Providing 'the bigger picture': benefits and feasibility of integrating remote monitoring from smartphones into the electronic health record

Patient and Staff Insights on Digital Care Pathways for Patients With Low Back Pain in the Emergency Department: A Qualitative Study

BACKGROUND

Back pain is a huge global problem. For some people, the pain is so severe that they feel the need to present to an emergency department (ED). Our aim was to explore patient and staff perspectives for the development of a digital care pathway (DCP) for people with back pain who have presented to ED, including acceptability, barriers and facilitators.

METHODS

We used a descriptive phenomenology approach using semi-structured interviews with patient and staff participants at a tertiary hospital. Interviews were transcribed and data codes were developed using inductive thematic analysis. Themes were discussed between researchers until consensus was achieved.

RESULTS

A total of 16 interviews were carried out, half of which involved patient participants. We identified three major themes: (i) expectations and experiences of staff and patients with low back pain in ED; (ii) a digital care pathway can empower patients and support clinicians in providing care; and (iii) acceptability, barriers, facilitators and recommendations of engaging with a DCP to track the trajectory of back pain. Each theme was further categorised into subthemes.

CONCLUSION

Introducing a DCP was perceived as acceptable and beneficial by patients and staff. Both groups were aware of the potential participant burden if surveys were too long. Introducing a DCP could be a valuable adjunct to current management care models, providing a standardised source of education with the potential for individualised tracking and monitoring. The design and development of a DCP will need to consider reported facilitators and address perceived barriers for engagement.

PATIENT OR PUBLIC CONTRIBUTION

This project sought insights from patients and staff about a digital care pathway. This forms the first step of patient and consumer consultation before implementing a digital care pathway. All consumers were offered the opportunity to review their responses and our interpretation.

Meeting report: patient and caregiver recommendations for a mobile health application for paediatric systemic lupus erythematosus

Paediatric systemic lupus erythematosus (pSLE) management and research could be enhanced by a mobile health application (app); however, no app designed for pSLE is currently available. A development and design committee comprising of patients, parents/caregivers and other stakeholders met to inform development and design of an app specific for pSLE. This meeting report summarises the group's discussions and recommendations that could help create a useful and desirable app or mobile health tool for the pSLE community.

mHealth app features that facilitate adolescent use for lifestyle management, and are endorsed by caregivers and health care providers

Background

Mobile health (mHealth) apps are becoming a promising tool to motivate sustainable lifestyle and behavior changes, including modifications to diet and exercise. However, most current mHealth apps do not have meaningful, and sustained user acceptance, particularly, among adolescents. They perceive mHealth apps designed for adults to be tedious and visually unexciting, which discourage adolescent usage. Researchers and adolescent mHealth app developers would benefit from a foundational understanding of which functions and features adolescents feel would most motivate app use. Capturing caregivers' and health care providers' inputs are also important as both groups play an integral role in adolescent health care decision-making. The purpose of the study is to explore and analyze mHealth app features identified by adolescents, caregivers, and health care providers that have the potential to inspire continued use, thereby resulting in sustained health behavior changes in adolescents.

Methods

We used inductive thematic analysis of qualitative data obtained from semi-structured focus groups conducted via Zoom©. Important features of mHealth apps that encourage adoption and continued use were explored with 25 participants, including adolescents, their caregivers, and health care providers.

Results

Common features facilitating continual usage of mHealth apps that were identified as significant by participating adolescents, their caregivers and health care providers were: look and feel of the app, customization, educational information/recommendations, and integration with electronic health record. Features such as gamification and social interaction that are usually lacking in current adolescent mHealth apps were well recognized as meaningful for motivational purposes.

Conclusions

The findings suggest that adolescents and caregivers identify an app as valuable when it is user-friendly and intuitive and appreciate features that are motivating and can engage users in positive behaviors. Health care providers prefer mHealth apps that are user-friendly and can be effectively integrated into the cycle of care, thereby enabling delivery of efficient and value-based health care. Thus, mHealth app designs that are informed by health care providers' clinical experience and needs, in combination with app features that are desired and supported by both adolescents and their caregivers, have the potential to motivate widespread adoption and long-term use, which could result in improved health behaviors and outcomes among adolescents.

Classifying Self-Reported Rheumatoid Arthritis Flares Using Daily Patient-Generated Data From a Smartphone App: Exploratory Analysis Applying Machine Learning Approaches

BACKGROUND

The ability to predict rheumatoid arthritis (RA) flares between clinic visits based on real-time, longitudinal patient-generated data could potentially allow for timely interventions to avoid disease worsening.

OBJECTIVE

This exploratory study aims to investigate the feasibility of using machine learning methods to classify self-reported RA flares based on a small data set of daily symptom data collected on a smartphone app.

METHODS

Daily symptoms and weekly flares reported on the Remote Monitoring of Rheumatoid Arthritis (REMORA) smartphone app from 20 patients with RA over 3 months were used. Predictors were several summary features of the daily symptom scores (eg, pain and fatigue) collected in the week leading up to the flare question. We fitted 3 binary classifiers: logistic regression with and without elastic net regularization, a random forest, and naive Bayes. Performance was evaluated according to the area under the curve (AUC) of the receiver operating characteristic curve. For the best-performing model, we considered sensitivity and specificity for different thresholds in order to illustrate different ways in which the predictive model could behave in a clinical setting.

RESULTS

The data comprised an average of 60.6 daily reports and 10.5 weekly reports per participant. Participants reported a median of 2 (IQR 0.75-4.25) flares each over a median follow-up time of 81 (IQR 79-82) days. AUCs were broadly similar between models, but logistic regression with elastic net regularization had the highest AUC of 0.82. At a cutoff requiring specificity to be 0.80, the corresponding sensitivity to detect flares was 0.60 for this model. The positive predictive value (PPV) in this population was 53%, and the negative predictive value (NPV) was 85%. Given the prevalence of flares, the best PPV achieved meant only around 2 of every 3 positive predictions were correct (PPV 0.65). By prioritizing a higher NPV, the model correctly predicted over 9 in every 10 non-flare weeks, but the accuracy of predicted flares fell to only 1 in 2 being correct (NPV and PPV of 0.92 and 0.51, respectively).

