THU0447 HOME-MONITORING GOUT FLARES WITH A SMARTPHONE APP – RESULTS OF A FEASIBILITY STUDY

Background: Gout flares are considered a key clinical and research outcome in gout. Early treatment of gout flares increases patient well-being and warrants timely notification of the treating clinician. Objectives: To test the feasibility of a smartphone app to home-monitor gout flares real-time fo...

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Bibliographic Details
Published inAnnals of the rheumatic diseases Vol. 79; no. Suppl 1; pp. 460 - 461
Main Authors Pouls, B., Bekker, C., Van den Bemt, B., Gaffo, A., Flendrie, M.
Format Journal Article
LanguageEnglish
Published 01.06.2020
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Summary:Background: Gout flares are considered a key clinical and research outcome in gout. Early treatment of gout flares increases patient well-being and warrants timely notification of the treating clinician. Objectives: To test the feasibility of a smartphone app to home-monitor gout flares real-time for both patients with a suspicion of and established gout. Methods: Thirty patients were recruited during their visit at the outpatient rheumatology clinic. Inclusion criteria were age ≥ 18 years, smartphone possession, established gout (crystal proven) or a clinical suspicion of gout and at least one flare reported in the last three months. A straight-forward query app was used to incorporate an adapted version of the 2017 four-criteria gout flare definition.[1] For 90 consecutive days the app asked patients to report their current pain score on an 11-points scale as screening question. Scoring pain below 4 terminated the query, otherwise the app posed the remaining criteria: does the patient experience warm and/or swollen joints and are symptoms regarded as a gout flare. Responses were transmitted in real-time to the dashboard and the clinician was alerted via email if predefined conditions were met. End of study evaluation consisted of the number of generated alerts, duration of (possible) flares and actions taken. Patient feasibility was assessed by measuring app attrition and using a questionnaire based on the Technology Acceptance Model. [2] All constructs were analysed using descriptive statistics. Results: All 30 recruited patients finished the trial. Three minor, resolvable technical issues were reported. Seventeen participants never missed a question. In total 110 responses (4.1%) were missed with three participants responsible for 66 missings. 90% of the participants rated app usability good to excellent and 70% would recommend the app to other patients. Twelve out of thirty patients generated a total amount of 174 alerts where four patients with a suspicion of gout were responsible for 148 alerts (85%). These patients scored three out of four criteria as they had warm, swollen and painful joints but, after consultation with the clinician, their symptoms were not regarded as a gout flare. The 174 alerts belonged to 23 (possible) flares with a median duration of 5 days [IQR 3,5 – 7,5]. Twenty-one pro-active telephone calls were made which resulted in four visits to the clinic within 48 hours. Clinical guidance over the phone consisted of checking in on patient’s symptoms, giving advice and ten medication adjustments. Conclusion: This prospective study shows feasibility of a smartphone app for home-monitoring gout flares for patients because of high usability scores and low attrition rates. The app has added value for gout care because it enables clinicians to act on flares as they occur. The next step is to further implement the app whilst perpetuating investigation into the added value for patients and clinical practice alike. References: [1]Gaffo AL, Dalbeth N, Saag KG, et al. Brief Report: Validation of a Definition of Flare in Patients With Established Gout. Arthritis Rheumatol. 2018;70(3):462-467. [2]Davis Jr. FD. A Technology Acceptance Model for empirically testing new end-user information systems: theory and results. MIT PhD thesis. 1985 [3]Stoyanov SR, Hides L, Kavanagh DJ, Wilson H. Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS). JMIR Mhealth Uhealth. 2016;4(2):e72. Acknowledgements: This study was funded by AbbVie and Menarini. Disclosure of Interests: : Bart Pouls: None declared, Charlotte Bekker: None declared, Bart van den Bemt Grant/research support from: UCB, Pfizer and Abbvie, Consultant of: Delivered consultancy work for UCB, Novartis and Pfizer, Speakers bureau: Pfizer, AbbVie, UCB, Biogen and Sandoz., Angelo Gaffo Grant/research support from: Received a research grant from AMGEN, Marcel Flendrie Grant/research support from: M. Flendrie has received grants from Menarini and Grunenthal. , Consultant of: M. Flendrie has received consultancy fees from Menarini and Grunenthal.
ISSN:0003-4967
1468-2060
DOI:10.1136/annrheumdis-2020-eular.3643