discharge care plans are created and monitored to prevent readmissions.

Step 1: Arcadia identifies patients with diabetes based on claims and EHR data.

Step 2: The platform tracks key indicators such as HbA1c levels, blood pressure, and cholesterol.

Step 3: Care managers use Arcadia to provide personalized education and support to patients.

Step 4: The platform monitors patient progress and adjusts care plans as needed to improve outcomes.

Step 1: Arcadia analyzes prescription fill data to identify patients with low medication adherence.

Step 2: The platform sends reminders and educational materials to patients to improve adherence.

Step 3: Care teams use Arcadia to monitor patient adherence and provide support.

Step 4: The platform tracks adherence rates and measures the impact on clinical outcomes.