Our cloud-based, HITRUST CSF®™-certified, HIPAA-compliant Arcadia Analytics Population Health Platform is purpose-built with best-in-class big data technology to support high availability data ingestion, computation and storage.
We extract rich, useful clinical EHR data and combine it with adjudicated claims systems, SDoH data, ADT feeds and more to build a high-quality, continually updated enterprise data asset that powers your success in value-based care.
Illuminate drivers of cost and utilization, measure performance, find and close risk and quality gaps, identify impactable patients for care management and outreach. The result: reduced TME, more accurate risk adjustment and improved quality.
Achieve better and more sustainable financial outcomes by combining the most comprehensive patient view with actionable AI-powered insights into care team-centered workflows for outreach, documentation, tasking and care coordination.
We help innovative healthcare organizations across the country succeed under value-based care with high-quality aggregated data, actionable insights, and provider-friendly workflow applications.
We collaborate with their provider networks to improve STARS/HEDIS performance and risk adjustment accuracy.
We build population health management strategies to take on Medicare, Medicaid, and Commercial risk-based contracts
We work with employer groups striving to provide high-quality, high-value care options for their employees
$11M in retained earnings by reducing TCC by 11% in commercial downside risk
Achieved 99.6% quality performance under MSSP
Learn key strategies to identify Social Determinants of Health data and incorporate it with clinical data to enable proactive care strategies for vulnerable populations.
May 11, 2021
Their talk focused on leveraging analytics to drive provider incentives, track ROI, and inform strategic program investment….
May 10, 2021
Gartner makes three recommendations for CIOs: 1) Reengineer your data services layer by investing in next-generation smart data technologies. Develop a pipeline of data tools and enablers across your digital architecture. 2) Move AI from the lab to value realization by focusing on the human elements of culture and frontline adoption. Democratize ownership by engaging end users early and continuously. 3) Break down and reconstruct your data governance processes and models. Drive improved enterprise data agility and collaboration by using adaptive data governance and DataOps approaches.
April 28, 2021