TY - GEN
T1 - Wearable technology model to control and monitor hypertension during pregnancy
AU - Lopez, Betsy Diamar Balbin
AU - Aguirre, Jimmy Alexander Armas
AU - Coronado, Diego Antonio Reyes
AU - Gonzalez, Paola A.
N1 - Publisher Copyright:
© 2018 AISTI.
PY - 2018/6/27
Y1 - 2018/6/27
N2 - In this paper, we proposed a wearable technology model to control and monitor hypertension during pregnancy. We enhanced prior models by adding a series of health parameters that could potentially prevent and correct hypertension disorders in pregnancy. Our proposed model also emphasizes the application of real-time data analysis for the healthcare organization. In this process, we also assessed the current technologies and systems applications offered in the market. The model consists of four phases: 1. The health parameters of the patient are collected through a wearable device; 2. The data is received by a mobile application; 3. The data is stored in a cloud database; 4. The data is analyzed on real-time using a data analytics application. The model was validated and piloted in a public hospital in Lima, Peru. The preliminary results showed an increased-on number of controlled patients by 11% and a reduction of maternal deaths by 7%, among other relevant health factors that allowed healthcare providers to take corrective and preventive actions.
AB - In this paper, we proposed a wearable technology model to control and monitor hypertension during pregnancy. We enhanced prior models by adding a series of health parameters that could potentially prevent and correct hypertension disorders in pregnancy. Our proposed model also emphasizes the application of real-time data analysis for the healthcare organization. In this process, we also assessed the current technologies and systems applications offered in the market. The model consists of four phases: 1. The health parameters of the patient are collected through a wearable device; 2. The data is received by a mobile application; 3. The data is stored in a cloud database; 4. The data is analyzed on real-time using a data analytics application. The model was validated and piloted in a public hospital in Lima, Peru. The preliminary results showed an increased-on number of controlled patients by 11% and a reduction of maternal deaths by 7%, among other relevant health factors that allowed healthcare providers to take corrective and preventive actions.
KW - Data analytics
KW - Hypertension
KW - Mobile health application
KW - Pregnancy
KW - Technology
KW - Wearable
UR - https://www.scopus.com/pages/publications/85049888423
U2 - 10.23919/CISTI.2018.8399200
DO - 10.23919/CISTI.2018.8399200
M3 - Contribución a la conferencia
AN - SCOPUS:85049888423
T3 - Iberian Conference on Information Systems and Technologies, CISTI
SP - 1
EP - 6
BT - Memorias de la CISTI 2018 - 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion / Proceedings of CISTI 2018 - 13th Iberian Conference on Information Systems and Technologies
A2 - Rocha, Alvaro
A2 - Cota, Manuel Perez
A2 - Lozano-Tello, Adolfo
A2 - Goncalves, Ramiro
PB - IEEE Computer Society
T2 - 13th Iberian Conference on Information Systems and Technologies, CISTI 2018
Y2 - 13 June 2018 through 16 June 2018
ER -