Session Information
Session Type: ACR Poster Session C
Session Time: 9:00AM-11:00AM
Background/Purpose: Treatment for patients with rheumatoid arthritis (RA) is shaped by monitoring changes in disease severity over time. At present, clinicians managing RA have few (or no) objective measurements of disease activity between clinic visits, even though a number of patient related outcomes measures (PROMs) exist. Smartphones provide a possible solution to allow regular monitoring of disease severity between clinic visits with integration into electronic medical records. Benefits could include better information for consultations, triaging of outpatient appointments and aiding patient self-management. Such data can also support novel research by providing temporally-rich data. REMORA (REmote MOnitoring of Rheumatoid Arthritis) is a study which is designing, implementing and evaluating a system of remote data collection for people with RA for health and research purposes. The project asks whether electronic collection of patient reported outcomes (ePROS) directly from patients between clinic visits can enhance clinical care and provide a sustainable source of data for research. The aim of this paper is to describe the process of determining the ePROS for inclusion in the app, in preparation for piloting the app in clinical practice, and to present the final dataset.
Methods: This study obtained stakeholders’ views on the potential value of recording a range of ePROS. Interviews were conducted with 10 RA practitioners (clinicians, nurses and physiotherapists), 12 RA researchers and 21 patients. Interviews determined provisional ePROSs for inclusion, recording frequency, and value of a free text diary. Table 1 summarises the approach to gaining consensus on app components.
Results: All stakeholder groups wanted to capture information on changes in disease activity and the impact of the disease (physically and emotionally). Practitioners and researchers wanted routine data that had been recorded consistently using existing validated tools (such as the DAS 28 and the HAQ), but saw the value of a diary for recording triggers and alleviators of disease activity. Patients favoured recording notable events (such as flares) as they occurred, however, they could see the benefits of recording data routinely to see patterns in disease activity. The final data set therefore comprised a combination of routine data and a diary (table 2).
Conclusion: Consensus on the key components of the Smartphone app was achieved using the process outlined in table 1. The components shown in table 2 have now been incorporated into the ‘beta app’ in readiness for piloting within clinical practice.
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Table 1: Consensus process o Qualitative interviews were conducted with researchers and practitioners to determine their preferences regarding the components of the app and the rationale for their choices o A table summarising the key components suggested by practitioners and researchers was generated in preparation for discussion and feedback from the PPI (patient and public involvement) group working alongside the research team o The content and wording of the tabulated information was refined in response to suggestions made by the patient group in preparation for patient interviews o Qualitative interviews were conducted with patients with RA to determine their preferences regarding the components of the app. Following this open discussion, patients were shown the tabulated information, derived from practitioner and researcher interviews, and patient feedback sought on the suitability of components suggested o The components which had widespread consensus across the stakeholder groups were incorporated into the app o Suggested components that did not have consensus across all groups, or were beyond the scope of the study, were documented with a view to being incorporated into future developments. Components suggested included the facility for taking photographs, and linking the app to a device, such as a pedometer, for measuring exercise o PPI group members reviewed and commented on the final components prior to their incorporation into the beta app |
| Table 2: Final data set – frequency, components and mode of data capture | ||
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Daily question set |
Pain Difficulty with physical activities Fatigue Sleep difficulties Physical wellbeing Emotional wellbeing Coping | 10 point visual analogue scale |
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Morning stiffness |
Fixed 7 point scale (radio button) |
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Weekly question set |
Number of tender joints Number of swollen joints |
Numeric value |
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Global assessment of wellbeing |
10 point visual analogue scale |
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Employment status |
Yes/No response (radio button) |
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Impact on hours worked |
Numeric value |
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Experienced a flare |
Yes/No response (radio button) |
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Description of flare |
Free text box |
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Monthly question set |
Health Assessment Questionnaire (HAQ) impact of disease on daily activities including function, mobility and grooming | Fixed point scales (radio button) plus free text entry box |
To cite this abstract in AMA style:
Dixon WG, Sanders C, Austin L. Identifying Key Variables for Inclusion in a Smartphone App to Support Clinical Care and Research in Patients with Rheumatoid Arthritis [abstract]. Arthritis Rheumatol. 2016; 68 (suppl 10). https://acrabstracts.org/abstract/identifying-key-variables-for-inclusion-in-a-smartphone-app-to-support-clinical-care-and-research-in-patients-with-rheumatoid-arthritis/. Accessed .« Back to 2016 ACR/ARHP Annual Meeting
ACR Meeting Abstracts - https://acrabstracts.org/abstract/identifying-key-variables-for-inclusion-in-a-smartphone-app-to-support-clinical-care-and-research-in-patients-with-rheumatoid-arthritis/