Hazra-Ganju Aditi, Dlima Schenelle Dayna, Menezes Sonia Rebecca, Ganju Aakash, Mer Anjali
Saathealth, Mumbai, India.
Front Digit Health. 2023 Aug 25;5:1007687. doi: 10.3389/fdgth.2023.1007687. eCollection 2023.
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 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 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.
资源有限社区的人群健康意识淡薄、金融知识水平较低且难以获得初级医疗保健服务，导致预防性健康行为的采用率低、就医行为不足以及健康状况不佳。医疗服务提供者的覆盖范围和洞察力有限，限制了他们为资源有限环境设计相关产品的能力。我们的主要预防性健康干预措施，即家庭健康干预，是一种规模化的数字服务，旨在提高人们对各种健康主题的知识水平，推动积极的行为改变，并改善健康状况。本案例研究展示了我们在资源有限环境中推广这些数字健康干预措施并最大化其影响方面的经验和最佳实践。我们采用多管齐下的方法将这些干预措施进行推广，累计覆盖印度超过1000万用户：（1）通过用户研究确保所提供健康内容的本地化和文化相关性；（2）采用全渠道方法传播内容，包括使用多种内容类型和多个数字平台；（3）使用诸如游戏化和基于人工智能的预测模型等迭代产品功能；（4）利用实时分析，通过使用交互式内容引导用户使用产品和服务来调整用户的数字体验；（5）试验可持续性模式并取得了一些早期成功。从2022年2月到2023年1月，Saathealth家庭健康移动应用的下载量超过25000次，该干预措施通过移动应用、Facebook和Instagram的组合，每月在印度覆盖超过87.3万用户。我们反复观察到视频和测验是所有使用的数字渠道中最受欢迎的内容类型。我们基于人工智能的预测模型有助于提高用户留存率和内容消费量，有助于移动应用的可持续性。除了在印度覆盖大量用户外，我们的推广策略还促进了更深入的参与并改善了就医行为。我们希望这些策略有助于指导在其他资源有限环境中可持续且有影响力地推广移动健康干预措施。