CONCLUSIONS

Predicting self-reported flares based on daily symptom scorings in the preceding week using machine learning methods was feasible. The observed predictive accuracy might improve as we obtain more data, and these exploratory results need to be validated in an external cohort. In the future, analysis of frequently collected patient-generated data may allow us to predict flares before they unfold, opening opportunities for just-in-time adaptative interventions. Depending on the nature and implication of an intervention, different cutoff values for an intervention decision need to be considered, as well as the level of predictive certainty required.

A Mobile Health Application Integrated in the Electronic Health Record for Rheumatoid Arthritis Patient-Reported Outcomes: A Controlled Interrupted Time-Series Analysis of Impact on Visit Efficiency

OBJECTIVE

Patient-reported outcome (PRO) collection between visits for rheumatoid arthritis (RA) could improve visit efficiency, reducing in-person visits for patients with stable symptoms while facilitating access for those with symptoms. We examined whether a mobile health PRO application integrated in the electronic health record (EHR) could reduce visit volume for those with RA.

METHODS

We developed an application for RA that prompted patients every other day to complete brief PRO questionnaires. Results of the application were integrated into the EHR. We tested the application in a controlled interrupted time-series analysis between 2020 and 2023. Rheumatologists received EHR-based messages based on PRO results recommending the patient receive a visit earlier or later than scheduled. The primary outcome was monthly visit volume during the year before versus the year after initiation.

RESULTS

A total of 150 patients with RA consented and used the application. The median age was 62 years, 83% were female, 7% had fewer than 2 years of disease, and 50% were seropositive; 150 controls were well matched. Among those in the application cohort, the estimated monthly median visit volume in the year before use of the application was 31.2 (95% confidence interval [95% CI] 28.0-34.3); in controls, this was 30.4 (95% CI 27.3-33.6). In the year using the application, the estimated monthly visit volume was 36.8 (95% CI 33.4-40.3) compared to 38.7 (95% CI 35.2-42.3) in controls. The difference in the differences between the cohorts was not statistically significant (-2.7 visits, 95% CI -9.3 to 4.0). No differences were noted in flare rates or visit delays.

CONCLUSION

In this initial trial of a PRO application intervention to improve visit efficiency, we found no association with reduced visit volume.

Acceptability of Tele-mental Health Services Among Users: A Systematic Review and Meta-analysis

BACKGROUND

Mental disorders are currently a global public health concern, particularly after the coronavirus disease 2019 (COVID-19) pandemic. Mental health services gradually transitioned to teleservices, employing various methods like texting and videoconferencing. This meta-analysis aimed mainly to quantify the acceptability of tele-mental health services among both beneficiaries and providers. Secondary objectives included quantifying the usability of and satisfaction with these services.

METHODS

We conducted a systematic search of the following databases PubMed Central, SAGE, Google Scholar, Scopus, Web of Science, PubMed Medline, and EBSCO according to Preferred Reporting Items of the Systematic Reviews and Meta-Analysis (PRISMA) guidelines until December 2022.

RESULTS

Out of 3366 search results, 39 studies fully met the inclusion criteria. The pooled acceptability of tele-mental health services among beneficiaries was [71.0% with a 95% confidence interval (CI) of 63.0 - 78.5%, I2 = 98%]. Using meta-regression, four key factors contributed to this heterogeneity (R2 = 99.75%), namely, year of publication, type of mental disorder, participant category, and the quality of included studies. While acceptability among providers was [66.0% (95%CI, 52.0 - 78.0%), I2 = 95%]. The pooled usability of tele-mental health services among participants was [66.0% (95%CI, 50.0 - 80.0%), I2 = 83%]. Subgroup analysis revealed statistically significant results (p = 0.003), indicating that usability was higher among beneficiaries compared to providers.

CONCLUSIONS

The study highlighted a high acceptability of tele-mental health services. These findings suggest a promising outlook for the integration and adoption of tele-mental health services and emphasize the importance of considering user perspectives and addressing provider-specific challenges to enhance overall service delivery and effectiveness.

Digital Phenotyping, Wearables, and Outcomes

There is a significant need for robust and objective outcome assessments in spine surgery. Constant monitoring via smartphones and wearable devices has the potential to fill this role by providing an in-depth picture of human well-being, creating an unprecedented amount of objective data to augment clinical decision-making. The metrics obtained from continuous patient monitoring increase the amount and ecological validity of data relevant to spine surgery. This can provide physicians with patient and disease-specific medical information, facilitating personalized patient care.

Users' views on the use of a smartwatch app to collect daily symptom data in individuals with multiple long-term conditions (Multimorbidity): A qualitative study

Introduction

Long-term conditions are a major burden on health systems. One way to facilitate more research and better clinical care among patients with long-term conditions is to collect accurate data on their daily symptoms (patient-generated health data) using wearable technologies. Whilst evidence is growing for the use of wearable technologies in single conditions, there is less evidence of the utility of frequent symptom tracking in those who have more than one condition.

Aims

To explore patient views of the acceptability of collecting daily patient-generated health data for three months using a smartwatch app.

Methods

Watch Your Steps was a longitudinal study which recruited 53 patients to track over 20 symptoms per day for a 90-day period using a study app on smartwatches. Semi-structured interviews were conducted with a sub-sample of 20 participants to explore their experience of engaging with the app.

Results

In a population of older people with multimorbidity, patients were willing and able to engage with a patient-generated health data app on a smartwatch. It was suggested that to maintain engagement over a longer period, more 'real-time' feedback from the app should be available. Participants did not seem to consider the management of more than one condition to be a factor in either engagement or use of the app, but the presence of severe or chronic pain was at times a barrier.

Conclusion

This study has provided preliminary evidence that multimorbidity was not a major barrier to engagement with patient-generated health data via a smartwatch symptom tracking app.

"Keep It Short and Simple": Perceptions of patients and healthcare professionals on the use of a mobile health app in the care for patients undergoing radical prostatectomy

Background

Patients undergoing radical prostatectomy for localised prostate cancer generally have good long-term survival rates. However, late recurrences can occur and require lifelong follow-up.

Objective

This research aims to investigate different stakeholders' perceptions on the use of mobile health (mHealth) applications for prostate cancer follow-up after radical prostatectomy.

