NoteSwift, Inc., Brings Machine Learning and Artificial Intelligence to EHR Charting

The promise of NLP and machine learning technologies are advancing, but have yet to be applicable to the challenge of entering patient notes — until now.

NoteSwift, Inc., has set out to disrupt the EHR charting process by incorporating components of machine learning and artificial intelligence to develop a tailored, heuristic approach to solving the challenges that plague the EHR patient note input process.

NoteSwift’s patent-pending Parsing and Dynamic Matching (PDM) technology allows physicians to dictate or type a narrative of the patient encounter without having to wade through layers of menu screens, navigate hundreds of mouse clicks and check boxes, or spend time looking up ICD10, SNOMED, and CPT codes. As a result, physicians have more time to treat patients, document co-morbidities, and will also see a reduction in claim denials and resubmissions, thanks to improved reporting accuracy.

“Speech recognition is often cited as a way to get narrative information into the EHR, but that is only part of the solution,” explains NoteSwift VP of Research and Development Allan Stratton. “With our new approach, we take the recognized text from any speech recognition product and apply our proprietary PDM technology to provide a complete solution that specifically addresses and alleviates the challenges associated with patient charting.”

NoteSwift’s PDM technology takes narrative input and parses and dynamically matches the data to discern the key elements of the stated phrases within the note. For example, “ECG 12 leads” is identified within the note and the PDM understands that the EHR is looking for “tracing only of routine 12 lead electrocardiogram (CPT code 93005)” and automatically applies it. The results are entered as…

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