JMIR Publications

ABSTRACT

Background:

There is growing evidence supporting the use of mobile health (mHealth) interventions in low- and middle-income countries (LMICs) to address resource limitations in the delivery of health information and services to vulnerable populations. In parallel, there is an increasing emphasis on the use of implementation science tools and frameworks for early identification of implementation barriers and to improve the acceptability, appropriateness, and adoption of mHealth interventions in resource-limited settings. However, there are limited examples of the application of implementation science tools and frameworks to the formative phase of mHealth design for resource-limited settings, despite the potential benefit of this work for enhancing subsequent implementation, scale-up, and sustainability.

Objective:

We present a case study on the use of an implementation science framework during mHealth design. In particular, we illustrate the utility of the Consolidated Framework for Implementation Research (CFIR) for organizing and interpreting formative research findings during the design of the mobile Inspección Visual con Ácido Acético (mIVAA) system in Lima, Peru.

Methods:

We collected formative data from prospective users of the mIVAA intervention using multiple research methodologies including structured observations, surveys, group and individual interviews, and discussions with local stakeholders at the partnering organization in Peru. These activities enabled documentation of clinical workflows, perceived barriers and facilitators of mIVAA, overarching barriers to cervical cancer screening in community-based settings, as well as related local policies and guidelines in healthcare. Using a convergent mixed methods analytic approach and CFIR as an organizing framework, we mapped formative research findings to identify key implementation barriers and inform iterations of the mIVAA system design.

Results:

In the setting of our case study, the majority of implementation barriers were identified in the CFIR domains of intervention characteristics and inner setting. All but one barrier were addressed prior to mIVAA deployment by modifying the system design and adding supportive resources. Solutions involved improvements to infrastructure including cellular data plans to avoid disruption from internet failure; improved process and flow including updated software interface; and better user role definition for image capture to be consistent with local healthcare laws.

Conclusions:

CFIR can serve as a comprehensive framework for organizing formative research data and to identify key implementation barriers during mHealth intervention design. In our case study of the mIVAA system in Peru, formative research contributing to the CFIR domains of intervention characteristics and inner setting elicited the majority of key barriers to implementation. The early identification of barriers enabled design iterations prior to system deployment. Future efforts to develop mHealth interventions for LMICs may benefit from using the approach presented in this case study as well by prioritizing the CFIR domains of intervention characteristics and inner setting. Clinical Trial: Not Applicable