Methods

A cross-sectional qualitative study was conducted to explore stakeholders' perceptions of an mHealth application for follow-up after radical prostatectomy. Urologists, nurses, and patients treated with radical prostatectomy were interviewed, and data were transcribed and analysed using thematic analysis according to Qualitative Analysis Guide of Leuven. Recommended features for an ideal mHealth application were grouped according to the Persuasive Systems Design model.

Results and Limitations

A total of 30 stakeholders, consisting of nurse specialists (n = 7), urologists (n = 8), and patients (n = 15), were interviewed. Expected benefits and barriers were mentioned and grouped in five overarching themes: healthcare optimisation, disease management, app compliance, legal and organisational requirements, and patient-mHealth interaction. Stakeholders provided a multitude of suggestions for an ideal mHealth app. Yet, not all types of stakeholders were interviewed, and patient selection limited generalisability of findings.

Conclusions

Stakeholders indicate that an mHealth app in the care for post-prostatectomy patients can improve patient care and promote disease management but consider app compliance as a major challenge.

Patient Summary

We interviewed patients, nurses, and urologists about using an mHealth application for follow-up after radical prostatectomy. The participants agreed that an mHealth app could improve care optimisation and disease management, but some concerns and barriers were expressed. This resulted in a list of recommended features for an ideal app.

Recommendation to implementation of remote patient monitoring in rheumatology: lessons learned and barriers to take

Remote patient monitoring (RPM) leverages advanced technology to monitor and manage patients' health remotely and continuously. In 2022 European Alliance of Associations for Rheumatology (EULAR) points-to-consider for remote care were published to foster adoption of RPM, providing guidelines on where to position RPM in our practices. Sample papers and studies describe the value of RPM. But for many rheumatologists, the unanswered question remains the 'how to?' implement RPM.Using the successful, though not frictionless example of the Southmead rheumatology department, we address three types of barriers for the implementation of RPM: service, clinician and patients, with subsequent learning points that could be helpful for new teams planning to implement RPM. These address, but are not limited to, data governance, selecting high quality cost-effective solutions and ensuring compliance with data protection regulations. In addition, we describe five lacunas that could further improve RPM when addressed: establishing quality standards, creating a comprehensive database of available RPM tools, integrating data with electronic patient records, addressing reimbursement uncertainties and improving digital literacy among patients and healthcare professionals.

Patients' perspectives on digital health tools

Objective

Digital technology has changed the way healthcare is delivered and accessed. However, the focus is mostly on technology and clinical aspects. This review aimed to integrate and critically analyse the available knowledge regarding patients' perspectives on digital health tools and identify facilitators and barriers to their uptake.

Methods

A narrative review was conducted using the Scopus and Google Scholar databases. Information related to facilitators and barriers to uptake was synthesised and interpreted using thematic and content analyses, respectively.

Results

Seventy-one out of 1722 articles identified were eligible for inclusion. Patient empowerment, self-management, and personalisation were identified as the main factors that contributed to patient uptake in using digital health tools. Digital literacy, health literacy, and privacy concerns were identified as barriers to the uptake of digital health technology.

Conclusion

Digital health technologies have changed the way healthcare is experienced by patients. Research highlights the disconnect between the development and implementation of digital health tools and the patients they are created for. This review may serve as the foundation for future research incorporating patients' perspectives to help increase patients' engagement with emerging technologies.

Innovation

Participatory design approaches have the potential to support the creation of patient-centred digital health tools.

Beyond the symptoms: Personalizing giant cell arteritis care through multidimensional patient reported outcome measure

BACKGROUND

Giant Cell Arteritis (GCA) is the commonest form of systemic vasculitis in people over the age of 50. Published research highlighted the lack of a disease-specific patient reported outcomes (PROMs) for GCA.

OBJECTIVES

To assess the validity, reliability and responsiveness to change of a devised disease specific patient self-reported outcome measures questionnaire for Giant Cell Arteritis (GCA).

METHODS

The GCA-PROMs was conceptualized based on frameworks outlined in the OMERACT developed core set of Outcome Measures for Large-Vessel Vasculitis and the guiding principles of the FDA guidance. Initially, cognitive interviews were conducted to identify item pool of questions. Item selection and reduction was achieved based on patients as well as an interdisciplinary group of specialists. Rasch and internal consistency reliability analyses were implemented.

RESULTS

A total of 54 GCA patients completed the questionnaire. The GCA-PROMs questionnaire was reliable as demonstrated by a high standardized alpha (0.878-0.983). Content construct assessment of the GCA-PROMs functional disability and QoL revealed significant correlation (p< 0.01) with both HAQ and EQ-5D. Changes in functional disability, QoL showed significant (p< 0.01) variation with diseases activity status in response to therapy.

CONCLUSIONS

The developed GCA-PROMs questionnaire is a reliable and valid instrument for assessment of GCA patients. A stratified treatment regimen depending on the individual patient's risk factors as well as preferences and associated comorbidities is the best approach to tailored patient management.

Participant Engagement and Adherence to Providing Smartwatch and Patient-Reported Outcome Data: Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Real-World Study

BACKGROUND

Digital health studies using electronic patient-reported outcomes (ePROs) and wearables bring new challenges, including the need for participants to consistently provide trial data.

OBJECTIVE

This study aims to characterize the engagement, protocol adherence, and data completeness among participants with rheumatoid arthritis enrolled in the Digital Tracking of Arthritis Longitudinally (DIGITAL) study.

METHODS

Participants were invited to participate in this app-based study, which included a 14-day run-in and an 84-day main study. In the run-in period, data were collected via the ArthritisPower mobile app to increase app familiarity and identify the individuals who were motivated to participate. Successful completers of the run-in period were mailed a wearable smartwatch, and automated and manual prompts were sent to participants, reminding them to complete app input or regularly wear and synchronize devices, respectively, during the main study. Study coordinators monitored participant data and contacted participants via email, SMS text messaging, and phone to resolve adherence issues per a priori rules, in which consecutive spans of missing data triggered participant contact. Adherence to data collection during the main study period was defined as providing requested data for >70% of 84 days (daily ePRO, ≥80% daily smartwatch data) or at least 9 of 12 weeks (weekly ePRO).

