KenSci and T3K Health Announces Strategic Partnership to Deliver AI Based Predictions Directly Within EHRs
KenSci, an AI led risk prediction platform for healthcare and T3K Health, a healthcare consulting firm focused on implementation, optimization and integration of EHR systems, have announced a strategic partnership focused on helping care givers leverage AI and Machine Learning within their existing EHR systems and workflows.
While Artificial Intelligence and Machine Learning led innovation in healthcare has made rapid strides, front line care givers and Chief Medical Officers continue to struggle with operationalizing advanced analytics within existing systems and workflows. The partnership aims to make it easier to connect advanced innovation to systems that the care givers are already using, thereby reducing disruption and administrative loads on doctors and nurses.
“We are tremendously excited about the opportunity to operationalize AI in the clinical and operational context for care givers without changing existing workflows,” said Sunny Neogi, KenSci’s Chief Growth Officer. “For AI to succeed, we need to reduce the additional software UX burden on doctors and nurses. Our vision is to be a true System of Insight for Healthcare, working with existing data and systems of engagement, adding tremendous value through AI without causing disruption.”
“We have seen consistent feedback from EHR users regarding their need to reduce additional workflows and disruption. By bringing AI enabled predictive analytics within the context of EHR workflows, we are bringing together the best of both worlds – disruptive innovation and streamlined processes,” said Brad Beauvais, Partner at T3K Health.
KenSci and T3K is deploying multiple solutions across Acute Care Management and AI led Hospital Command Center that work within EPIC and Cerner for large health systems across US. The team will be partnering closely with CMOs and CIOs at health systems who have deployed enterprise wide EHR systems to unlock more value using AI within the context of their existing EHRs.