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Using Speech Recognition to Drive EHR Adoption

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Meaningful Use (MU)-certified EHRs have become the de facto standard and a must-have technology for most hospitals. But despite the availability of significant amounts of federal stimulus funds toward adoption, most physicians see tools that simplify, speed up and improve the quality of clinical documentation within their existing EHRs to be a higher priority.

A further obstacle is that structured clinical documentation using EHR templates may actually negatively impact physician productivity in a point-and-click environment.

Physician Narrative
An essential part of improving the quality of clinical notes is the capture of a more complete patient story via the physician narrative to complement the less expressive point-and-click templates. Without such narrative, and due to widespread copy-and-paste behavior, clinical notes lack documentation of the physician thought process that is so critical in coordinating care among multiple care providers. In the words of one physician: "I am looking at eight pages of detailed, structured EHR documentation and still have no clue what's going on with this patient."

This explains why the physician narrative has always been the most popular mode of physician documentation. On average, 60 percent of a patient's medical history still resides in unstructured clinical documentation. And with the recent availability of powerful speech and natural language understanding tools that liberate the clinical content hidden inside those narratives, that number is likely to go up rather than down.

In the past, narrative clinical documentation was neither accessible nor actionable from a computational perspective, but that has changed rapidly in the last few years.

Validated Data Capture
Today, we can capture validated clinical data directly from physician narrative in real-time, and use it to drive MU and Quality Measures reporting, abstracting and billing needs - all without making physicians point-and-click through pages and pages of structured templates.

This not only delights physicians by allowing them to spend more time with their patients again, it also results in more meaningful (lowercase!) clinical documentation that physicians find more useful. The data tells the patient's story and contains all the relevant clinical facts and considerations, rather than putting too much emphasis on just the reimbursement requirements.

Speech and Natural Language Understanding Technology
Recent advances in Speech and Natural Language Understanding technology are giving physicians the best of both worlds - efficient narrative documentation and compliance, with regulatory and financial requirements - something traditional speech recognition technology is not capable of delivering.

These new technologies implement a closed loop documentation workflow where physicians receive guidance about documentation requirements and compliance based on the content of their narrative documentation. This allows physician to get to the right level and specificity of clinical documentation (i.e, key use case for appropriate ICD-10 documentation) in a once-and-done workflow, as opposed to receiving queries from coders or CDI specialists at a later time when it is a huge disruption.

With the continuous increase in regulatory requirements relative to clinical documentation (e.g., MU, quality measures, ICD-10, value-based purchasing), keeping physician productivity and quality of clinical documentation high through the use of speech technologies is a key driver of successful adoption of EHR systems.

Dr. Fritsch is chief scientist at M*Modal. Dr. Fritsch co-founded MultiModal Technologies Inc. in 2001. Prior to that, he co- founded  Interactive Systems Inc., where he served as principal research scientist and was responsible for developing a next-generation medical speech understanding system. Dr. Fritsch has held research positions at the University of Karlsruhe and at Carnegie Mellon University. He earned his MSc and PhD degrees in computer science from the University of Karlsruhe.


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Ditto about Carol's question. I want to know the same thing.

Darlene October 25, 2012



So where does that put all the medical transcriptionists in the world -- in the out-of-work category?? Is there some way they can fit in to the new system?

Carol October 25, 2012




     

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