RESULTS

Of the 470 participants expressing initial interest, 278 (59.1%) completed the run-in period and qualified for the main study. Over the 12-week main study period, 87.4% (243/278) of participants met the definition of adherence to protocol-specified data collection for weekly ePRO, and 57.2% (159/278) did so for daily ePRO. For smartwatch data, 81.7% (227/278) of the participants adhered to the protocol-specified data collection. In total, 52.9% (147/278) of the participants met composite adherence.

CONCLUSIONS

Compared with other digital health rheumatoid arthritis studies, a short run-in period appears useful for identifying participants likely to engage in a study that collects data via a mobile app and wearables and gives participants time to acclimate to study requirements. Automated or manual prompts (ie, "It's time to sync your smartwatch") may be necessary to optimize adherence. Adherence varies by data collection type (eg, ePRO vs smartwatch data).

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/14665.

The Clinical Impact of Electronic Patient-Reported Outcome Measures in the Remote Monitoring of Inflammatory Arthritis: A Systematic Review and Meta-analysis

OBJECTIVE

The inflammatory arthritides (IAs) make up a significant proportion of conditions followed up in rheumatology clinics. These patients require regular monitoring, but this is increasingly difficult with rising patient numbers and demand on clinics. Our objective is to evaluate the clinical impact of electronic patient-reported outcome measures (ePROMs) as a digital remote-monitoring intervention on disease activity, treatment decisions, and health care resource use in patients with IA.

METHODS

Five databases (MEDLINE, Embase, PubMed, Cochrane Library, and Web of Science) were searched, with randomized controlled trials and (nonrandomized) controlled clinical trials included, and meta-analysis and forest plots conducted for each outcome. Risk of bias was assessed using the Risk of Bias-2 tool and Risk of Bias in Nonrandomized Studies of Interventions.

RESULTS

Eight studies were included with a total of 4,473 patients, with seven studies assessing patients with rheumatoid arthritis. Compared with control, the disease activity in the ePROM group was lower (standardized mean difference [SMD] -0.15; 95% confidence interval [CI] -0.27 to -0.03) and rates of remission/low disease activity were higher (odds ratio1.65; 95% CI 1.02-2.68), but five of eight studies provided additional combined interventions (e.g., disease education). Fewer face to face visits were needed in the remote ePROM group (SMD -0.93; 95% CI -2.14-0.28).

CONCLUSION

Most studies were at high risk of bias with significant heterogeneity in design, but our results suggest there is an advantage in using ePROM monitoring in patients with IAs, with the potential for reduction in health care resource use without detrimental impact in disease outcomes.

Attitudes towards technology supported rheumatoid arthritis care: investigating patient- and clinician-perceived opportunities and barriers

Objectives

Globally, demand outstrips capacity in rheumatology services, making Mobile Health (mHealth) attractive, with the potential to improve access, empower patient self-management and save costs. Existing mHealth interventions have poor uptake by end users. This study was designed to understand existing challenges, opportunities and barriers for computer technology in the RA care pathway.

Methods

People with RA were recruited from Barts Health NHS Trust rheumatology clinics to complete paper questionnaires and clinicians were recruited from a variety of centres in the UK to complete an online questionnaire. Data collected included demographics, current technology use, challenges managing RA, RA medications and monitoring, clinic appointments, opportunities for technology and barriers to technology.

Results

A total of 109 patient and 41 clinician questionnaires were completed. A total of 83.5% of patients and 93.5% of clinicians use smartphones daily. However, only 25% had ever used an arthritis app and only 5% had persisted with one. Both groups identified managing pain, flares and RA medications as areas of existing need. Access to care, medication support and disease education were mutually agreeable opportunities; however, discrepancies existed between groups with clinicians prioritizing education over access, likely due to concerns of data overwhelm (80.6% considered this a barrier).

Conclusions

In spite of high technology use and willingness from both sides, our cohort did not utilize technology to support care, suggesting inadequacies in the existing software. The lack of an objective biomarker for RA disease activity, existing challenges in the healthcare system and the need for integration with existing technical systems were identified as the greatest barriers.

Trial registration

Registered on the Clinical Research Network registry (IRAS ID: 264690).

Patient-centric assessment of rheumatoid arthritis using a smartwatch and bespoke mobile app in a clinical setting

Rheumatoid arthritis (RA) is a fluctuating progressive disease requiring frequent symptom assessment for appropriate management. Continuous tracking using digital technologies may provide greater insights of a patient's experience. This prospective study assessed the feasibility, reliability, and clinical utility of using novel digital technologies to remotely monitor participants with RA. Participants with moderate to severe RA and non-RA controls were monitored continuously for 14 days using an iPhone with an integrated bespoke application and an Apple Watch. Participants completed patient-reported outcome measures and objective guided tests designed to assess disease-related impact on physical function. The study was completed by 28 participants with RA, 28 matched controls, and 2 unmatched controls. Completion rates for all assessments were > 97% and were reproducible over time. Several guided tests distinguished between RA and control cohorts (e.g., mean lie-to-stand time [seconds]: RA: 4.77, control: 3.25; P < 0.001). Participants with RA reporting greater stiffness, pain, and fatigue had worse guided test performances (e.g., wrist movement [P < 0.001] and sit-to-stand transition time [P = 0.009]) compared with those reporting lower stiffness, pain, and fatigue. This study demonstrates that digital technologies can be used in a well-controlled, remote clinical setting to assess the daily impact of RA.

What do people living with chronic pain want from a pain forecast? A research prioritization study

Because people with chronic pain feel uncertain about their future pain, a pain-forecasting model could support individuals to manage their daily pain and improve their quality of life. We conducted two patient and public involvement activities to design the content of a pain-forecasting model by learning participants' priorities in the features provided by a pain forecast and understanding the perceived benefits that such forecasts would provide. The first was a focus group of 12 people living with chronic pain to inform the second activity, a survey of 148 people living with chronic pain. Respondents prioritized forecasting of pain flares (100, or 68%) and fluctuations in pain severity (94, or 64%), particularly the timing of the onset and the severity. Of those surveyed, 75% (or 111) would use a future pain forecast and 80% (or 118) perceived making plans (e.g., shopping, social) as a benefit. For people with chronic pain, the timing of the onset of pain flares, the severity of pain flares and fluctuations in pain severity were prioritized as being key features of a pain forecast, and making plans was prioritized as being a key benefit.

