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Table 1 SWOT analysis of included studies

From: Systematic review on what works, what does not work and why of implementation of mobile health (mHealth) projects in Africa

Factors Strengths Weaknesses Opportunities Threats
Mid-and long-term results/project sustainability -Improve delivery of services (e.g. skilled delivery attendance) [65] and service request (e.g. appointments) [27],[34],[62] -Unclear benefits, uncertain long-term results and effectiveness (e.g. insufficient results from RCTs) [16],[32],[37],[46],[61],[63], and unclear cost-benefit analysis [29],[61]. -Potential to enhance timeliness in reporting health and stock data in rural and remote areas [34] -High facility workload and staff/patient/user illiteracy [38, 54]
-Improved patient-health worker and clinic staff-health worker communication [31] -Results are variable depending on the duration of the intervention and may be overestimated [55], limited study design and external validity [20, 21], weak evidences [27] -Lack of stock management resulting in patients untreated [49] -Limited knowledge on the effects of mHealth on patient health outcomes in low-resource settings [15, 62]
-Increased health workers’ adherence to clinical guidelines and quality of treatment [17],[22],[34],[37], worker morale and sense of empowerment [43], access to medical/health information at the point-of-care [17],[37],[50], and motivation due to training and improved skills [32] -Difficult to monitor text messages content [23], high possibility of data under-reporting [37, 46], and possibility of biased responses from participants [14] -mHealth projects are regarded as innovative and current data collection methods tend to have poor quality [47] -Use of mobile technology for research is recent [22]
-Higher rate and more efficient patient follow-up [33], uptake of counselling and testing [22],[31],[50], reporting of adverse reaction to treatment [24], improved patient’s adherence and response to treatment [15], and higher detection of adherence failure [21],[22],[30]-[32],[37]. -Reported patient anxiety due receiving information [61] -Dependency in donor funding and limited funding opportunities may limit long-term sustainability [56]
-Supports efficient stock management, local drug distribution, counting and ordering accuracy, and supply chain monitoring [22] -mHealth results are dependant of external factors (e.g. long duration of patient treatment may reduce adherence and motivation to participate) [18, 63]
-Overcome communication delays, ensure real-time data acquisition and reporting, reduces data losses and monitor data quality [46],[47],[49], makes available pre-define indicators and reduces delayed reporting [14],[18],[38],[46],[50, 51],[54],[56],[63]  
-Decreases referral time and care costs burden to patients due to transportation [49],[51],[62]
-Supports disease surveillance systems and monitoring of interventions [25],[31],[34]
-Allows delivery of lab text results [51, 57] and reduction of facility’s turnaround time [34, 40]
-Overcome logistical and distance barriers [40], and reduce operational costs [17, 40]
-Provide health education [39]
Integration into the health system -Support patient management [20] -Unclear roles, responsibilities, actions, boundaries and responses needed at different levels of healthcare system (government) for project implementation and scale-up [45] -Existing communication gap between health workers, managers and patients [63] -Political crisis may hindered project implementation and results [26, 50]
-Intervention flexible to be adapted to local context and language [31, 62] -Project results depend on training and clinical practice of health workers [49, 63] -Weak routine health, logistics, and surveillance data reporting systems [62] -Current care delivery processes will need to be redesigned (e.g. change to electronic records and data) [22]
-Allows focusing efforts of clinical staff in areas not covered by the intervention (e.g. remote areas with no mobile phone coverage) [37, 56] -Most pilot projects are started by implementing organisations themselves rather than integrated to the health system [45] -Monitoring and evaluation of programmes may be done with collection of electronic information[62] -Costs of mHealth implementation may affect patient treatment costs [55]
-Public-private partnerships proved to work effectively in these projects [25, 37] -mHealth projects are unlikely to prove effective in poorly performing systems [63] -Improved adherence to clinical guidelines by health workers is required [52] -Unknown health systems complexities for large scale implementation of mHealth projects [55]
-High government commitment, existing governmental eHealth strategy [47] -Poor management of drug supply chain and large discrepancies of and limited control in stock levels of health facilities [43], and poor stock forecasting [15, 47, 49] -Lack of cultural and organisational capacity to manage digital health information [63] may lead to late reporting, lack of feedback and incomplete data collection [63]
-Availability of local private providers willing to set up the mHealth system [47] -Opportunities to be implemented in different national disease control programmes; provide access to data for an evidence-based approach [47],[50]
-Increased participation of local health staff in active case detection in surveillance systems (e.g. malaria) [49] -Project may be attractive and acceptable for private or commercial partners and governments (MoH) [21],[29],[49],[50]
-Places rural health centres in direct communication with the MoH and other stakeholders [45, 50] -Underutilise community health workforce (e.g. health workers) [19, 47, 49] and lack of specialised care/mentoring in rural areas [26, 50]
-Difficult to collect and disseminate health data in remote areas [33, 58]
