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System for Automating Medication Orders to the Hospital Pharmacy by Nurses in Peru Through Voice Recognition

Year: 2025

Type: conference-paper

Abstract: The management of nurses' orders to a Peruvian hospital pharmacy faces efficiency challenges, which affects time spent on patient care. This context highlights the need for a system that optimizes this process. In this sense, a web-based system is proposed for the automation of orders from the nurse's cell phone, which uses a customized model for automatic speech recognition. The development of the system was divided into three stages: first, data collection with 21 orders placed by three nurses and 978 audio recordings to validate the automatic speech recognition model; second, implementation of the system allowing agile order processing; and finally, evaluation of results in terms of time and accuracy. The findings indicate that the processing time ranged from 37.70 to 60.15 seconds, representing a 97%-time reduction in operational tasks. In addition, the Word Error Rate was 10.51%, significantly lower than the 25.05% of Whisper Large V2. These results demonstrate the system's potential for adoption in various hospital contexts.

Source: International Conference on Software Engineering and Computer Science (CSECS)

DOI: 10.1109/csecs64665.2025.11009294

Authors: Conrado Moreno-Fernández, Fabian Colque-Fernández, José Luis Castillo-Sequera, Lenis Wong

Institutions: Peruvian University of Applied Sciences, Universidad de Alcalá

Language: English

Topic: Electronic Health Records Systems

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4410853448