Implementation of a hybrid healthcare model in rheumatic musculoskeletal diseases: 6-months results of the multicenter Digireuma study

OBJECTIVES

Rheumatic and musculoskeletal diseases (RMDs) require a tailored follow-up that can be enhanced by the implementation of innovative tools. The Digireuma study aimed to test the feasibility of a hybrid follow-up utilizing an electronic patient reported outcomes (ePROs)-based monitoring strategy in patients with RMDs.

METHODS

Adult patients with rheumatoid arthritis (RA) and spondyloarthritis (SpA) were recruited for a 6-month bicentric prospective follow-up consisting of face-to-face and digital assessments. Patients were asked to report disease-specific ePROs on a pre-established basis, and could also report flares, medication changes, and recent infections at any time. Four rheumatologists monitored these outcomes and contacted patients for interventions when deemed necessary. Results from face-to-face and digital assessments were described.

RESULTS

Of 56 recruited patients, 47 (84%) submitted any ePROs to the digital platform. Most patients with RA were female (74%, median age of 47 years), while 48% of patients with SpA were female (median age 40.4 years). A total of 3,800 platform visits were completed, with a median of 57 and 29 visits in patients with RA and SpA, respectively. Among 52 reported alerts, 47 (90%) needed contact, of which 36 (77%) were managed remotely. Adherence rates declined throughout the study, with around half of patients dropping out during the 6 months follow-up.

CONCLUSION

The implementation of a hybrid follow-up in clinical practice is feasible. Digital health solutions can provide granular knowledge of disease evolution and enable more informed clinical decision making, leading to improved patient outcomes. Further research is needed to identify target patient populations and engagement strategies.

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.

The natural history of chronic widespread pain in patients with axial spondyloarthritis: a cohort study with clinical and self-tracking data

OBJECTIVES

This study investigates longitudinal patterns, predictors and long-term impact of pain in axial spondyloarthritis (axSpA), using clinical and self-tracking data.

METHODS

The presence of multisite pain (MSP), affecting at least six of nine body regions using a Margolis pain drawing, and subsequent chronic widespread pain (CWP), MSP at more than one timepoint, was assessed in a cohort of axSpA patients. Incident MSP (MSP at two consecutive visits or more), intermittent MSP (MSP at two or more non-consecutive visits) and persistent MSP (MSP at each visit) were described. Demographic, clinical and self-tracking measures were compared for the CWP vs non-CWP groups using Students t test, Wilcoxon-Mann-Whitney and χ2 test for normal, non-normal and categorical data, respectively. Predictors of CWP were evaluated using logistic regression modelling.

RESULTS

A total of 136 patients, mean clinical study duration of 120 weeks (range 27-277 weeks) were included, with sufficient self-tracking data in 97 patients. Sixty-eight (50%) patients reported MSP during at least one clinical visit: eight (6%) incident MSP; 16 (12%) persistent MSP; and 44 (32%) intermittent MSP. Forty-six (34%) of the cohort had CWP. All baseline measures of disease activity, function, quality of life, sleep disturbance, fatigue and overall activity impairment were significant predictors of the development of CWP. BASDAI and BASFI scores were significantly higher in those with CWP and self-tracking data revealed significantly worse pain, fatigue, sleep quality and stress.

CONCLUSIONS

The development of CWP is predicted by higher levels of disease activity and burden at baseline. It also impacts future disease activity and wellbeing.

Remote Therapeutic Monitoring in Rheumatic and Musculoskeletal Diseases: Opportunities and Implementation

Therapeutic Monitoring (RTM) is a new program in the United States that began in 2022 allowing electronic patient-reported outcomes (ePRO) and other patient-generated data to be reviewed by clinical staff between visits so that patients can receive clinical attention as needed. Remote Therapeutic Monitoring simultaneously enhances the capacity to generate prospective longitudinal data that may be useful for secondary research purposes. As many governmental and private insurance programs in the United States now provide reimbursement for Remote Therapeutic Monitoring, increasing numbers of rheumatologists may be incentivized to provide this service for their patient populations. Launched in 2015, the ArthritisPower® Research Registry and associated mobile and desktop application, registered with the Food & Drug Administration (FDA) as a Class I medical device, enables patients to track their disease across dozens of domains and to securely participate in voluntary research studies. ArthritisPower, in partnership with Illumination Health, has developed infrastructure and a clinical workflow for Remote Therapeutic Monitoring that will help rheumatologists more closely track their patients' disease activity and flares, identify primary non-adherence, record changes in key health domains (e.g. fatigue, pain, physical function, mental health) and meet the needs for other data elements important for clinical care identified by individual providers. Ultimately, the approach to use digital health tools between visits seeks to improve clinical outcomes for patients with rheumatic and musculoskeletal diseases. This editorial review discusses the evolution of remote monitoring in rheumatologic care, describes the opportunities for physician reimbursement as of 2023, and provides a suggested workflow in order to establish Remote Therapeutic Monitoring within rheumatology practices.

Interventions Aimed at Enhancing Health Care Providers' Behavior Toward the Prescription of Mobile Health Apps: Systematic Review

BACKGROUND

Mobile health (mHealth) apps have great potential to support the management of chronic conditions. Despite widespread acceptance of mHealth apps by the public, health care providers (HCPs) are reluctant to prescribe or recommend such apps to their patients.

OBJECTIVE

This study aimed to classify and evaluate interventions aimed at encouraging HCPs to prescribe mHealth apps.

METHODS

A systematic literature search was conducted to identify studies published from January 1, 2008, to August 5, 2022, using 4 electronic databases: MEDLINE, Scopus, CINAHL, and PsycINFO. We included studies that evaluated interventions encouraging HCPs to prescribe mHealth apps. Two review authors independently assessed the eligibility of the studies. The "National Institute of Health's quality assessment tool for before-and-after (pretest-posttest design) studies with no control group" and "the mixed methods appraisal tool (MMAT)" were used to assess the methodological quality. Owing to high levels of heterogeneity between interventions, measures of practice change, specialties of HCPs, and modes of delivery, we conducted a qualitative analysis. We adopted the behavior change wheel as a framework for classifying the included interventions according to intervention functions.

