Novel Methods for Ascertainment of Gout Flares -A Pilot Study

The purpose of this study is to determine the feasibility and acceptability of using different remote data collection technologies to ascertain flare occurrence among gout patients. Two technologies will be the focus of this study: a telephone based interactive voice response (IVR) and a smartphone mobile application (called RheumPRO). The results of this study will not only guide research approaches in clinical trials, but may also have direct implications for monitoring patient outcomes in the context of day-to-day clinical practice.

The investigators hypothesize that acceptability will be greater for RheumPRO application than IVR. Additionally, the investigators hypothesize that RheumPRO will be associated with a greater frequency of patient-initiated interactions.

Acute gout flares are a major cause of morbidity. Flares lead to substantial reductions in health-related quality of life, increased work absenteeism, productivity loss, and substantial healthcare costs. Acute gout flares are likely related to more than 174,000 emergency department visits in the U.S. annually with corresponding charges approaching $166 million.

In recent surveys, gout patients and healthcare providers alike identified the reduction of gout flares as the highest priority outcome that should be examined in future comparative effectiveness studies of urate lowering therapy (ULT) (unpublished results). Despite consensus about the importance of capturing flares, clinical trials investigating ULTs or anti-inflammatory prophylaxis have used inconsistent flare definitions and methods of flare ascertainment. The inconsistency has likely been driven by the absence of a standardized definition or ascertainment method. These deficits limit comparisons that can be made across investigations.

Recently, a group supported by the American College of Rheumatology \& European League Against Rheumatism (ACR \& EULAR) has attempted to define a gout flare (8-10). For simplicity, the group focused on defining only those flares occurring after a definitive gout diagnosis. Nine elements of a flare definition emerged from the first two studies. These nine elements included physician reported information, laboratory data and patient self-report. In a third study, Gaffo et al. compared the discriminatory ability of the self-reported items against the gold standard of a rheumatologist's judgment of flare presence. Self-report of 4 criteria had the greatest discriminatory ability with an area under the curve (AUC) of 0.931. These promising results indicate the important role for a standardized self-report definition of a gout flare.

In addition to variability in gout flare definitions, the optimal method for obtaining self-reported flares remains undefined. An early study of febuxostat, for example, assessed flares weekly at physician visits Another study counted a flare only when it was treated by a healthcare provider. Still other studies assessed flares during physician visits occurring at variable time points. These inconsistent methods also pose practical limitations given by their time and resource intensive nature. Opportunities to increase efficiency have only recently become available with the validation of the self-reported definition for gout flares described above. Self-report can now be combined with technological advances in remote data collection to develop novel and highly efficient methods to identify gout flares. The investigators propose a study to address this pressing need by leveraging technological advances that facilitate the remote and real-time collection of patient reported flares and outcomes (PROs) in gout.

Eligibility Criteria:
Inclusion Criteria:

* \>/= to 18 yrs of age with Current physician diagnosed gout
* current hyperuricemia (serum urate level \>6.8 mg/dl)
* self-report of at least two gout flares in the previous 6 months
* current smartphone user utilizing a FitBit compatible smart Phone (with the ability to download RheumPRO from Apple/Google Play store).