Study protocol: mobile improvement of self-management ability through rural technology (mI SMART)

There are 62 million Americans currently residing in rural areas who are more likely to have multiple chronic conditions and be economically disadvantaged, and in poor health, receive less recommended preventive services and attend fewer visits to health care providers. Recent advances in mobile healthcare (mHealth) offer a promising new approach to solving health disparities and improving chronic illness care. It is now possible and affordable to transmit health information, including values from glucometers, automated blood pressure monitors, and scales, through Bluetooth-enabled devices. Additionally, audio and video communications technologies can allow healthcare providers to conduct many parts of a physical exam remotely from varied settings. These technologies could remove geographical distance as a barrier to care and diminish the access to care issues faced by patients who live rurally. However, currently there is lack of studies that provide evidence of feasibility, acceptability, and effectiveness of mHealth initiatives on improved outcomes of care, a needed step to make the translation to implementation studies in healthcare systems. The purpose of this paper is to present the protocol for the first study of mI SMART (mobile Improvement of Self-Management Ability through Rural Technology), a new integrated mHealth intervention.

Our objective is to provide evidence of feasibility and acceptability for the use of mI SMART in an underserved population and establish evidence for the refinement of mI SMART. The proposed study will take place at Milan Puskar Health Right, a free primary care clinic in the state of West Virginia. The clinic provides health care at no cost to uninsured, low income; adults aged 18-64 living in West Virginia. We will enroll 30 participants into this feasibility study with plans of implementing a longitudinal randomized, comparative effectiveness design in the future. Data collection will include tracking of barriers and facilitators to using mI SMART on patient and provider feedback surveys, tracking of patient-provider communications, self-reports from patients on quality of life, adherence, and self-management ability, and capture of health record data on chronic illness measures.

We expect that the mI SMART intervention, refined from participant and provider feedback, will be acceptable and feasible. We anticipate high patient-provider satisfaction, enhanced patient-provider communication, and improved health related quality of life, adherence to treatment, and self-management ability. In addition, we hypothesize that patients who use mI SMART will demonstrate improved physical outcomes such as blood glucose, blood pressure, and weight.