RESULTS

In total, 11 studies were included in this review. Most of the studies reported positive findings, with improvements in a number of outcomes, including increased knowledge of mHealth apps among clinicians, improved self-efficacy or confidence in prescribing, and an increased number of mHealth app prescriptions. On the basis of the behavior change wheel, 9 studies reported elements of environmental restructuring such as providing HCPs with lists of apps, technological systems, time, and resources. Furthermore, 9 studies included elements of education, particularly workshops, class lectures, individual sessions with HCPs, videos, or toolkits. Furthermore, training was incorporated in 8 studies using case studies or scenarios or app appraisal tools. Coercion and restriction were not reported in any of the interventions included. The quality of the studies was high in relation to the clarity of aims, interventions, and outcomes but weaker in terms of sample size, power calculations, and duration of follow-up.

CONCLUSIONS

This study identified interventions to encourage app prescriptions by HCPs. Recommendations for future research should consider previously unexplored intervention functions such as restrictions and coercion. The findings of this review can help inform mHealth providers and policy makers regarding the key intervention strategies impacting mHealth prescriptions and assist them in making informed decisions to encourage this adoption.

A rapid review for developing a co-design framework for a pediatric surgical communication application

BACKGROUND

The exponential growth in the use of mobile health (mHealth) applications in patient care has highlighted the importance of understanding end-users' needs for successful interventions, achievable through the process of co-design. This review aims to summarize previously published uses of co-design in mHealth applications. It will inform the development of a local mHealth tool in pediatric surgery.

METHODS

The rapid review was conducted following Cochrane Rapid Review guidelines. We searched four databases from inception until August 2021 for collaborative design in mHealth apps. Two reviewers independently screened titles and abstracts using Rayyan, with a third reviewer resolving any conflicts. Studies were excluded if they were non-empirical or in other languages than English.

RESULTS

Out of 984 records screened, 175 were included for full-text screening, and 27 met all eligibility criteria. The purpose of the studies related to care support, communication, self-management or information management. All interventions involved their target audience in the co-design process, and 85% included healthcare professionals for expert opinion. Stakeholder participation was solicited via interviews, surveys, focus groups, design sessions, and prototype evaluation. To initiate the process, 15 studies included needs identification, 8 did background research, and 7 performed literature reviews.

CONCLUSION

Co-design has a positive impact on mHealth development, research processes and outcomes. Its success relies on a clearly identified framework of terminology, activities involved, and evaluation techniques. The findings of this review will be integrated into a novel co-design framework, which will be used to inform the development of a pediatric surgery mHealth application.

LEVEL OF EVIDENCE

This review uses manuscripts that are rated level III-V.

Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): An exploratory analysis of a longitudinal smartwatch feasibility study

Introduction

People living with multiple long-term conditions (MLTC-M) (multimorbidity) experience a range of inter-related symptoms. These symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices, and then summarised to provide useful clinical insight.

Aim

We aimed to perform an exploratory analysis to summarise the extent and trajectory of multiple symptom ratings tracked via a smartwatch, and to investigate the relationship between these symptom ratings and demographic factors in people living with MLTC-M in a feasibility study.

Methods

'Watch Your Steps' was a prospective observational feasibility study, administering multiple questions per day over a 90 day period. Adults with more than one clinician-diagnosed long-term condition rated seven core symptoms each day, plus up to eight additional symptoms personalised to their LTCs per day. Symptom ratings were summarised over the study period at the individual and group level. Symptom ratings were also plotted to describe day-to-day symptom trajectories for individuals.

Results

Fifty two participants submitted symptom ratings. Half were male and the majority had LTCs affecting three or more disease areas (N = 33, 64%). The symptom rated as most problematic was fatigue. Patients with increased comorbidity or female sex seemed to be associated with worse experiences of fatigue. Fatigue ratings were strongly correlated with pain and level of dysfunction.

Conclusion

In this study we have shown that it is possible to collect and descriptively analyse self reported symptom data in people living with MLTC-M, collected multiple times per day on a smartwatch, to gain insights that might support future clinical care and research.

Feasibility and acceptability to use a smartphone-based manikin for daily longitudinal self-reporting of chronic pain

Background

As management of chronic pain continues to be suboptimal, there is a need for tools that support frequent, longitudinal pain self-reporting to improve our understanding of pain. This study aimed to assess the feasibility and acceptability of daily pain self-reporting using a smartphone-based pain manikin.

Methods

For this prospective feasibility study, we recruited adults with lived experience of painful musculoskeletal condition. They were asked to complete daily pain self-reports via an app for 30 days. We assessed feasibility by calculating pain report completion levels, and investigated differences in completion levels between subgroups. We assessed acceptability via an end-of-study questionnaire, which we analysed descriptively.

Results

Of the 104 participants, the majority were female (n = 87; 84%), aged 45-64 (n = 59; 57%), and of white ethnic background (n = 89; 86%). The mean completion levels was 21 (± 7.7) pain self-reports. People who were not working (odds ratio (OR) = 1.84; 95% confidence interval (CI), 1.52-2.23) were more likely, and people living in less deprived areas (OR = 0.77; 95% CI, 0.62-0.97) and of non-white ethnicity (OR = 0.45; 95% CI, 0.36-0.57) were less likely to complete pain self-reports than their employed, more deprived and white counterparts, respectively. Of the 96 participants completing the end-of-study questionnaire, almost all participants agreed that it was easy to complete a pain drawing (n = 89; 93%).

Conclusion

It is feasible and acceptable to self-report pain using a smartphone-based manikin over a month. For its wider adoption for pain self-reporting, the feasibility and acceptability should be further explored among people with diverse socio-economic and ethnic backgrounds.

