mHealth for Clinical Decision-Making in Sub-Saharan Africa: A Scoping Review.
BACKGROUND
In a bid to deliver quality health services in resource-poor settings, mobile health (mHealth) is increasingly being adopted. The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms, and evidence-based guidelines, for example, is established in resource-rich settings. However, the extent to which mobile clinical decision support systems (mCDSS) have been adopted specifically in resource-poor settings such as Africa and the lessons learned about their use in such settings are yet to be established.


OBJECTIVE
The aim of this study was to synthesize evidence on the use of mHealth for point-of-care decision support and improved quality of care by health care workers in Africa.


METHODS
A scoping review of 4 peer-reviewed and 1 grey literature databases was conducted. No date limits were applied, but only articles in English language were selected. Using pre-established criteria, 2 reviewers screened articles and extracted data. Articles were analyzed using Microsoft Excel and MAXQDA.


RESULTS
We retained 22 articles representing 11 different studies in 7 sub-Saharan African countries. Interventions were mainly in the domain of maternal health and ranged from simple text messaging (short message service, SMS) to complex multicomponent interventions. Although health workers are generally supportive of mCDSS and perceive them as useful, concerns about increased workload and altered workflow hinder sustainability. Facilitators and barriers to use of mCDSS include technical and infrastructural support, ownership, health system challenges, and training.


CONCLUSIONS
The use of mCDSS in sub-Saharan Africa is an indication of progress in mHealth, although their effect on quality of service delivery is yet to be fully explored. Lessons learned are useful for informing future research, policy, and practice for technologically supported health care delivery, especially in resource-poor settings.
Athena Institute for Research on Innovation and Communication in Health and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.|Institute of Tropical Medicine, Maternal and Reproductive Health Unit, Department of Public Health, Antwerp, Belgium.
Ibukun-Oluwa Omolade
http://orcid.org/0000-0003-0139-0541
IO
Adepoju
Athena Institute for Research on Innovation and Communication in Health and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Bregje Joanna Antonia
http://orcid.org/0000-0003-2243-2907
BJ
Albersen
Institute of Tropical Medicine, Maternal and Reproductive Health Unit, Department of Public Health, Antwerp, Belgium.
Vincent
http://orcid.org/0000-0001-8560-6041
V
De Brouwere
Athena Institute for Research on Innovation and Communication in Health and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.|Leiden University Medical Center, Department of Obstetrics, Leiden, Netherlands.
Jos
http://orcid.org/0000-0002-6746-3259
J
van Roosmalen
Athena Institute for Research on Innovation and Communication in Health and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Marjolein
http://orcid.org/0000-0001-7015-4951
M
Zweekhorst
clinical decision-making; decision support systems, clinical; mHealth; sub-Saharan Africa