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. (April 2020)

• Record Type: Journal Article
• Authors: Griffiths, Frances; Watkins, Jocelyn Anstey; Huxley, Caroline; Harris, Bronwyn; Cave, Jonathan; Pemba, Senga; Chipwaza, Beatrice; Lilford, Richard; Ajisola, Motunrayo; Arvanitis, Theodoros N.; Bakibinga, Pauline; Billah, Muntasir; Choudhury, Nazratun; Davies, David; Fayehun, Olufunke; Kabaria, Caroline; Iqbal, Romaina; Omigbodun, Akinyinka; Owoaje, Eme; Rahman, Omar; Sartori, Jo; Sayani, Saleem; Tabani, Komal; Yusuf, Rita; Sturt, Jackie
• Is Part Of: Digital health. Volume 6(2020)
• Publication Date: 2020-04
• Subjects: mHealth -- mConsulting -- mobile consulting -- remote consultation -- healthcare -- low-and middle-income countries -- slums -- rural areas; Medical care -- Data processing -- Periodicals; Medical informatics -- Periodicals; 362.10285
• DOI: 10.1177/2055207620919594
• Languages: English
• ISSNs: 2055-2076

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.