Monitoring chronic inflammatory musculoskeletal diseases mixing virtual and face-to-face assessments-Results of the digireuma study

Mobile health technology holds great promise for the clinical management of patients with chronic disease. However, evidence on the implementation of projects involving digital health solutions in rheumatology is scarce. We aimed to study the feasibility of a hybrid (virtual and face-to-face) monitoring strategy for personalized care in rheumatoid arthritis (RA) and spondyloarthritis (SpA). This project included the development of a remote monitoring model and its assessment. After a focus group with patients and rheumatologists, relevant concerns regarding the management of RA and SpA were raised, leading to the development of the Mixed Attention Model (MAM), which combined hybrid (virtual and face-to-face) monitoring. Then, a prospective study using the mobile solution Adhera for Rheumatology was conducted. Over a 3-month follow-up period, patients were given the opportunity to complete disease-specific electronic patient reported outcomes (ePROs) for RA and SpA with a pre-established frequency, as well as flares and changes in medication at any time. Number of interactions and alerts were assessed. The usability of the mobile solution was measured by the Net-Promoter Score (NPS) and through a 5-star Likert scale. Following the MAM development, forty-six patients were recruited to utilize the mobile solution, of whom 22 had RA and 24 SpA. There were 4,019 total interactions in the RA group, and 3,160 in the SpA group. Fifteen patients generated a total of 26 alerts, of which 24 were flares and 2 were medication-related problems; most (69%) were managed remotely. Regarding patient satisfaction, 65% of the respondents were considered to have endorsed Adhera for Rheumatology, yielding a NPS of 57 and an overall rating was 4.3 out of 5 stars. We concluded that the use of the digital health solution is feasible in clinical practice to monitor ePROs for RA and SpA. Next steps involve the implementation of this telemonitoring method in a multicentric setting.

Who stop telemonitoring disease activity and who adhere: a prospective cohort study of patients with inflammatory arthritis

BACKGROUND

The use of frequent electronic patient reported outcome measures (ePRO's) enables monitoring disease activity at a distance (telemonitoring) in patients with inflammatory arthritis. However, telemonitoring studies report declining long-term adherence to reporting ePRO's, which may oppose the benefits of telemonitoring. Therefore, the objective was to investigate what factors are associated with (non-)adherence to telemonitoring with a weekly ePRO in patients with inflammatory arthritis (IA).

METHODS

We performed a prospective cohort study in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS) at Reade Amsterdam, The Netherlands. Patients telemonitored their disease activity weekly for 6 months with a modified Multidimensional Health Assessment Questionnaire completed in a smartphone application. The primary outcome was time to dropout, defined as ≥ 4 weeks of consecutively nonresponse. Based on literature and through expert meetings, a predefined set of 13 baseline factors were selected to assess the association with time to dropout through a multivariable Cox-regression analysis.

RESULTS

A total of 220 consecutive patients were included (mean age 54, SD 12; 55% females; 99 RA, 81 PsA, and 40 AS). A total of 141 patients (64%) dropped out, with a median time to dropout of 17 weeks (IQR 9-26). Women had a significant higher chance to dropout over 6 months compared to men (HR 1.58, 95% CI 1.06-2.36).

CONCLUSION

In the set of investigated factors, women stopped reporting the weekly ePRO sooner than men. Future focus group discussions will be performed to investigate the reasons for dropout, and in specific why women dropped out sooner. Trial registration This trials was prospectively registered at www.trialregister.nl (NL8414).

Value-based healthcare: is it the way forward?

It is undeniable that the NHS, our universal healthcare system, is struggling to meet the needs and expectations of a population that is very different from its inception in 1948. Costs are rising inexorably and, yet, patient experience of their healthcare is often not what we would want it to be. Inequities still exist, both in terms of access to care and clinical outcome. As we spend more and more, surprisingly little is known about the extent to which we are meeting the healthcare goals and outcomes that really matter to patients. Equally, clinical teams are stretched and facing burnout as we emerge slowly from the pandemic. Meanwhile, value-based healthcare has gathered momentum worldwide as a lens through which to examine these problems. But does it provide helpful solutions? This article examines the strengths and limitations of value-based healthcare and its application in the UK context.

Development and Testing of an Electronic Health Record-Integrated Patient-Reported Outcome Application and Intervention to Improve Efficiency of Rheumatoid Arthritis Care

OBJECTIVE

Many patients with rheumatoid arthritis (RA) have difficulty finding clinicians to treat them because of workforce shortages. We developed an app to address this problem by improving care efficiency. The app collects patient-reported outcomes (PROs) and can be used to inform visit timing, potentially reducing the volume of low-value visits. We describe the development process, intervention design, and planned study for testing the app.

METHODS

We employed user-centered design, interviewing patients and clinicians, to develop the app. To improve visit efficiency, symptom tracking logic alerts clinicians to PRO trends: worsening PROs generate alerts suggesting an earlier visit, and stable or improving PROs generate notifications that scheduled visits could be delayed. An interrupted time-series analysis with a nonrandomized control population will allow assessment of the impact of the app on visit frequency.

RESULTS

Patient interviews identified several of the following needs for effective app and intervention design: the importance of a simple user interface facilitating rapid answering of PROs, the availability of condensed summary information with links to more in-depth answers to common questions regarding RA, and the need for clinicians to discuss the PRO data during visits with patients. Clinician interviews identified the following user needs: PRO data must be easy to view and use during the clinical workflow, and there should be reduced interval visits when PROs are trending worse. Some clinicians believed visits could be delayed for patients with stable PROs, whereas others raised concerns.

CONCLUSION

PRO apps may improve care efficiency in rheumatology. Formal evaluation of an integrated PRO RA app is forthcoming.

Smartphone-Assisted Patient-Initiated Care Versus Usual Care in Patients With Rheumatoid Arthritis and Low Disease Activity: A Randomized Controlled Trial

OBJECTIVE

We developed a smartphone application for patients with rheumatoid arthritis (RA) that allows them to self-monitor their disease activity in between clinic visits by answering a weekly Routine Assessment of Patient Index Data 3. This study was undertaken to assess the safety (noninferiority in the Disease Activity Score in 28 joints using the erythrocyte sedimentation rate [DAS28-ESR]) and efficacy (reduction in number of visits) of patient-initiated care assisted using a smartphone app, compared to usual care.

