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Introduction India has become a lighthouse for large-scale digital innovation in the health sector, particularly for front-line health workers (FLHWs). However, among scaled digital health solutions, ensuring sustainability remains elusive. This study explores the factors underpinning scale-up of digital health solutions for FLHWs in India, and the potential implications of these factors for sustainability. Methods We assessed five FLHW digital tools scaled at the national and/or state level in India. We conducted in-depth interviews with implementers, technology and technical partners (n=11); senior government stakeholders (n=5); funders (n=1) and evaluators/academics (n=3). Emergent themes were grouped according to a broader framework that considered the (1) digital solution; (2) actors; (3) processes and (4) context. Results The scale-up of digital solutions was facilitated by their perceived value, bounded adaptability, support from government champions, cultivation of networks, sustained leadership and formative research to support fit with the context and population. However, once scaled, embedding digital health solutions into the fabric of the health system was hampered by challenges related to transitioning management and ownership to government partners; overcoming government procurement hurdles; and establishing committed funding streams in government budgets. Strong data governance, continued engagement with FLHWs and building a robust evidence base, while identified in the literature as critical for sustainability, did not feature strongly among respondents. Sustainability may be less elusive once there is more consensus around the roles played between national and state government actors, implementing and technical partners and donors. Conclusion The use of digital tools by FLHWs offers much promise for improving service delivery and health outcomes in India. However, the pathway to sustainability is bespoke to each programme and should be planned from the outset by investing in people, relationships and service delivery adjustments to navigate the challenges involved given the dynamic nature of digital tools in complex health systems.
We developed a conceptual framework to study what shapes scale-up and sustainability of digital tools for FLHWs (figure 1), reflecting broader literature on the subject.6 8 10 13 31 34–37 Our framework was adapted from the following existing conceptual frameworks by taking into account variables relevant to the implementation of digital tools in resource-constrained settings: (1) Greenhalgh et al’s framework taking into account complexity of scaling-up technology-supported programmes13; (2) Gericke et al’s framework which has been applied to assess the scale-up of mHealth innovations in Malawi and Zambia31; (3) Spicer et al’s framework based on studying scalable health innovations’ attributes in Ethiopia, India and Nigeria10 and (4) Gilson and Walt’s policy triangle.38 Doing so enabled us to simplify relevant variables into four themes: (1) digital solution characteristics, (2) actor roles and relationships, (3) implementation processes and (4) context. While drawing from existing frameworks for scaling and sustaining health interventions more generally, our work particularly takes into account specific ‘hardware’(eg, cloud storage) and ‘software’ (eg, technological partnerships) required to scale and sustain digital health solutions. In 2011, India’s population was 1.2 billion, with nearly three-quarters (74%) being literate.39 Mobile phone access in India has rapidly increased, with the 2015–2016 National Family Health Survey (NHFS) reporting 90% of households having access to mobile phones. However, less than half of women surveyed (46%) have access to mobile phones.40 India has a federal health system structure, where health is a state subject but national government defines key strategies and programmes.41 For example, the Ministry of Health and Family Welfare (MoHFW) is responsible for national programmes for health and family welfare, prevention and control of communicable diseases, promotion of traditional and indigenous systems of medicines, and setting standards and guidelines, which state governments can adapt. Additionally, The Ministry of Women and Child Development (MoWCD) is responsible, among other programmes, for implementing the Integrated Child Development Services (ICDS) programme, in collaboration with the MoHFW, which provides a package of services including supplementary nutrition, immunisation, health check-ups and referral services, and preschool education. The 2015–2016 NHFS reported that utilisation of key maternal and newborn health services are variable and characterised by breaks in the continuity of care. While most women (83%) attend at least one antenatal care visit, only half (51%) receive the recommended four visits. Despite high skilled birth attendance (81%), provision of postnatal care is uneven for mothers and newborns; with only 65% of mothers and 