Health Information Exchanges (HIEs) are exploding across the world and here in the US private companies, States and even large counties are launching their own HIEs. Competition to provide the most information about patients to the largest number of providers has high stakes.
Companies and organizations looking to improve the customer experience with improved speed, security and reduced cost (as well as trying to become the biggest HIE on the block) will look to merge these existing HIEs. This inherently will cause massive confusion with the use of different patient information nomenclatures, categories and partner designations. Here we speak with Kristin Brown of Tamr to try to clarify some of the confusion.
About Kristin Brown
Kristin Brown is a Federal Civilian Account Manager at Tamr, where she focuses on developing business for Tamr’s Civilian and SLED Government solutions Team. Kristin has over 15 years of strategic account and partner management experience. Before joining Tamr, Kristin has worked within the Federal market at numerous firms such as Varonis, Tenable, Vectra AI and Collibra. Kristin holds a B.A. in English from American University.
Tamr and through its subsidiary, Tamr Government Solutions, is the leading data mastering company that accelerates data-driven business outcomes for large organizations. Public sector leaders like: U.S. Department of Homeland Security, U.S. Army, U.S. Office of the Secretary of Defense, U.S. Air Force and U.S. Navy trust Tamr to manage their enterprise data as an asset.
Tamr’s unique approach of using human-guided machine learning algorithms to accelerate data mastering projects lets the world’s largest organizations enhance their data operations, rapidly activate latent data, and increase the velocity of business outcomes through data-driven insights. With a co-founding team led by Andy Palmer (founding CEO of Vertica) and Mike Stonebraker (Turing Award winner) and backed by investors including NEA and Google Ventures, Tamr is transforming how companies get value from their data.