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Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies

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...

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Autores principales: Gupta, Anil, Agrawal, Ritu, Gupt, Anadi, Guleri, Rajesh, Bajpayee, Devina, Joshi, Naresh, Sarin, Enisha, Gupta, Sachin, Kumar, Harish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8653496/
https://www.ncbi.nlm.nih.gov/pubmed/34934670
http://dx.doi.org/10.4103/jfmpc.jfmpc_466_21
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author Gupta, Anil
Agrawal, Ritu
Gupt, Anadi
Guleri, Rajesh
Bajpayee, Devina
Joshi, Naresh
Sarin, Enisha
Gupta, Sachin
Kumar, Harish
author_facet Gupta, Anil
Agrawal, Ritu
Gupt, Anadi
Guleri, Rajesh
Bajpayee, Devina
Joshi, Naresh
Sarin, Enisha
Gupta, Sachin
Kumar, Harish
author_sort Gupta, Anil
collection PubMed
description 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.
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spelling pubmed-86534962021-12-20 Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies Gupta, Anil Agrawal, Ritu Gupt, Anadi Guleri, Rajesh Bajpayee, Devina Joshi, Naresh Sarin, Enisha Gupta, Sachin Kumar, Harish J Family Med Prim Care Original Article 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. Wolters Kluwer - Medknow 2021-10 2021-11-05 /pmc/articles/PMC8653496/ /pubmed/34934670 http://dx.doi.org/10.4103/jfmpc.jfmpc_466_21 Text en Copyright: © 2021 Journal of Family Medicine and Primary Care https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Gupta, Anil
Agrawal, Ritu
Gupt, Anadi
Guleri, Rajesh
Bajpayee, Devina
Joshi, Naresh
Sarin, Enisha
Gupta, Sachin
Kumar, Harish
Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies
title Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies
title_full Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies
title_fullStr Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies
title_full_unstemmed Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies
title_short Systems E-approach for women at risk (SEWA)—A digital health solution for detection of high-risk pregnancies
title_sort systems e-approach for women at risk (sewa)—a digital health solution for detection of high-risk pregnancies
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8653496/
https://www.ncbi.nlm.nih.gov/pubmed/34934670
http://dx.doi.org/10.4103/jfmpc.jfmpc_466_21
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