Using patient-generated health data in clinical practice: How timing influences its function in rheumatology outpatient consultations

The role of patient reported symptom data in co-producing meaning in rheumatoid arthritis

RATIONALE

Patients with rheumatoid arthritis (RA) experience a range of symptoms including joint pain and inflammation, stiffness, fatigue, anxiety, and low mood. Similar to patients with other long-term conditions, they may have periods of time when their disease is under control, and times when their condition is less stable, requiring treatment adjustments. The REMORA2 feasibility study explored the implementation of an integrated symptom-tracking system using a smartphone application (app), enabling patients to track day-to-day symptoms. The data was available in the electronic health record to be viewed at subsequent consultations.

AIMS AND OBJECTIVES

This paper explores patients' comments on living with RA, and how patient-reported symptom data supports informed interactions as patients and clinicians work together to coproduce meaning from the data.

METHOD

Individual semi-structured interviews were conducted with 21 patients and 7 clinicians, supplemented by nonparticipant observations of 5 clinical appointments. Thematic analysis was used to analyse data from the interviews, with an ethnographic approach used to analyse the observational data.

RESULTS

Both clinicians and patients reported the benefits of reviewing the data in the clinic together. This helped inform decisions about pain management and identified patients who might otherwise have dismissed symptoms such as pain, because of their natural inclination to be stoical.

CONCLUSION

Improved insights on the care of RA were generated as patients and clinicians discuss symptom tracking data. This can assist the patient-clinician dyad in the process of two-way learning and shared decision-making on the management of a long-term condition.

Preparing to deliver a stepped wedge cluster-randomised trial to test the effectiveness of daily symptom tracking integrated into electronic health records for managing rheumatoid arthritis: a mixed-methods feasibility trial

BACKGROUND

We sought to assess the feasibility of a stepped-wedge cluster-randomised trial testing the effectiveness of a complex mHealth intervention called REMORA: a co-designed smartphone app enabling daily, weekly and monthly symptom tracking integrated into electronic health records for people with rheumatoid arthritis (RA).

METHODS

We conducted a mixed-methods feasibility trial using a convergent approach with some explanatory sequential elements. Patients were eligible to take part if they were older than ≥18 years of age, had (suspected) RA or undifferentiated inflammatory arthritis, and consented to take part from two outpatient departments. We analysed quantitative app and electronic health record data descriptively. We analysed qualitative data from interviews and clinic observations thematically. We assessed four feasibility domains: recruitment and consent (target: 15 patients per site), intervention uptake (≥70% of recruited participants completed on-boarding, i.e., registered with the app and submitted at least one symptom report), intervention adherence (>50% daily symptom reports provided), and measuring disease activity as the primary outcome (scores available for ≥80% of people with a follow-up clinic visit). Due to time constraints, we only recruited patients to the intervention group, leaving us unable to test the logistics of randomising sites in accordance with the trial's cluster stepped wedge design.

RESULTS

Of 130 people screened, 52 consented. Of those, 32 (62%) completed on-boarding. On-boarded participants provided symptom data on 2384/3771 (63%) of possible days. Among the 48 people who had ≥1 follow-up appointment, at least one disease activity scored was obtained for 46 (96%) of them. Factors related to intervention uptake formed the biggest threat to trial feasibility, including lack of clarity of communication and guidance, access to technology, and personal challenges (e.g., being busy or unwell).

CONCLUSION

We found that delivering a trial to test the effectiveness of integrated symptom tracking in rheumatology outpatient settings was feasible. The future REMORA trial will contribute to the much-needed evidence base for the impact of integrated symptom tracking on care delivery and patient outcomes, including decision-making, patient experience, disease activity, and symptom burden.

TRIAL REGISTRATION

This feasibility trial was registered at https://www.isrctn.com/ on 23-Jan-2023 (ISRCTN21226438).

Remote monitoring of rheumatoid arthritis (REMORA): study protocol for a stepped wedge cluster randomized trial and process evaluation of an integrated symptom tracking intervention

BACKGROUND

Management of rheumatoid arthritis (RA) relies on symptoms reported by patients during infrequent outpatient clinic visits. These reports are often incomplete and inaccurate due to poor recall, leading to suboptimal treatment decisions and outcomes. Asking people to track symptoms in-between visits and integrating the data into clinical pathways may improve this. However, knowledge on how to implement this into practice and its impact on services and outcomes remains scarce in RA. Therefore, we evaluate the comparative effectiveness and cost-effectiveness of integrated symptom tracking in people with RA over and above usual care, while generating insights on factors for successful implementation.

