IIT Roorkee, AIIMS Delhi develop ‘SwasthGarbh’ mobile app for pregnant women

Researchers at the Indian Institute of Technology (IIT) Roorkee and AIIMS Delhi have developed a mobile application, ‘SwasthGarbh’, for providing antenatal care and real-time medical support to pregnant women. According to officials, this is the first pregnancy app that provides instantaneous access to doctor’s advice and is clinically endorsed as well as credible and this can be a vital tool for women in rural areas and those who do not have easy access to doctors.

“The utility of telemedicine in healthcare has been brought to the forefront by the COVID-19 pandemic. The smartphone, with over one billion users worldwide, has tremendous potential to transform the field of medical sciences and improve healthcare,” said K K Pant, Director, IIT Roorkee.

The app is aimed at assisting pregnant women by ensuring timely antenatal care visits, recording every clinical test and improving medication adherence.

“As higher neonatal mortality rate is an alarming concern, SwasthGarbh mobile app will provide real-time medical support to all pregnant women and improve maternal-fetal health,” said Deepak Sharma, Department of Biosciences and Bioengineering, IIT Roorkee.

Rama Chaudhry, Dean (Research), AIIMS New Delhi, said, “The app will be quite useful for providing potential solutions to common problems in pregnancy. Our goal is to make the SwasthGarbh app reach every household of our country and thus save precious maternal-fetal lives.”

She explained that the clinical assessment of 150 patients demonstrated the utility of the app in improving the quality of antenatal care and reducing complications.

The patients registered on the app showed a significantly higher number of mean antenatal visits and better compliance with the WHO guidelines. It also helps in better counselling of patients regarding the formulation of birth plans and the management of physiological problems encountered in pregnancy.

“The benefits of the app increase further during pandemic situations when patients are afraid to visit hospitals due to the risk of catching coronavirus infection, or are unable to do so due to countrywide lockdowns or movement restrictions. In future, we will use machine learning to predict the possibility of occurrence of any abnormality or disease so that timely intervention can be given,” he said.

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