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Studies show that clinicians are increasingly burning out in large part from the clerical burden associated with using Electronic Medical Record (EMR) systems. At the same time, recently developed health data analytic algorithms struggle with poor quality free-text entered data in these systems. We developed AutoScribe using artificial intelligence-based natural language processing tools to automate these clerical tasks and to output high-quality EMR data. In this article, we describe the benefits and drawbacks of our technology. Furthermore, we describe how we are positioning our company's culture within the existing healthcare system and suggest steps leaders of the system should consider in order to ensure that potentially transformative artificial intelligence-based technologies like ours are optimally adopted.
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A 2019 study studied this question.
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