Elsevier

World Development

Volume 104, April 2018, Pages 358-374
World Development

The struggle for digital inclusion: Phones, healthcare, and marginalisation in rural India

https://doi.org/10.1016/j.worlddev.2017.12.023Get rights and content

Highlights

  • This study relates to the social implications of (mobile) technology diffusion.

  • I hypothesise that phone diffusion undermines non-adopters’ healthcare access.

  • I use a panel of 12,003 sick households across rural India in 2005 and 2012.

  • Poor non-adopters’ access to private healthcare worsens during fast diffusion.

  • Wealthier households and public healthcare access are insulated from this trend.

Abstract

The gains from digital technology diffusion are deemed essential for international development, but they are also distributed unevenly. Does the uneven distribution mean that not everyone benefits from new technologies to the same extent, or do some people experience an absolute disadvantage during this process? I explore this question through the case study of curative healthcare access in the context of rapid mobile phone uptake in rural India, contributing thus to an important yet surprisingly under-researched aspect of the social implications of (mobile) technology diffusion.

Inspired by a previous analysis of cross-sectional data from rural India, I hypothesise that health systems increasingly adapt to mobile phone users where phones have diffused widely. This adaptation will leave poor non-adopters worse off than before and increases healthcare inequities. I use a panel of 12,003 rural households with an illness in 2005 and 2012 from the Indian Human Development Survey to test this hypothesis. Based on village-cluster robust fixed-effects linear probability models, I find that (a) mobile phone diffusion is significantly and negatively linked to various forms of rural healthcare access, suggesting that health systems increasingly adapt to phone use and discriminate against non-users; that (b) poor rural households without mobile phones experience more adverse effects compared to more affluent households, which indicates a struggle and competition for healthcare access among marginalised groups; and that (c) no effects emerge for access to public doctors, which implies that some healthcare providers are less responsive to mobile phone use than others.

Overall, my findings indicate that the rural Indian healthcare system gradually adapts to increasing mobile phone use at the expense of non-users. I conclude that rapid mobile phone diffusion creates an opportunity to improve people’s access to healthcare in rural India, but it also creates new forms of marginalisation among poor rural households.

Introduction

It is a common stance that the diffusion of information and communication technology (ICT) is essential for development (Aker and Mbiti, 2010, Donner, 2015, Heeks, 2008), but what if the process of digital inclusion is a struggle that leaves excluded groups worse off than before? I investigate this question through the case study of phone-aided curative healthcare access in rural India between 2005 and 2012, demonstrating that the increased availability of mobile phones intensifies competition for scarce healthcare services among poor rural households. While poor phone owners enjoy more access to private doctors in contexts of rapid mobile phone diffusion, the slow-growing supply of healthcare and a system that caters increasingly to phone users mean that poor households without mobile phones see their access to healthcare diminish. Left to their own devices, mobile phone adopters thus outcompete non-adopters in the struggle for scarce rural healthcare services.1 All the while, more affluent households with a broader range of options to access healthcare are insulated from these developments.

This research was motivated by the literature on “digital divides” and “information and communication technologies and development” (ICTD), which has begun to examine the inequalities of technology adoption (Donner, 2015:137–154; Graham, Hogan, Straumann, & Medhat, 2014:758–759; Napoli and Obar, 2014, Schroeder, 2015; van Dijk, 2005:22), but which tends to assume that diffusion itself is desirable and that nobody experiences an absolute disadvantage through it. Contrary to this position, an earlier mixed-methods research project on healthcare-related mobile phone use in rural India and rural China suggested that widespread mobile phone use can lead to an adverse over-utilisation of resource-constrained rural healthcare systems, which can leave digitally excluded groups at a growing disadvantage (Haenssgen & Ariana, 2017b). Because the cross-sectional study was not designed to capture long-term and systemic effects of mobile phone diffusion, the present paper uses India-wide panel data from the Indian Human Development Survey (IHDS; Desai et al., 2010b; Desai, Vanneman, & National Council of Applied Economic Research., 2016). Adopting a process perspective of mobile-phone-aided healthcare access, I hypothesise that the increasing spread of mobile phones in rural India worsens healthcare access for digitally excluded households.

