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An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study
Populations in resource-limited communities have low health awareness, low financial literacy levels, and inadequate access to primary healthcare, leading to low adoption of preventive health behaviours, low healthcare-seeking behaviours, and poor health outcomes. Healthcare providers have limited r...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486013/ https://www.ncbi.nlm.nih.gov/pubmed/37693341 http://dx.doi.org/10.3389/fdgth.2023.1007687 |
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author | Hazra-Ganju, Aditi Dlima, Schenelle Dayna Menezes, Sonia Rebecca Ganju, Aakash Mer, Anjali |
author_facet | Hazra-Ganju, Aditi Dlima, Schenelle Dayna Menezes, Sonia Rebecca Ganju, Aakash Mer, Anjali |
author_sort | Hazra-Ganju, Aditi |
collection | PubMed |
description | Populations in resource-limited communities have low health awareness, low financial literacy levels, and inadequate access to primary healthcare, leading to low adoption of preventive health behaviours, low healthcare-seeking behaviours, and poor health outcomes. Healthcare providers have limited reach and insights, limiting their ability to design relevant products for resource limited settings. Our primary preventive health intervention, called the Saathealth family health interventions, is a scaled digital offering that aims to improve knowledge levels on various health topics, nudge positive behaviour changes, and drive improved health outcomes. This case study presents our learnings and best practices in scaling these digital health interventions in resource-limited settings and maximising their impact. We scaled the Saathealth interventions to cumulatively reach >10 million users across India using a multi-pronged approach: (1) ensuring localization and cultural relevance of the health content delivered through user research; (2) disseminating content using omni-channel approaches, which involved using diverse content types and multiple digital platforms; (3) using iterative product features such as gamification and artificial intelligence-based (AI-based) predictive models; (4) using real-time analytics to adapt the user's digital experience by using interactive content to drive them towards products and services and (5) experiments with sustainability models to yield some early successes. The Saathealth family health mobile app had >25,000 downloads and the intervention reached >873,000 users in India every month through the mobile app, Facebook, and Instagram combined, from the time period of February 2022 to January 2023. We repeatedly observed videos and quizzes to be the most popular content types across all digital channels being used. Our AI-based predictive models helped improve user retention and content consumption, contributing to the sustainability of the mobile apps. In addition to reaching a high number of users across India, our scaling strategies contributed to deepened engagement and improved health-seeking behaviour. We hope these strategies help guide the sustainable and impactful scaling of mobile health interventions in other resource-limited settings. |
format | Online Article Text |
id | pubmed-10486013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104860132023-09-09 An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study Hazra-Ganju, Aditi Dlima, Schenelle Dayna Menezes, Sonia Rebecca Ganju, Aakash Mer, Anjali Front Digit Health Digital Health Populations in resource-limited communities have low health awareness, low financial literacy levels, and inadequate access to primary healthcare, leading to low adoption of preventive health behaviours, low healthcare-seeking behaviours, and poor health outcomes. Healthcare providers have limited reach and insights, limiting their ability to design relevant products for resource limited settings. Our primary preventive health intervention, called the Saathealth family health interventions, is a scaled digital offering that aims to improve knowledge levels on various health topics, nudge positive behaviour changes, and drive improved health outcomes. This case study presents our learnings and best practices in scaling these digital health interventions in resource-limited settings and maximising their impact. We scaled the Saathealth interventions to cumulatively reach >10 million users across India using a multi-pronged approach: (1) ensuring localization and cultural relevance of the health content delivered through user research; (2) disseminating content using omni-channel approaches, which involved using diverse content types and multiple digital platforms; (3) using iterative product features such as gamification and artificial intelligence-based (AI-based) predictive models; (4) using real-time analytics to adapt the user's digital experience by using interactive content to drive them towards products and services and (5) experiments with sustainability models to yield some early successes. The Saathealth family health mobile app had >25,000 downloads and the intervention reached >873,000 users in India every month through the mobile app, Facebook, and Instagram combined, from the time period of February 2022 to January 2023. We repeatedly observed videos and quizzes to be the most popular content types across all digital channels being used. Our AI-based predictive models helped improve user retention and content consumption, contributing to the sustainability of the mobile apps. In addition to reaching a high number of users across India, our scaling strategies contributed to deepened engagement and improved health-seeking behaviour. We hope these strategies help guide the sustainable and impactful scaling of mobile health interventions in other resource-limited settings. Frontiers Media S.A. 2023-08-25 /pmc/articles/PMC10486013/ /pubmed/37693341 http://dx.doi.org/10.3389/fdgth.2023.1007687 Text en © 2023 Hazra-Ganju, Dlima, Menezes, Ganju and Mer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Hazra-Ganju, Aditi Dlima, Schenelle Dayna Menezes, Sonia Rebecca Ganju, Aakash Mer, Anjali An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
title | An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
title_full | An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
title_fullStr | An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
title_full_unstemmed | An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
title_short | An omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
title_sort | omni-channel, outcomes-focused approach to scale digital health interventions in resource-limited populations: a case study |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10486013/ https://www.ncbi.nlm.nih.gov/pubmed/37693341 http://dx.doi.org/10.3389/fdgth.2023.1007687 |
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