Widespread health IT adoption in the United States is lagging, despite the promise of EMRs to reduce medical errors, improve quality of care, and overall cost of healthcare. While radiology is already reaping the rewards of speech recognition, many feel the technology holds the key for increased EMR utilization as well.
The United States spends a higher portion of its gross domestic product on healthcare than any other country in the world, but ranks only 37th in its performance, according to the World Health Organization. Many experts agree that the best way to improve healthcare quality and reduce medical errors is to fully deploy EMRs.
President George W. Bush set a goal to provide a portable health record for every American by 2014, and the savings from EMR adoption could exceed $30 billion annually. While Bush’s goal might be considered unreachable, speech recognition could help speed adoption.
Healthcare currently represents 85 percent of the global PC- and server-based speech recognition market—a market estimated to be worth $170 million in 2007 and $207 million in 2008. British market research firm Datamonitor estimates that the North American healthcare speech recognition market is currently valued at approximately $160 million.
Radiology recognizes benefits
Within radiology, speech recognition technology holds the promise of being more than a tool to convert speech to text. By incorporating natural language processing tools and a controlled medical vocabulary, the mapping and distribution of administrative codes and terminologies may enable interoperability and clinician support as part of an EMR.
According to Joe Moore, chief information officer at Radiology Consultants of Iowa (RCI) in Cedar Rapids, speech recognition has made a huge impact on the practice—more than any other IT-based technology.
Moore says he was hired in 2004 to implement systems and technology, such as PACS and HL7 interfacing, to support the core business of professional radiology services. “All have led to improved workflow and efficiency, but nothing has impacted us greater than speech recognition,” he adds. In 2005, RCI, which generates approximately 450,000 studies per year, implemented MedQuist’s SpeechQ for Radiology front-end speech recognition solution across all 12 hospitals and its imaging center that interfaces with eight different RIS. Radiologists working within SpeechQ can access PACS from the program to view films and pull reports.
Moore notes that since implementing SpeechQ, the percentage of exams with a final report delivery in under an hour is now at 87 percent, compared to approximately 7 percent prior; the percentage of exams with a delivery of final report in less than two hours is now at 94 percent, compared to approximately 15 percent before. For emergent cases, 85 percent are delivered in less than 30 minutes and 96 percent are delivered in less than an hour.
“Our biggest naysayers are now our biggest advocates for speech recognition—they never want to go back to the old way,” he says.
An off-ramp to the EMR
John Athas, MD, president of Athas Radiology in New York, N.Y., confirms that most radiologists have finally embraced speech recognition, realizing that without it, work can be time-consuming and inefficient. “Early on, speech recognition was difficult and time-consuming to use, but there have been many improvements over the last five years making speech much more accurate and easy to use.”
As a teleradiology company providing final interpretations, with approximately 30,000 to 40,000 studies per year, Athas wanted a scalable solution that would fit his growing practice.
Using M*Modal’s AnyModal CDS Speech Understanding technology, integrated into NeuroStar’s Virtual Radiology system since August 2008, the practice plugs into any imaging system to establish a comprehensive worklist for their radiologists. “We can add readers, track cases and give the service we need to, in an organized fashion—because radiology is all about that now,” he says.
AnyModal CDS Live captures and comprehends clinical information from dictation and can populate the medical record—creating a kind of “off-ramp” to the EMR. Physicians can elect to self-edit and use the real-time service or back-end approach to send drafts for editing by a medical transcriptionist.
Neurostar essentially provides an overlay