Seattle-based KenSci, a healthcare analytics and artificial intelligence (AI) company, launched its AI Platform for Digital Health that helps healthcare organizations accelerate their journey from business intelligence (BI) to AI to return on investment (ROI). The re-imagined AI platform extends KenSci’s runtime engine with BI-AI development capabilities and the latest predictive analytics technology that enables health organizations to develop BI and AI-based workloads in an easy and agile way.
Hospitals, healthcare systems, providers, and health plans are redefining the way data-driven insights are integrated with their operational, clinical, and financial workflows. Built specifically for healthcare, KenSci’s AI Platform for Digital Health is an interpretable, integrated, and simplified data platform which powers operational and clinical workflows with AI based insights. The KenSci solution enables users to rapidly build their own customized AI-enabled use cases or deploy KenSci solutions built into the platform.
“Healthcare organizations have access to a treasure trove of data which can be maximized to gain insights and improve quality of care and the patient experience,” says Samir Manjure, KenSci chief executive officer. “The bottleneck in the AI journey originates from the time it takes to transform and shape data into a format that allows for intelligent insights to be extracted. The KenSci AI Platform for Digital Health aims to bridge this gap using a modern AI-ready data architecture that we truly believe will be a game changer in making the healthcare industry AI ready.”
The KenSci AI platform has comprehensive and scalable data management functionality that delivers a real-time data pipeline ready for advanced analytics use cases. A key feature is a late-binding extract-load-transform (ELT) capability which moves data from various health data sources—including electronic medical records (EMR), insurance claims, admittance, discharge and transfer records (HL7 ADT), and medical device data—into the KenSci AI platform. Data can then be mapped into standard data schemas such as fast healthcare interoperability resources (FHIR) and other commonly used formats for downstream analytics.
With a comprehensive AI model development, scoring and monitoring environment, the KenSci AI Platform for Digital Health allows users to build, train, and manage AI models and accelerate their impact across a diverse set of operational and clinical scenarios. Pre-built AI models and a clinically validated feature library enable analytics teams to quickly fire up new AI-based solutions and applications on top of the service-level-agreement (SLA)-backed managed data pipeline.
KenSci’s AI Platform for Digital Health integrates Microsoft Power BI data visualization tools to enable in-house analytics on top of the data pipeline. Analytics teams can leverage auto-generated key performance indicators, system-wide metrics, and pre-built integrations directly into Microsoft Power Apps, Microsoft Teams and key EMRs to streamline adoption. New analytics-based applications can be developed and deployed in a matter of days without complex customization work.
“Through collaboration with Microsoft and using their healthcare technology expertise, KenSci is helping healthcare organizations simplify their data movement to the cloud, accelerating use of AI in improving operational and care management outcomes. KenSci’s AI platform for digital health helps health teams build data-rich use-cases and innovate in a secure data pipeline within their own Azure environments.” says Heather Cartwright, general manager, Microsoft Health.
KenSci’s existing customers have access to the new features and capabilities of the AI platform through their existing subscriptions and can enable their analytics teams to build and innovate leveraging the latest analytics technology. The company says health organizations that are looking to reduce the time-to-value for their Azure cloud investments will benefit by adopting KenSci’s AI platform to quickly transform their data into an ROI generating asset in their own Azure environments.
For more information, visit KenSci.