Abstract
BACKGROUND: High-risk pregnancy (HRP) puts current pregnancy at an increased risk of complications. In the absence of pre-existing HRP implementation model of the country, in collaboration with the Government of Himachal Pradesh, a new digital HRP model called the 'SEWA-A System E-approach for Women at risk' was developed. The current article demonstrates a model for the early identification and line listing of high-risk pregnant women (PW) with appropriate referrals and increased engagement with the healthcare workers using a digital tool in the form of the Android App. METHODS: SEWA was implemented as a pilot intervention in two community development blocks of the Chamba district. The key implementation steps included finalizing protocols for the identification of HRPs, defining processes and roles, mapping health facilities, setting up the communication loop, and developing of digital solutions. The digital app, used by the auxiliary nurse midwife (ANM) and program officers, tracked PW for a year from October 19 to October 20 and recorded the ANC visits, referrals, and birth outcomes. A qualitative assessment was conducted among the health workers to find out their level of acceptance. RESULTS: A total of 1,340 high-risk PW were identified. The intervention year saw a rise in the identification of HRP to 27.9% from 3.5% in the previous year. A total of 2,559 conditions were tagged to the identified 1,340 women categorized into current pregnancy (81%), previous pregnancy (16%), and any existing chronic illness (3%). A majority of the women who required urgent referrals were provided referrals. The application recorded 53% of the delivered HRP with a digital birth preparedness plan, prepared and shared with the PW and Accredited Social Health Activists (ASHA), by text message for compliance. CONCLUSION: The SEWA application is a feasible and sustainable solution to complement the competency of the care providers for early identification of the high-risk conditions and reduce the burden of preventable unprecedented deaths around the time of birth.