ASUS and National Taiwan University Hospital (NTUH) Hsin-Chu branch today announced that medical speech recognition will be rolled out to outpatient clinics, clinical care and other facilities. This speech-to-text instantaneously records patient notes, allowing medical professionals to conduct patient consultations while the software takes notes. This reduces doctor or nurse administrative loads by up to 30%, improving hospital efficiency.
While speech recognition software is fairly common in Europe and in the United States, Taiwanese hospital staff tend to use a combination of Mandarin and English, making it difficult for software to capture patient notes. The medical speech recognition solution is customized to recognize these two languages.
“Medical speech recognition combines speaking and writing modes to allow medical staff to talk to patients in their native language, with the system converting speech to text almost immediately,” said NTUH Hsin-Chu branch Superintendent Chong-Jen Yu after testing the medical speech recognition solution. “This gives medical staff more time to interact with the patient, thereby enhancing the doctor-patient relationship.
ASUS and NTUH conducted small-scale clinical trials, taking feedback from front-line staff and using it to develop the algorithm and significantly improve the accuracy of speech recognition. Medical speech recognition has already been used in outpatient and clinical wound care, physical examinations, and other situations.
Doctors previously had to manually record patient diagnoses in a timely manner, and this proved difficult if they had to conduct patient palpation and physical exams. “Before we adopted this technology, doctors had to rely on memory, or nursing staff had to go back to the nursing station to capture information digitally for medical records, which was very time-consuming,” said Ching-Ting Tan, deputy superintendent of NTUH Hsin-Chu branch.
ASUS Chief Operating Officer Joe Hsieh hopes further collaboration with hospitals will create a new smart healthcare model, stating “Forward-looking technologies such as speech recognition and robotics, combined with advancements in medical care, will provide the best medical solutions.”