This paper contributes to the interdisciplinary study of the social implications of technology diffusion in general, and to the study of digital divides and inclusive innovation in the field of ICTD in particular. It advances the conceptualisation of digital inclusion through an empirically grounded process framework of technology adoption that appreciates dynamic and systemic effects of mobile phone diffusion on healthcare access in rural, resource-constrained areas. Empirically, it provides the first quantitative evidence that the healthcare access of digitally excluded groups deteriorates with increasing mobile phone diffusion, which challenges the framing of mobile phones as an inclusive innovation and of digital inclusion as an unproblematic process. The tools and findings of this paper offer space for further research in other areas of digital development, like employment, government service access, or social interaction.

The remainder of this paper situates the study in the fields of technology adoption and ICTD, followed by a detailed description of the analytical framework (Section 2). Section 3 explains the empirical model to analyse the household panel data from the IHDS, using fixed-effects linear probability models with village-cluster robust standard errors to estimate households’ probability to access healthcare as a function of mobile phone adoption and district-level phone diffusion. The results are described in Section 4, showing that households who failed to acquire a mobile phone between 2005 and 2012 are on average poorer, and that poor households without mobile phones are less likely to gain access to “responsive” private healthcare providers if mobile phones have otherwise diffused widely in their district. Section 5 will argue that the results correspond to the analytical framework. On the demand side, diffusion drives competition and creates divides between poor phone users and non-users. On the supply side, healthcare providers who are more responsive to patients’ mobile phone use will increasingly cater to this group at the expense of non-users. That public healthcare access is yet unaffected by these trends should only offer momentary respite, given that my previous cross-sectional study in 2013–2014 indicated that public providers in rural India have begun to adapt to patients’ mobile phone use, too. Section 6 concludes.

Section snippets

Technology Diffusion, ICTD, and digital divides in the context of mobile phones

This paper speaks to the literature on digital divides and “information and communication technologies and development” (ICTD) as part of the broader, interdisciplinary study of the social implications of technology diffusion. Two key insights from the broader field—comprising anthropological, sociological, and economic research—are that (a) technology diffusion has both positive and negative consequences for social, economic, and political development; and that (b) these implications are not

Materials and methods

I base my analysis on recently published panel data from the nationwide Indian Human Development Survey (IHDS; Desai et al., 2010b; Desai et al., 2016), which was carried out in two waves in 2004–2005 and 2011–2012. Wave I included 41,554 households with 215,754 individuals; Wave II surveyed 42,152 households with 204,569 individuals. The panel data structure in the IHDS allows for the matching of households over the two survey periods, yet not of individuals. The analysis therefore involves

Indian health system context

The study period from 2004 to 2012 was shaped by the introduction of the National Rural Health Mission (NRHM) in 2005, established to improve the health status of the Indian population in general, but also to integrate the hitherto fragmented health programmes landscape in India under a common umbrella (MoHFW, 2002: §2.3.2.1; Prasad & Sathyamala, 2006:13). This section describes the India healthcare system, the changes associated with the introduction of the NRHM, and the continuing challenges

Limitations

While I have already hinted at a possible interpretation of the results in the previous section, it is important to consider at least three important limitations of the analysis before discussing its significance. Firstly, it could be considered problematic that the severity of illness, which controls for households’ healthcare access, is defined by the survey agency rather than by the respondents themselves. Individuals’ initial decisions to seek care are more likely to be driven by their own 

Conclusion

Challenging the framing of “digital inclusion” as an unproblematic process, this paper explored the relationship between mobile phone diffusion and rural Indian households’ access to curative healthcare. Based on previous research in rural India, I hypothesised that households without mobile phones are increasingly disadvantaged in their healthcare access if mobile phones diffuse rapidly in their environment. This assumed that health systems comprise actors with different degrees of

Funding sources

This research arises from research funded by the John Fell Oxford University Press (OUP) Research Fund (Ref. 122/670). I gratefully acknowledge financial support from the UK Economic and Social Research Council (Ref. SSD/2/2/16), the Scatcherd European Scholarship (Ref. GAF1213_SES_511446), the Oxford Department of International Development, the University of Oxford Vice-Chancellors’ Fund, and Hertford College.

Conflicts of interest

I declare that no conflict of interest, financial or otherwise, exists.

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