METHODS

In this superiority stepped wedge cluster-randomized controlled trial with continuous recruitment short exposure design, 16 rheumatology outpatient departments (clusters) recruit a total of 732 people with active RA. They initially offer clinic visits according to standard of care before switching in pairs to visits with integrated symptom tracking. Clusters switch in randomized order every 3 weeks. Integrated symptom tracking consists of (1) a mobile app for patients to track their symptoms daily and other RA aspects weekly/monthly, and (2) an interactive dashboard visualizing the app data, which healthcare professionals access from their electronic health record system. Clinic visits happen according to usual practice, with tracked symptom data only reviewed during visits. Our primary outcome is a difference in marginal mean disease activity score at 12 ± 3 months between standard of care and integrated symptom tracking, after accounting for baseline values, cluster, and other covariates. Secondary outcomes include patient-reported disease activity, quality of life and quality-adjusted life-years, medication/resource use, consultation and decision-making experience, self-management, and illness perception. We also conduct interviews and observations as part of a parallel process evaluation to gather information on implementation.

DISCUSSION

Our trial will generate high-quality evidence of comparative and cost-effectiveness of integrated symptom tracking compared to standard of care in people with RA, with our process evaluation delivering knowledge on successful implementation. This optimizes the chances of integrated symptom tracking being adopted more widely if we find it is (cost-) effective.

TRIAL REGISTRATION

Registered 4-Jun-2024 on https://www.isrctn.com/ , ISRCTN51539448. TRIAL OPEN SCIENCE FRAMEWORK REPOSITORY: https://osf.io/sj9ha/ .

Unleashing the Potential for Patient-Generated Health Data (PGHD)

Patient-generated health data (PGHD) is data created, captured, or recorded by patients in between healthcare appointments, and is an important supplement to data generated during periodic clinical encounters. PGHD has potential to improve diagnosis and management of chronic conditions, improve health outcomes, and facilitate more "connected health" between patients and their care teams. Electronic PGHD is rapidly accelerating due to the proliferation of consumer health technologies, remote patient monitoring systems, and personal health platforms. Despite this tremendous growth in PGHD and anticipated benefits, broadscale use of PGHD has been challenging to implement with significant gaps in current knowledge about how PGHD can best be employed in the service of high-quality, patient-centered care. While the role of PGHD in patient self-management continues to grow organically, we need a deeper understanding of how data collection and sharing translate into actionable information that supports shared decision-making and informs clinical care in real-world settings. This, in turn, will foster both clinical adoption and patient engagement with PGHD. We propose an agenda for PGHD-related research in the Veterans Health Administration that emphasizes this clinical value to enhance our understanding of its potential and limitations in supporting shared decision-making and informing clinical care.

The Complexity of Transferring Remote Monitoring and Virtual Care Technology Between Countries: Lessons From an International Workshop

International deployment of remote monitoring and virtual care (RMVC) technologies would efficiently harness their positive impact on outcomes. Since Canada and the United Kingdom have similar populations, health care systems, and digital health landscapes, transferring digital health innovations between them should be relatively straightforward. Yet examples of successful attempts are scarce. In a workshop, we identified 6 differences that may complicate RMVC transfer between Canada and the United Kingdom and provided recommendations for addressing them. These key differences include (1) minority groups, (2) physical geography, (3) clinical pathways, (4) value propositions, (5) governmental priorities and support for digital innovation, and (6) regulatory pathways. We detail 4 broad recommendations to plan for sustainability, including the need to formally consider how highlighted country-specific recommendations may impact RMVC and contingency planning to overcome challenges; the need to map which pathways are available as an innovator to support cross-country transfer; the need to report on and apply learnings from regulatory barriers and facilitators so that everyone may benefit; and the need to explore existing guidance to successfully transfer digital health solutions while developing further guidance (eg, extending the nonadoption, abandonment, scale-up, spread, sustainability framework for cross-country transfer). Finally, we present an ecosystem readiness checklist. Considering these recommendations will contribute to successful international deployment and an increased positive impact of RMVC technologies. Future directions should consider characterizing additional complexities associated with global transfer.

Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity): A longitudinal observational study

Introduction

People living with multiple long-term conditions (multimorbidity) (MLTC-M) experience an accumulating combination of different symptoms. It has been suggested that these symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices.

Aim

The aim of this study was to investigate longitudinal user engagement with a smartwatch application, collecting survey questions and active tasks over 90 days, in people living with MLTC-M.

Methods

‘Watch Your Steps’ was a prospective observational study, administering multiple questions and active tasks over 90 days. Adults with more than one clinician-diagnosed long-term conditions were loaned Fossil® Sport smartwatches, pre-loaded with the study app. Around 20 questions were prompted per day.

Daily completion rates were calculated to describe engagement patterns over time, and to explore how these varied by patient characteristics and question type.

Results

Fifty three people with MLTC-M took part in the study. Around half were male ( = 26; 49%) and the majority had a white ethnic background (n = 45; 85%). About a third of participants engaged with the smartwatch app nearly every day. The overall completion rate of symptom questions was 45% inter-quartile range (IQR 23–67%) across all study participants. Older patients and those with greater MLTC-M were more engaged, although engagement was not significantly different between genders.

Conclusion

It was feasible for people living with MLTC-M to report multiple symptoms per day over 3 months. User engagement appeared as good as other mobile health studies that recruited people with single health conditions, despite the higher daily data entry burden.