TY - GEN
T1 - Mobile application to digitize handwritten patient records in Peruvian public hospitals
AU - Villa, Wilfredo Sebastian Romero
AU - Machuca, Franco Alonso Gregorini
AU - Cornejo, Richard Nivaldo Copaja
N1 - Publisher Copyright:
© 2023 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2023
Y1 - 2023
N2 - This research has shown that public hospitals need a digitization model that allows the availability of medical records for patient medical consultation within a repository that unifies their medical information. This article presents MEDREC APP, a mobile application aimed at public hospitals of the Ministry of Health (MINSA), in order to expedite the immediate obtaining of the medical history in digital format, and to visualize their medical care. The main function of this solution is based on Optical Character Recognition (OCR) as a text extraction process by capturing images of handwritten medical history formats and registering them within the mobile application in digital format. As part of the validation process, indicators were defined, surveys and interviews were conducted with our users of the application: the medical staff. The results obtained show that the average time to obtain a medical history is between 30 and 15 minutes. By including the mobile solution to be presented, the time was reduced to 6 minutes, which means a reduction of 9 minutes, equivalent to approximately 70%.
AB - This research has shown that public hospitals need a digitization model that allows the availability of medical records for patient medical consultation within a repository that unifies their medical information. This article presents MEDREC APP, a mobile application aimed at public hospitals of the Ministry of Health (MINSA), in order to expedite the immediate obtaining of the medical history in digital format, and to visualize their medical care. The main function of this solution is based on Optical Character Recognition (OCR) as a text extraction process by capturing images of handwritten medical history formats and registering them within the mobile application in digital format. As part of the validation process, indicators were defined, surveys and interviews were conducted with our users of the application: the medical staff. The results obtained show that the average time to obtain a medical history is between 30 and 15 minutes. By including the mobile solution to be presented, the time was reduced to 6 minutes, which means a reduction of 9 minutes, equivalent to approximately 70%.
KW - Digitalization
KW - Digitization
KW - Medical Records
KW - Optical Character Recognition
KW - Optical Character Recognition
KW - Public Hospitals
UR - https://www.scopus.com/pages/publications/85172304183
M3 - Contribución a la conferencia
AN - SCOPUS:85172304183
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - Proceedings of the 21st LACCEI International Multi-Conference for Engineering, Education and Technology
A2 - Larrondo Petrie, Maria M.
A2 - Texier, Jose
A2 - Matta, Rodolfo Andres Rivas
PB - Latin American and Caribbean Consortium of Engineering Institutions
T2 - 21st LACCEI International Multi-Conference for Engineering, Education and Technology, LACCEI 2023
Y2 - 19 July 2023 through 21 July 2023
ER -