Rheumatoid Arthritis (RA) is a chronic and debilitating systemic inflammatory disease that causes the destruction of joints throughout the body. In the US, arthritis causes more disability than any other condition, including back problems, cardiovascular disease, and diabetes1. Arthritis places an enormous financial burden on the healthcare system and society as a whole with an estimated cost of $128 billion dollars to the US economy annually. While RA can manifest in a variety of joints throughout the body, the vast majority of patients experience RA symptoms in their hands and wrists. Hand deformities are a common feature of RA as are other physical deficits such as reduced grip strength and pain which reduce the ability of the individual to perform activities of daily living (ADL). Each episode of RA-induced inflammation in the synovial joints of the hand and wrist are painful predictors of future bone loss and long term deformity. RA bone damage and deformity progression can be prevented through reduction of individual patient triggers that induce inflammatory “flares”, and by early and consistent use of disease-modifying antirheumatic drugs (DMARDs) and other pharmacotherapeutics. Not only is the hand a primary area of painful and disabling symptoms, it is also an area that can be monitored to predict disease flares and monitor disease progression. While clinicians can use imaging to monitor RA progression, measurement is infrequent due to costs of implementing radiographic tests, availability of radiologists for interpretation, and slow changes over time in this era of more effective therapies. Additionally frequent radiograph measurement adds new risks due to radiation exposure. There are limited options for individuals with RA to self-monitor disease flare triggers or disease progression. There are currently no consumer imaging modalities that would allow an individual to closely monitor and manage their RA symptoms, triggers, and disease progression. The goal of this research to test the feasibility of a smartphone application designed to improve self-management and improve health outcomes in individuals with RA. We propose studying a group of patients suffering with RA to validate whether the application of a smartphone technology can provide more accurate and quantifiable measurements of RA symptoms, correlate them with effects of treatment, weather, and lifestyle, and determine whether this application signals improvements in patient self-management. Our central hypothesis is that a smartphone technology that provides objective imaging of RA hand changes and quantifies associated lifestyle factors will improve daily self-management and self-efficacy in users while providing valuable health information to improve health outcomes. The outcome of this research will validate that a smartphone application is a feasible intervention to improve self-management in individuals with RA, while collecting valuable clinical data on RA symptoms and associated triggers. The results of this project will serve as the basis for a larger population study and clinical trial(s) that would be the subject of a R01 grant application in 2017.
Aim 1. We will test the usability and data validity of a smartphone medical application for RA self-management. We will enroll 40 subjects willing to record clinical data related to their RA over at least six months. The collected data will include self-imaging of the patient’s hands, level of pain, treatment information, weather, and lifestyle factors such as patient diet and physical activity. We will validate the use of smartphone technology, evaluate the assistance of the technology in monitoring symptom status, and identify barriers to use of the smartphone app. Based on these data, we will evaluate the quality and statistical significance of the data considering the effects of data interval, sparseness, and total collection period. We will assess the quality for each of the various data components including pain, treatment, weather, diet, activities, etc.
Aim 2. We will compare the self-management and self-efficacy of patients using a RA self-management smartphone application compared to those getting standard care. We will evaluate if the smartphone technology can improve self-management and self-efficacy through responses to two questionnaires: the Patient Activation Measure (PAM) and the PROMIS Self-Efficacy Managing Symptoms. We will evaluate participant response to these metrics before commencing the study and after study completion. We will compare the results of the study participants with a control group from the study-recruitment pool who do not use smartphone technology for their arthritis self-management. Expected Outcomes: The results of this study will allow us to see if a smartphone application for RA symptom self-management is feasible, and provide preliminary data as to whether or not this application improves self-management, self-efficacy, and health outcomes in participants. We expect that our findings will provide the necessary data to apply for a subsequent R01 grant, where this application is utilized among a much larger population in the NDB6 (n=10,000), managed by the PI, Dr. Michaud.