Cerner CEO Brent Shafer said the EHR vendor will continue to transform its business strategy in 2020 by redefining its client experience and cementing its position as part of the new cognitive era in healthcare.
Mr. Shafer outlined Cerner's business strategy for the year ahead during a Jan. 14 presentation at the 38th annual JP Morgan Healthcare Conference in San Francisco.
Last year, Mr. Shafer announced the company's new operating model, which pivoted Cerner's focus from EHRs to a platform organization. The introduction of the operating model has served as a key steppingstone for Cerner to initiate an overall transformation effort, focused on defining the company's client experience and ensuring its clients are successful in their respective environments, Mr. Shafer said.
Cerner's partnership with Amazon Web Services, which the companies announced last July, will also support Cerner's growth in the coming year as it moves into a new era for EHRs. Moving forward, Mr. Shafer said Cerner's priorities with the partnership are to migrate privately hosted platforms to the cloud-based service to eventually support data science at scale and leverage artificial intelligence and machine learning to create new solutions.
"This is where we get into the idea of cognitive healthcare," Mr. Shafer said. "The EHR market is largely penetrated; there has been adoption, but it's not loved. Most users don't love using the EHR [because] it's data intensive…Finding ways to simplify that experience; better user interface, better workflows, using voice where possible, these are all great opportunities."
Mr. Shafer said the intention of re-establishing the joy of practicing medicine will be one of Cerner's driving factors in the year ahead to improve patient outcomes and reduce operational and administrative burdens that get in the way of delivering care.
In December, the company achieved its 500th patent, which is a voice-assisted technology to support clinician documentation, and developed a new platform with AWS that supports data scientists in creating and managing machine learning models at scale.