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Lonnie Rae Kurlander
Lonnie Rae is an American business executive, strategist, and human rights advocate focused in healthcare and machine learning. She is the CEO, President and Co-Founder of Medal, Inc, a technology company specializing in the extraction and transformation of unstructured clinical data to generate intelligent longitudinal patient profiles and automate the population of thousands of common medical forms for insurers and government entities through state of the art machine learning. She serves as a mentor to Henkel and to Founders Embassy, the world's first embassy designed for international and immigrant entrepreneurs committed to making a positive impact on the world.
Beginning in 2011 she has worked to understand and address the care of underserved populations around the globe. She has been recognized as a “Badass Woman in Health Tech” due to her abandonment of her M.D. degree with a remaining 8 months after compiling research which indicated the majority of her patient population was dying of information-related errors, estimating that an 8-month delay in her work was equivalent to 166,666 unnecessary deaths. She is known amongst the healthcare community for having founded her company after being hit by a bus. Two years later, she subsequently overcame and discovered the underlying contributors to an unrelated “incurable” illness in order to continue her work. Lonnie has become an advocate for affordable commercial solutions to reduce healthcare waste and improve outcomes.
Her talks have reached tens of thousands of individuals and she has spoken on Capitol Hill, at the White House, and at numerous private events on patient rights, the future of healthcare, and how to implement personalized medicine at scale. She asserts that we need effective management strategies, and not ones that force us to choose who lives, who dies, and who suffers without cause, but rather ones that recast the problem to understand how we treat each member of the population effectively and affordably.
Medal Inc. delivers a complete system for extracting medical information from every possible source where data is trapped: fax, printed paper, health information exchange data, and from most electronic records through Medal's proprietary technology. The Medal Machine Learning and Natural Language Processing system matches over 300 medical attributes to each word of unstructured text, making it the most comprehensive clinical story-generator on the market. Medal Inc. is based in San Francisco, CA.