3 Uses for Speech Recognition Software in the Health Care Setting

speech recognition in health careMany health care industry observers are discussing electronic health records (EHR), insurance exchanges, mobile apps, data analytics and other tech innovations that are reshaping America’s health care system. Another technology that has quietly gained traction in the medical profession is speech recognition software. In fact, popular investment gurus at The Motley Fool have argued that speech recognition offers a terrific under-the-radar opportunity for investors.

EHRs may become great vehicles to involve patients in their own care. They may also offer governments a vital tool for predicting pandemics and shaping health policy. Even so, 93 percent of doctors say that their EHR software hasn’t reduced the time required to prepare patient documentation. Investment analysts and many hospital administrators (click this link to learn about administrative positions) see speech recognition as the key to unlocking the full potential of EHRs. Integrating speech recognition into EHRs significantly speeds up documentation, and these three solutions are leading the way.

Dragon Medical 360 by Nuance

Before speech recognition software became popular, many doctors carried handheld tape recorders. After an appointment, they would dictate information about the appointment into their recorders. At the end of the day, they would hand cassettes to nurses or office professionals. Those staff members would then transcribe the doctor’s recordings into each patient’s record.

Dragon Medical 360 allows doctors to dictate their appointment notes using either their laptops or their mobile devices. The speech recognition software then transcribes those notes with an out-of-the-box accuracy rate of 98 percent. Dragon Medical is compatible with most Windows-based EHRs including solutions by Cerner, Epic, GE and McKesson. With Dragon, doctors can simply speak a record of a patient’s visit directly into their own electronic medical records (EMR) and into the patient’s EHR.

Watson EMR Assistant by IBM

EMRs often contain conflicting data that make them difficult for doctors to search and interpret. For example, a patient may have two EMRs because of a misspelling of the patient’s name or the incorrect recording of the patient’s birth date. Also, EMRs may travel from facility to facility in a health care group, and data in other facilities may be collected, recorded and organized in different ways. Scanning through an EMR can mean going through as much as 100MB of text, imaging studies and medication history.

A few years ago, Watson made its debut on Jeopardy by defeating uber-champion Ken Jennings. Watson EMR Assistant, developed by IBM in partnership with Case Western University, is designed to help doctors make connections between disparate mounds of data. Watson can process EMRs using its natural language expertise. It can surface information and relationships within data even when processing a lifetime of patient records. After going through an EMR, Watson can create reports using visual analytics. Doctors can quickly interpret the data and use the results in their practice.

Ultimately, researchers hope that the technology will pull out the most important information in patient records to help doctors predict future clinical concerns. Researchers also expect Watson EMR Assistant to correlate medications and key lab results for disease prevention and detection.

WatsonPaths by IBM

Imagine a futuristic scene in which a doctor verbally asks a computer for help diagnosing a patient. With WatsonPaths, another IBM-Case Western collaboration, that futuristic scene may soon become reality. WatsonPaths can analyze complicated scenarios and generate solutions just like doctors do during patient appointments. It gathers information from medical literature, and it learns from the doctors that use the tool.

When WatsonPaths is ready for showtime, Case Western will pilot the technology with Cleveland Clinic faculty and students. In addition to providing both faculty and students with the latest medical information, WatsonPaths will also train students to draw conclusions using the type of reasoning that it has learned from faculty. Ultimately, by discussing patients with Watson, doctors will have access to both real-time medical information and a machine that can critique flawed reasoning.

Conclusion

Dragon Medical 360 is already in the marketplace, and IBM’s Watson solutions aren’t far behind. These speech recognition technologies can improve doctors’ workflows and improve patient EMR/EHR interpretation. You may have already called your broker about investing in EHR companies; you might want to call her again to discuss investing in speech recognition technology.

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