• Create 'research ready' data sets using Generative AI without burdening data engineering teams
• Train AI Models on data that remain behind partners' firewalls with Federated Learning
• Securely deploy custom code and workflows on partners' data (e.g. annotation software, Jupyter notebooks)

Same as above

• Physician scientists interested in AI / ML, especially federated consortia, quality measure development, or public health surveillance
• Hospital CMIO, research operations, data engineering, or innovation teams
• Pharma or Biotech AI, data science, data engineering, evidence, or HEOR teams
• Payor CIO, CDO, population health, claims operations, or FWA teams

A Texas based was looking for a single source of truth that could
provide insights on their care continuum. The organization deployed Innovaccer’s Data Activation Platform, that helped them establish intact patient records, standardize care processes, and managed to deliver meaningful information. The ACO was engaged with five national and commercial payers, looking after more than 200,000 patients. With data incoming from EHRs at 60+ practices, over 280 physicians, and three labs, the ACO required a holistic view of population health. The ACO had the following data needs:
• Data aggregation and normalization from multiple facilities
• Accurate data segmentation and ensured security
• Interoperability across systems
• Gaps in care monitoring
• Quality and performance measurement

With the help of Innovaccer's platform, the outcomes were:
• Gaps in care bridged for 9,000+ lives by 25 care managers in only 6 months.
• 1 FTE saved for the network within the first month of implementation.
• One-click access to patient records, anywhere in the network.
• Network utilization monitored across 5 measures to optimize the utilization of Emergency Room facilities, Inpatient Admits, Specialist Visits, and High Tech Imaging.
• Quality of care tracked across 20 quality measures and calculated to encourage improvement in the quality scores.
• Over 200,000 patient records streamlined for 60+ practices.

Innovaccer applications rely heavily on trustworthy data formatted into a master patient index.
DAP’s EMPI engine helps in uniquely identifying members (patients) across disparate healthcare IT systems, as an imperative for any downstream applications. DAP employs a proprietary Bayesian-based flexible matching algorithm that produces an accuracy of more than 96% every time to create a Patient 360 longitudinal view.
Deployment of pediatric solution powered by data ie. pediatric centric, we collect, normalize, standardize data and then through our automated workflows find pediatric-specific care gaps and some of them are:
Well Child Visits (W15)
Child Immunization Status (CIS)
Adolescent Immunization Status (IMA)
Private Duty Nursing (PDN), and more.

This supports our pediatric solution deployment and the data powers downstream applications to show results over 100+ pediatric measures.

Data Analysts, Administrators, IT Support personnel, Business Analysts, Data Analytics Managers