Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis.

Mobile phones have the potential to improve access to healthcare information and services in low-resourced settings. This study investigated the use of mobile phones among patients with chronic diseases, pregnant women, and health workers to enhance primary healthcare in rural South Africa. Qualitative research was undertaken in Mpumalanga in 2014. Semi structured in-depth interviews were conducted with 113 patients and 43 health workers from seven primary healthcare clinics and one district hospital. Data were thematically analysed. We found that some health workers and patients used their own mobile phones for healthcare, bearing the cost themselves. Patients used their mobile phones to remind themselves to take medication or attend their clinic visits, and they appreciated receiving voice call reminders. Some patients and health workers accessed websites and used social media to gather health information, but lacked web search strategies. The use of the websites and social media was intermittent due to lack of financial ability to afford airtime among these patients and health workers. Many did not know what to search for and where to search. Doctors have developed their own informal mobile health solutions in response to their work needs and lack of resources due to their rurality. Physical and social factors influence the usability of mobile phones for healthcare, and this can shape communication patterns such as poor eyesight. The bottom-up use of mobile phones has been evolving to fill the gaps to augment primary care services in South Africa; however, barriers to access remain, such as poor digital infrastructure and low digital literacy.

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Background A well‐functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management. Objectives To assess the effects of interventions to improve routine health information systems in terms of RHIS performance, and also, in terms of improved health system management performance, and improved patient and population health outcomes. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE Ovid and Embase Ovid in May 2019. We searched Global Health, Ovid and PsycInfo in April 2016. In January 2020 we searched for grey literature in the Grey Literature Report and in OpenGrey, and for ongoing trials using the International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov. In October 2019 we also did a cited reference search using Web of Science, and a ‘similar articles’ search in PubMed. Selection criteria Randomised and non‐randomised trials, controlled before‐after studies and time‐series studies comparing routine health information system interventions, with controls, in primary, hospital or community health care settings. Participants included clinical staff and management, district management and community health workers using routine information systems. Data collection and analysis Two authors independently reviewed records to identify studies for inclusion, extracted data from the included studies and assessed the risk of bias. Interventions and outcomes were too varied across studies to allow for pooled risk analysis. We present a 'Summary of findings' table for each intervention comparisons broadly categorised into Technical and Organisational (or a combination), and report outcomes on data quality and service quality. We used the GRADE approach to assess the certainty of the evidence. Main results We included six studies: four cluster randomised trials and two controlled before‐after studies, from Africa and South America. Three studies evaluated technical interventions, one study evaluated an organisational intervention, and two studies evaluated a combination of technical and organisational interventions. Four studies reported on data quality and six studies reported on service quality. In terms of data quality, a web‐based electronic TB laboratory information system probably reduces the length of time to reporting of TB test results, and probably reduces the overall rate of recording errors of TB test results, compared to a paper‐based system (moderate certainty evidence). We are uncertain about the effect of the electronic laboratory information system on the recording rate of serious...

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.