Assessing a digital technology-supported community child health programme in India using the Social Return on Investment framework.
Assessing a digital technology-supported community child health programme in India using the Social Return on Investment framework.
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DOI：
10.1371/journal.pdig.0000363
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发表时间：
2023-11
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2020年估计有500万5岁以下儿童死亡，其中82%发生在撒哈拉以南非洲和南亚。孟买超过三分之一的人口获得医疗保健的机会有限，城市贫困人口的儿童健康状况尤其严重。我们描述了孟买基于数字技术的儿童健康方案的实施情况，并评估了其整体影响。利用人工智能（AI）驱动的移动健康平台，我们制定了以社区为基础的儿童健康管理方案。该方案利用现有的社区卫生工作者队伍，旨在加强分诊和转诊，改善社区获得卫生保健的机会，并减少对医院的依赖。社会投资回报（SROI）框架用于评估整体影响。该方案将在社区接受治疗的疾病比例从4%提高到76%，从而减少了住院和向私人医疗保健提供者支付的自付费用。总投资2,632,271印度卢比（INR），社会回报为34,435,827印度卢比，SROI比率为13。该方案每年为每个儿童支付的费用为625印度卢比。在人工智能驱动的决策支持工具的帮助下，提高卫生保健员等现有劳动力的技能，有可能将关键卫生服务的能力扩展到社区环境中。本研究为使用SROI等循证工具评估卫生技术的整体影响提供了蓝图。这些发现适用于所有收入环境，为促进技术支持的干预措施提供了明确的理由，以加强医疗保健服务。2020年估计有500万5岁以下儿童死亡，其中82%发生在撒哈拉以南非洲和南亚。孟买超过三分之一的人口难以获得医疗保健，城市贫困人口的儿童健康状况尤其严重。在本文中，我们报告了一项数字技术支持计划的实施情况，该计划旨在加强孟买贫民窟儿童疾病的社区管理。通过使用由社区卫生工作者操作的人工智能驱动的移动平台增加适当的分诊和转诊，该规划将社区成功治疗的疾病发作比例从4%提高到76%，从而减少了住院治疗和患者及其家属的自付支出。我们的分析表明，该项目的总投资产生了13倍的社会回报，每投资印度卢比（INR），每个孩子的年成本为625印度卢比。本文重点介绍了一种新型人工智能临床决策支持平台的实施，以改善社区卫生服务。本文讨论了几项引人注目且与政策高度相关的发现，这些发现适用于所有收入环境，为促进通过技术支持的卫生规划加强初级卫生保健服务的干预措施提供了明确的理由。
An estimated 5.0 million children aged under 5 years died in 2020, with 82% of these deaths occurring in sub-Saharan Africa and southern Asia. Over one-third of Mumbai’s population has limited access to healthcare, and child health outcomes are particularly grave among the urban poor. We describe the implementation of a digital technology-based child health programme in Mumbai and evaluate its holistic impact. Using an artificial intelligence (AI)-powered mobile health platform, we developed a programme for community-based management of child health. Leveraging an existing workforce, community health workers (CHW), the programme was designed to strengthen triage and referral, improve access to healthcare in the community, and reduce dependence on hospitals. A Social Return on Investment (SROI) framework is used to evaluate holistic impact. The programme increased the proportion of illness episodes treated in the community from 4% to 76%, subsequently reducing hospitalisations and out-of-pocket expenditure on private healthcare providers. For the total investment of Indian Rupee (INR) 2,632,271, the social return was INR 34,435,827, delivering an SROI ratio of 13. The annual cost of the programme per child was INR 625. Upskilling an existing workforce such as CHWs, with the help of AI-driven decision- support tools, has the potential to extend capacity for critical health services into community settings. This study provides a blueprint for evaluating the holistic impact of health technologies using evidence-based tools like SROI. These findings have applicability across income settings, offering clear rationale for the promotion of technology-supported interventions that strengthen healthcare delivery. An estimated 5.0 million children under 5 years of age died in 2020, with 82% of these deaths occurring in sub-Saharan Africa and southern Asia. More than one-third of Mumbai’s population has poor access to healthcare, and child health outcomes are particularly grave among the urban poor. In this paper, we report on the implementation of a digital-technology supported programme for strengthening community-based management of childhood diseases in Mumbai’s slums. By augmenting appropriate triage and referral using an artificial intelligence (AI)-driven mobile platform operated by community health workers, the programme increased the proportion of illness episodes successfully treated in the community from 4% to 76%, subsequently reducing hospitalisations and out-of-pocket expenditures for patients and their families. Our analysis showed that the total investment for the project yielded a 13-fold social return for each Indian Rupee (INR) invested, with an annual cost per child of INR 625. This paper highlights the implementation of a novel AI-powered clinical decision-support platform to improve community-based health services. Several compelling and highly policy-relevant findings that have applicability across income settings, offering clear rationale for the promotion of interventions that strengthen primary healthcare delivery through technology-supported health programmes are discussed.