ILITIA: telehealth architecture for high-risk gestation classification
Res. Biomed. Eng. (Online)
;
33(3): 237-246, Sept. 2017. tab, graf
Article
in English
| LILACS
| ID: biblio-896189
ABSTRACT
Abstract Introduction According to the World Health Organization, about 9.2% of the 28 million newborns worldwide are stillborn. Besides, about 358,000 women died due to complications related to pregnancy in 2015. Part of these deaths could have been avoided with improving prenatal care agility to recognize problems during pregnancy. Based on that, many efforts have been made to provide technologies that can contribute to offer better access to information and assist in decision-making. In this context, this work presents an architecture to automate the classification and referral process of pregnant women between the basic health units and the referral hospital through a Telehealth platform. Methods The Telehealth architecture was developed in three components: The data acquisition component, responsible for collecting and inserting data; the data processing component, which is the core of the architecture implemented using expert systems to classify gestational risk; and the post-processing component, in charge of the delivery and analysis of cases. Results Acceptance test, system accuracy test based on rules and performance test were realized. For the tests, 1,380 referral forms of real situations were used. Conclusion On the results obtained with the analysis of real data, ILITIA, the developed architecture has met the requirements to assist medical specialists on gestational risk classification, which decreases the inconvenience of pregnant women displacement and the resulting costs.
Full text:
Available
Index:
LILACS (Americas)
Type of study:
Etiology study
/
Risk factors
Language:
English
Journal:
Res. Biomed. Eng. (Online)
Journal subject:
Engenharia Biomdica
Year:
2017
Type:
Article
Affiliation country:
Brazil
Institution/Affiliation country:
Federal University of Rio Grande do Norte/BR
Similar
MEDLINE
...
LILACS
LIS