Mobile consulting (mConsulting) and its potential for providing access to quality healthcare for populations living in low-resource settings of low- and middle-income countries

Author:

Griffiths Frances12ORCID,Watkins Jocelyn Anstey1ORCID,Huxley Caroline1ORCID,Harris Bronwyn12,Cave Jonathan3,Pemba Senga4,Chipwaza Beatrice4,Lilford Richard1,Ajisola Motunrayo5,Arvanitis Theodoros N.6,Bakibinga Pauline7,Billah Muntasir8,Choudhury Nazratun8,Davies David1,Fayehun Olufunke5,Kabaria Caroline7,Iqbal Romaina9,Omigbodun Akinyinka5ORCID,Owoaje Eme5,Rahman Omar8ORCID,Sartori Jo1,Sayani Saleem9,Tabani Komal9ORCID,Yusuf Rita8,Sturt Jackie10

Affiliation:

1. Warwick Medical School, University of Warwick, UK

2. Centre for Health Policy, University of the Witwatersrand, South Africa

3. Department of Economics, University of Warwick, UK

4. St Francis University College of Health and Allied Sciences, Tanzania

5. University of Ibadan, Nigeria

6. Institute of Digital Healthcare, WMG, University of Warwick, UK

7. African Population and Health Research Centre, Kenya

8. Independent University Bangladesh, Bangladesh

9. Aga Khan University, Pakistan

10. The Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care, King’s College London, UK

Abstract

Objective The poorest populations of the world lack access to quality healthcare. We defined the key components of consulting via mobile technology (mConsulting), explored whether mConsulting can fill gaps in access to quality healthcare for poor and spatially marginalised populations (specifically rural and slum populations) of low- and middle-income countries, and considered the implications of its take-up. Methods We utilised realist methodology. First, we undertook a scoping review of mobile health literature and searched for examples of mConsulting. Second, we formed our programme theories and identified potential benefits and hazards for deployment of mConsulting for poor and spatially marginalised populations. Finally, we tested our programme theories against existing frameworks and identified published evidence on how and why these benefits/hazards are likely to accrue. Results We identified the components of mConsulting, including their characteristics and range. We discuss the implications of mConsulting for poor and spatially marginalised populations in terms of competent care, user experience, cost, workforce, technology, and the wider health system. Conclusions For the many dimensions of mConsulting, how it is structured and deployed will make a difference to the benefits and hazards of its use. There is a lack of evidence of the impact of mConsulting in populations that are poor and spatially marginalised, as most research on mConsulting has been undertaken where quality healthcare exists. We suggest that mConsulting could improve access to quality healthcare for these populations and, with attention to how it is deployed, potential hazards for the populations and wider health system could be mitigated.

Funder

Medical Research Council

Publisher

SAGE Publications

Subject

Health Information Management,Computer Science Applications,Health Informatics,Health Policy

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