Project management process -Support provision of user and staff training [52] -Low patient motivation to participate (e.g. reply messages or calls) [54, 56], particularly if project is not tailored to their needs (e.g. local language) [32] -Implementation needs to become multidisciplinary [44] -Challenge of management of mHealth projects remain underestimated [26]
-Minimal human resources and training are required [32, 54] -Small sample size of pilot projects provide limited or biased results [20, 31] -Available funding from larger programmes (e.g. PEPFAR mobile clinic) [62]
-Financial incentive (e.g. airtime credit) allows high response rate to the project [21, 22] -Costs and logistics affect text messaging responding on time [14, 33, 61] -Reporting transparency for donors and stakeholders [37]
-Allows real-time supervision and monitoring work rate, attendance, and staff working hours [47, 50] -Occasional staff shortages during project implementation [22], and staff may be overwhelmed of increased calls or messages [50] -Low capacity and administrative challenges for data collection [49]
-Research is needed to optimize project delivery and intervention targets [31]
Legal issues, regulations and standards -Coded information contributes to data security and confidentiality [63] -Privacy concerns raised when using mobile phones, particularly if not owned by the patient [34, 56] Not mentioned -No minimum number of critical surveillance parameters to be reported has been established [34]
-Integration of SMS guidelines into healthcare process delivery [50] -Security measures (e.g. PIN) may be confusing to users when unfamiliar and poorly understood [37, 54] and expectations are variable for maintaining confidentiality [32] -Lack of published data on feasibility and acceptability of confidentiality methods [62]
-Unknown standards for monitoring and evaluation of mHealth programmes [21, 34]
Technology and infrastructure -Text messaging is inexpensive, uses existing infrastructure (e.g. existing networks, reducing phone costs) [18],[22],[26],[49],[50],[56],[58],[59],[62],[63], and is easy to use [43] -Limited text capacity of mobile phones and text messages (e.g. up to 160 char.) [18] -High access and rapid expansion of mobile network coverage, availability of inexpensive handsets, and decreasing costs of mobile phone services and rapidly-growing technological field [14]-[19, 22, 26, 28, 31, 34, 37, 40],[43, 49, 56, 62] -High phone theft and limited electricity to charge phones [38]
-Users are familiar to mobile phone services [31],[34],[47],[53],[59],[62] -Staff are not always able to use or act promptly to the text messaging requests, or do not have the skills required [43, 62] -Potential of SMSs to influence uptake of healthcare technologies [33, 57] -Technical or expert knowledge for development, maintenance and platforms (software and hardware) may be limited [37, 56], and slowdown implementation [49, 57, 62]
-High acceptance, satisfaction and valued by patients and staff [16],[18],[33],[34],[47],[49],[56],[63] -Variable access to mobile phones (e.g. not all patients own a personal phone, phones are often shared, cost of service) [32, 37] -SMS-based software and delivery systems can be updated and review for future developments [24] -Dependency on network coverage [19]
-Mobile phones are not easily broken and less subject to thief than other technologies [17, 22, 25, 28, 34, 54, 63] -Technical challenges reduce data quality and transfer [18],[37], lost network, phone maintenance costs [17]and risk of theft and lose [19] -The lack of other communication technologies (e.g. internet) offers opportunities to mobile phones [55] -High illiteracy and users’ preference makes voice calls more attractive than text messaging [14],[17],[62]
-Use of similar technologies may not have similar results [21, 25, 54] -Unreliable network, internet and electricity access [32],[34],[37]
-Staff may not use the mobile phones appropriately or handle them with care [57] -Receptiveness of the technology is limited by socioeconomic and sociocultural factors, geographic barriers and quality of care [19, 20, 32, 33, 49]
-Software may not be adaptable or flexible, and are still subject to human error [63]
Scale-up and replication -Allows monitoring and impact assessment prior to scaling-up [27] -No assessment has been performed to know if an effective implementation for one disease works for other diseases [24, 40, 44, 54, 62] -Cost-effective implementation of m-Health programmes (e.g. lower running costs) [59] -Unknown cost-effectiveness of deployment and maintenance [56]
-Feasible to be implemented in remote and resource-limited areas [49], and potential nationwide scale-up [32, 56] -High upfront set-up costs [43], difficulties to secure sustainable funding for scaling-up [19, 32], and uncertainty on future changes of costs [63] -Innovations for automated text messaging and partnerships with mobile technology developers may improve scalability [37, 39, 49] - Lack of a mechanism to use data collected at district and national levels [17, 32, 43, 46, 56]
  -Low replication costs and highly adaptable to specific cultural contexts [51] -Open source programmes may support implementation of mHealth in low-resource settings [22] -MoH guidance and policies, and government financial support are lacking and are required for scaling-up [49]
  -High potential to be scaled-up [32],[47],[56]    -Little existing evidence on efficacy and effectiveness of mHealth interventions [49, 63], particularly at large-scale [32]
  1. The table below summarizes and compiles findings of the studies included in the review. The SWOT analysis methodology was used in five areas related to implementation of mHealth projects: project sustainability and mid/long-term results, integration of the project to the health system, technology and infrastructure, project management process, scale-up and replication, and legal, regulatory and standardization aspects. When more than 3 studies were found to be referring to the same issues, these were embolden to highlight their relevance according to appearance in the studies.
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