Transforming the way we give and receive care
As AI becomes more common in businesses and society, many are starting to see its potential in the healthcare sector, where it can reduce costs, enhance the quality of patient care, and streamline the day-to-day jobs of medical professionals.
Automated speech recognition (ASR) technology holds particular promise. When combined with natural language processing (NLP), speech technology can understand, interpret and generate human language and perform tasks such as translation, transcription, automatic summarization, topic segmentation, and much more.
The ability to perform these tasks allows AI models to support human workers by giving healthcare professionals more time to focus on personalized, face-to-face patient care. For example, a nurse could use speech recognition technology to create patient discharge notes or update electronic medical records (EMR), giving her extra shift time to interact directly with patients.
Research supports the rising interest and demand for speech recognition technology and AI in healthcare. Accenture predicts the AI health market could reach a staggering $6.6 billion by 2021, representing a compound annual growth rate of 40%.
How Speech Recognition Technology Can Help Healthcare
Many healthcare companies understand the benefits of speech recognition, using the technology to create innovative solutions for some of our most pressing modern challenges.
ASR saves time and increases productivity
Underpinned by natural language processing, speech technology is helping doctors save time and improve productivity by taking over some of the labor-intensive administrative tasks related to their profession.
Voice recognition documentation tool, Dragon Medical, for example, delivers real-time transcription, making it easier for healthcare professionals to keep comprehensive records. Instead of doctors typing up lengthy notes to fill electronic reports, Dragon Medical accurately translates their voice notes and memos into a detailed clinical narrative, allowing them to spend more time with their patients.
Amazon Transcribe Medical offers a similar service. This machine learning tool quickly and accurately creates transcriptions of medical consultations between doctors and patients. The transcribed text can be analyzed using natural language processing and used to submit electronic health reports.
AI-powered transcription may not seem groundbreaking, but when you consider that a 2017 study by the University of Wisconsin and the American Medical Association showed that primary care physicians spend six hours a day entering records into electronic health record systems, you begin to realize how the smallest of automations can make the biggest of differences.
ASR improves healthcare communication
Leading secure enterprise messaging service, NetSfere, incorporated medical-specific speech recognition technology into their mobile messaging platform to improve healthcare communications.
NetSfere’s solution provides a secure, encrypted messaging experience that accurately understands complex medical jargon shared through voice command. According to Raúl Castanon-Martinez, Senior Analyst for Workforce Collaboration at 451 Research, this allows frontline workers to “provide contextually intelligent, personalized and predictive delivery of patient care.”
According to a press release issued by NetSfere:
As speech technology using mobile messaging becomes more widely adopted in the healthcare sector, consumer-grade speech services are adequate for day-to-day communication but lack the ability to recognize industry-specific vocabulary routinely used in the medical field – i.e. anatomical and surgical terms, procedures, diagnostic tests, ailments, and prescription drug names. Doctors, nurses, and other medical professionals can now communicate and consult with one another through the NetSfere application regarding patient diagnosis or test results, leveraging speech recognition with the immediacy of messaging in a secure and encrypted fashion.
ASR allows remote diagnosis and care
Speech recognition technology also makes it much easier for patients and healthcare professionals to search for information about COVID-19 symptoms.
Mayo Clinic has added a skill to Amazon Alexa (called “Answers on COVID-19”), which acts as a self-assessment tool to help patients access clear and precise information about symptoms and determine if they require further testing.
Alexa’s new skill is one example of how speech recognition technology can help healthcare professionals deliver support at scale and remotely. For most healthcare providers, expanding their remote offerings eases the strain on overloaded systems and provides better protection against airborne viruses.
Assists in monitoring health status of patients
Speech technology is also helping doctors communicate with patients in more human ways. South Korea has enforced a 14-day mandatory quarantine for all those who have recently travelled into the country and for those who have been in contact with a COVID-19-positive patient.
Technology is helping South Korean healthcare workers monitor the health status of these potentially infected people. SK Telecom enabled its home AI assistant “Nugu” to make twice-a-day voice calls to those under quarantine, to enquire about symptoms and analyze answers to determine the seriousness of the symptoms displayed.
Amazingly, people who interact with Nugu are not restricted to ‘yes’ or ‘no’ answers and can provide the AI-model with complex, elaborate answers, just as they would to a human professional. This use of speech technology aims to reduce the heavy load of healthcare workers while improving the accuracy and efficiency of monitoring.
The changing face of healthcare
As can be seen from the above examples, ASR is already transforming the way people give and receive healthcare. AI can reduce the workload of medical professionals in many ways, freeing them up to spend more time on quality face-to-face interactions. The technology can also provide healthcare professionals with readily available information that will provide them with the insights they need to make important decisions. By combining human intelligence with machine learning, medical professionals are able to provide more comprehensive, more accurate and more engaging healthcare to everyone, everywhere.