27% of newborns receiving postnatal care within 2 days of birth.40 In this study, programmes were considered to be sufficiently scaled up to serve as case studies if they were reaching a large proportion of eligible FLHWs across at least one state in India. Case studies of varying complexity were selected based on three features. First, our cases showcase a range of technical features such as data capture, decision-support, direct-to-FLHW health information messages. Second, they are at different levels of maturity in terms of scale and sustainability, which enabled us to explore differences in their experiences in scaling and varying levels of success in being sustained. And third, they are geographically diverse, enabling an examination of contrasting Indian governmental state capacities. Our cases and respective digital tools are as follows: (1) TECHO +in Gujarat; (2) Mobile Academy (MA) in Gujarat and Madhya Pradesh; (3) Anmol in Madhya Pradesh and at national level; (4) the non-communicable diseases (NCDs) App at the national level and (5) Common Application Software (CAS) at the national level. Table 1 compares and contrasts each case study in terms of their components and functions, actors involved and coverage. Case study overview FLHW, front-line health workers; MoWCD, Ministry of Women and Child Development; NCD, non-communicable diseases. We conducted semistructured in-depth interviews with respondents identified using investigator contacts and snowball sampling in person in New Delhi, Bangalore, Bhopal and Ahmedabad from May to October 2019, and remotely using Zoom software from July to October 2020. Respondents were sampled from the following categories: technology partners, implementers and technical partners (n=11); senior government stakeholders who had played key roles in commissioning, scaling and/sustaining the digital tools (n=5); funders (n=1) and evaluators/academics (n=3) (table 2). Our sample size was limited due to COVID-19 pandemic starting in the middle of our study, which impacted respondents’ availability, as well as our ability to follow up with them in person. However, several respondents (n=7) had in-depth knowledge of multiple cases: MA (n=8); TECHO+ (n=5); ANMOL (n=5); NCD app (n=4); CAS (n=9). Key informants Interviewed by respondent type with knowledge of specific case studies *Respondents across categories had knowledge of multiple cases: Mobile Academy (n=8); TECHO+ (n=5); ANMOL (n=5); NCD app (n=4); CAS (n=9). †One respondent (KI07) is classified as both a technology partner/implementer and academic. NCD, non-communicable diseases. Research began by introducing the participant to the study, providing them with an information sheet and consent form for the study, and obtaining and recording verbal consent only after giving them sufficient time to consider whether or not to participate in the research and answering any questions they may have. Interviews were conducted in English using a semistructured interview guide covering domains in the conceptual framework (figure 1). Interviews lasted approximately 1–1.5 hours. At the end of each interview, respondents were asked if they knew anyone with experience relevant to the subject of our research. Researchers took detailed notes and audio recorded each interview, which was transcribed for analysis. Analysis involved the following stages: NSS and KS systematically coded the interview transcripts using Dedoose software, adopting a framework approach whereby a priori and emerging themes were applied. KS prepared a detailed synthesis report that summarised findings by emerging themes and NSS, KS, AG and AEL participated in an analysis workshop, where emerging findings were reviewed and jointly agreed and the conceptual framework for the study was revised to reflect the study’s findings. Data were then revisited using the revised conceptual framework with the paper drafted by NSS with inputs from KS and reviewed by all authors to confirm the findings are accurately and coherently presented. We followed Noble and Smith’s recommended steps to enhance the validity and reliability of qualitative data collection and analysis, including accounting for personal biases, frequent communication with all researchers in the study team and ongoing critical reflection of methods to ensure sufficient depth and relevance of data collection and analysis.42 We operationalised these steps through convening planning and debrief meetings before and after each KI to: revisit the interview guide and focus our interview strategy, discuss the detailed interview notes and high level summary comments, and continually re-evaluate our impressions and interpretations of responses to ensure that personal bias was minimised. A preliminary analysis report was also reviewed by the team and discussed at length before proceeding with drafting the manuscript. Given the nature of our study—a high-level policy analysis—it was not appropriate to involve patients or the public in our research.
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