Adoption and Usage of mHealth Technology on Quality and Experience of Care Provided by Frontline Workers: Observations From Rural India

Abstract

BackgroundmHealth apps are deployed with the aim of improving access, quality, and experience of health care. It is possible that any mHealth intervention can yield differential impacts for different types of users. Mediating and determining factors, including personal and socioeconomic factors, affect technology adoption, the way health workers leverage and use the technology, and subsequently the quality and experience of care they provide.ObjectiveTo develop a framework to assess whether mHealth platforms affect the quality and experience of care provided by frontline workers, and whether these effects on quality and experience are different depending on the level of technology adoption and individual characteristics of the health worker. Literacy, education, age, and previous mobile experience are identified as individual factors that affect technology adoption and use, as well as factors that affect the quality and experience of care directly and via the technology.MethodsFormative research was conducted with 15 community health workers (CHWs) using CommCare, an mHealth app for maternal and newborn care, in Bihar, India. CHWs were first classified on the level of CommCare adoption using data from CommCareHQ and were then shadowed on home visits to evaluate their levels of technology proficiency, and the quality and experience of care provided. Regression techniques were employed to test the relationships. Out of all the CHWs, 2 of them refused to participate in the home visits, however, we did have information on their levels of technology adoption and background characteristics, which were included in the analysis as relevant.ResultsLevel of technology adoption was important for both quality and experience of care. The quality score for high users of CommCare was higher by 33.4% (P=.04), on average, compared to low users of CommCare. Those who scored higher on CommCare proficiency also provided significantly higher quality and experience of care, where an additional point in CommCare proficiency score increased the quality score by around half a point (0.541, P=.07), and experience score by around a third of a point (0.308, P=.03). Age affected CommCare user type negatively, with an increase in age increasing the likelihood of belonging to a lower category of CommCare adoption (-0.105, P=.08). Other individual characteristics did not affect adoption or the predicted values estimating the relationship between adoption and quality and experience of care, although illiteracy was able to affect the relationship negatively.ConclusionsmHealth technology adoption by frontline workers can positively impact the quality and experience of care they provide. Individual characteristics, especially literacy and age, can be important elements affecting technology adoption and the way users leverage the technology for their work. Our formative study provides informed hypotheses and methods for further research.

Mobile phone use among female entertainment workers in Cambodia: an observation study

“…mHealth, or mobile health, projects have shown to be increasingly successful in developing countries. Collecting health data (8)(9)(10), increasing access to health knowledge (11)(12)(13)(14), promoting provider quality (15)(16)(17), and increasing medication/appointment adherence (18)(19)(20) are a few ways in which mobile phones have successfully been used in developing countries to support health. In addition, rigorous evaluations have demonstrated mobile phone messages to be successful in supporting preventative healthcare (8,14,18,21,22) such as chronic disease prevention in Seychelles (23).…”

Scoping review and evaluation of SMS/text messaging platforms for mHealth projects or clinical interventions

“…CommCare was commonly used for programs requiring simultaneous electronic data capture by community health workers in the field and data management by program managers based at a hospital or clinic [28, 29, 33]. Therefore, its cloud database was a key advantage because it synchronizes in real-time [33].…”

Categorization of Factors Influencing Community Health Workers from a Socio-Technical Systems Perspective

“…As a result, De Neve et al [17] propose the need for countries to develop coherent and context-specific approaches to ensure optimal performance by CHWs through the consideration of the broader context, including demographic, socioeconomic, political, legislative, ecological, sociocultural, and technological factors contributing towards facilitating or inhibiting the success of many CHWs initiatives [18,19]. Some of the solutions to achieve what is postulated in the studies include coordinating the health system and community system to prioritize factors that inhibit or facilitate the understanding of CHWs programs' compatibility with community structures, cultural values, and perception, socio-economic context and support system [20].…”

“…Previous research that was focused on CHWs and their performance placed emphasis on developing frameworks that provide a broad context of the CHW's position in a larger environment by describing the interrelations of intrapersonal, family, community, and organizational settings as health professionals [6,10]. This perspective to a larger extent provides a limited understanding of the impact of the ecological environment on CHWs [20]. Most programs have not been able to effectively address the gap between research evidence and the routine practicality of CHWs as health professions, hence the poor integration of CHWs within the healthcare system and an even poorer understanding of their roles within their communities.…”

“…Moreover, minimal work has been done locally in terms of implementing universal guidelines to guide the integration strategies required to resolve the above-stated implications. Previous research has proved that the effectiveness of CHWs holds the potential to increase access to equitable health in LMICs [20]. As a result, CHWs' understanding of the socio-cultural norms of their communities, their unique intermediary position between communities and the health system places them in a central setting in delivering key health interventions.…”