Towards an On-line Handwriting Recognition Interface for Health Service Providers using Electronic Medical Records

• Main Authors: Dela Cruz, Viktor Mikhael, Pulmano, Christian E, Estuar, Ma. Regina Justina E
• Format: text
• Published: Archīum Ateneo 2020
• Subjects: electronic health records; handwriting recognition; health informatics; usability; Computer Sciences; Databases and Information Systems; Health and Medical Administration; Health Information Technology
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/268; https://www.scitepress.org/Link.aspx?doi=10.5220/0008944403830390
• Institution: Ateneo De Manila University

The 2019 Universal Health Care Act in the Philippines has allowed healthcare service providers to have a second look at using electronic medical records (EMRs) in their practice with tools that enable servicing the poorest of the poor and coursing payments via EMR. A review of first world country narratives, however, show evidence of the substandard usability of EMRs. Physician work is impeded as almost two-thirds of consultation time is spent documenting on an EMR instead conversing with patients face-to-face. This paper describes a handwriting recognition interface for EMR data entry that is user-friendly and is unobstructive to the patient-physician relationship. An initial prototype tested by medical students showed a handwriting recognition accuracy of 34% while a second testing by health service providers showed a handwriting recognition accuracy of 42%. Findings show that recognition is challenged by specialized words and accidental markings which cause extra spaces and extra symbols. Additional features to the system as well as possible augmentations to improve accuracy and efficiency through ontology, machine learning, and AI are also roadmapped.