EconPapers    
Economics at your fingertips  
 

Assessing a digital technology-supported community child health programme in India using the Social Return on Investment framework

Manasi Patil, Athar Qureshi, Elina Naydenova, Anand Bang, Jay Halbert, Maarten De Vos, Poornima Nair, Madhumita Patil and Melissa M Medvedev

PLOS Digital Health, 2023, vol. 2, issue 11, 1-14

Abstract: 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.Author summary: 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.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000363 (text/html)
https://journals.plos.org/digitalhealth/article/fi ... 00363&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pdig00:0000363

DOI: 10.1371/journal.pdig.0000363

Access Statistics for this article

More articles in PLOS Digital Health from Public Library of Science
Bibliographic data for series maintained by digitalhealth ().

 
Page updated 2025-05-31
Handle: RePEc:plo:pdig00:0000363