METHODS

A 12-month, randomized, noninferiority clinical trial was conducted in RA patients with low disease activity and without treatment changes in the past 6 months. Patients were randomized 1:1 to either app-supported patient-initiated care with a scheduled follow-up consultation after a year (app intervention group) or usual care. The coprimary outcome measures were noninferiority in terms of change in DAS28-ESR score after 12 months and the ratio of the mean number of consultations with rheumatologists between the groups. The noninferiority limit was 0.5 difference in DAS28-ESR between the groups.

RESULTS

Of the 103 randomized patients, 102 completed the study. After a year, noninferiority in terms of the DAS28-ESR score was established, as the 95% confidence interval (95% CI) of the mean ΔDAS28-ESR between the groups was within the noninferiority limit: -0.04 in favor of the app intervention group (95% CI -0.39, 0.30). The number of rheumatologist consultations was significantly lower in the app intervention group compared to the usual care group (mean ± SD 1.7 ± 1.8 versus 2.8 ± 1.4; visit ratio 0.62 [95% CI 0.47, 0.81]).

CONCLUSION

Patient-initiated care supported by smartphone self-monitoring was noninferior to usual care in terms of the ΔDAS28-ESR and led to a 38% reduction in rheumatologist consultations in RA patients with stable low disease activity.

Engagement and attrition with eHealth tools for remote monitoring in chronic arthritis: a systematic review and meta-analysis

OBJECTIVES

Although eHealth tools are potentially useful for remote disease monitoring, barriers include concerns of low engagement and high attrition. We aimed to summarise evidence on patients' engagement and attrition with eHealth tools for remotely monitoring disease activity/impact in chronic arthritis.

METHODS

A systematic literature search was conducted for original articles and abstracts published before September 2022. Eligible studies reported quantitative measures of patients' engagement with eHealth instruments used for remote monitoring in chronic arthritis. Engagement rates were pooled using random effects meta-analysis.

RESULTS

Of 8246 references, 45 studies were included: 23 using smartphone applications, 13 evaluating wearable activity trackers, 7 using personal digital assistants, 6 including web-based platforms and 2 using short message service. Wearable-based studies mostly reported engagement as the proportion of days the tracker was worn (70% pooled across 6 studies). For other eHealth tools, engagement was mostly reported as completion rates for remote patient-reported outcomes (PROs). The pooled completion rate was 80%, although between-study heterogeneity was high (I2 93%) with significant differences between eHealth tools and frequency of PRO-collection. Engagement significantly decreased with longer study duration, but attrition varied across studies (0%-89%). Several predictors of higher engagement were reported. Data on the influence of PRO-reporting frequency were conflicting.

CONCLUSION

Generally high patient engagement was reported with eHealth tools for remote monitoring in chronic arthritis. However, we found considerable between-study heterogeneity and a relative lack of real-world data. Future studies should use standardised measures of engagement, preferably assessed in a daily practice setting.

TRIAL REGISTERATION NUMBER

The protocol was registered on PROSPERO (CRD42021267936).

E-health as a sine qua non for modern healthcare

In each era we need to balance between being able to provide care with our “technical skill, scientific knowledge, and human understanding” (Harrison's Principles of Internal Medicine, 1950) to the individual patient and simultaneously ensure that our healthcare serves all. With the increasing demand of healthcare by an aging population and the lack of specialists, accessible healthcare within a reasonable time frame is not always guaranteed. E-health provides solutions for current situations where we do not meet our own aims of good healthcare, such as restrictions in access to care and a reduction in care availability by a reducing workforce. In addition, telemedicine offers opportunities to improve our healthcare beyond what is possible by in person visits. However, e-health is often viewed as an deficient version of healthcare of low quality. We disagree with this view. In this article we will discuss how to position e-health in the current situation of healthcare, given the continuing rapid development of digital technologies and the changing needs of healthcare professionals and patients. We will address the evolution of e-health towards connected and intelligent systems and the stakeholders perspective, aiming to open up the discussion on e-Health.

Monitoring of Disease Activity With a Smartphone App in Routine Clinical Care in Patients With Axial Spondyloarthritis

OBJECTIVE

To investigate the performance of a health app with respect to usability, adherence, and equivalence of data in daily care of patients with axial spondyloarthritis (axSpA).

METHODS

Consecutive patients with axSpA were asked to export patient-reported outcomes (PRO) electronically with the AxSpA Live App regularly every 2 weeks over a period of 6 months. The first clinical visit was followed by 2 further personal visits after 3 and 6 months. Patients completed paper-based PRO at every visit; they also completed the Mobile App Rating Scale and the System Usability Scale after 3 and 6 months.

RESULTS

Of 103 patients with axSpA, 69 agreed to participate (67.0%): age 41.5 (11.3) years, 58.0% male, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) 4.3 (2.0), and 76.8% treated with biologic disease-modifying antirheumatic drugs. Patients' adherence to regular app exports was 29.0% and 28.4% after 3 and 6 months, respectively. Significant predictors for good adherence were high disease activity (P = 0.02) and older age (P = 0.04). No systematic differences between digital and paper-based BASDAI scores were found (intraclass correlation coefficients 0.99 [95% CI 0.98-0.99]). Performance of the app was rated as good.

CONCLUSION

Collection of digital PROs by AxSpA Live App may be successfully used in patients with axSpA with high disease activity. Our study showed equivalence of digital data, but adherence to the app after 6 months was poor. Higher disease activity and older age resulted in increased adherence to the app. This suggests that the use of health apps like this should concentrate on more severely affected patients.

Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs)

Health care processes are under constant development and will need to embrace advances in technology and health science aiming to provide optimal care. Considering the perspective of increasing treatment options for people with rheumatic and musculoskeletal diseases, but in many cases not reaching all treatment targets that matter to patients, care systems bare potential to improve on a holistic level. This review provides an overview of systems and technologies under evaluation over the past years that show potential to impact diagnosis and treatment of rheumatic diseases in about 10 years from now. We summarize initiatives and studies from the field of electronic health records, biobanking, remote monitoring, and artificial intelligence. The combination and implementation of these opportunities in daily clinical care will be key for a new era in care of our patients. This aims to inform rheumatologists and healthcare providers concerned with chronic inflammatory musculoskeletal conditions about current important and promising developments in science that might substantially impact the management processes of rheumatic diseases in the 2030s.

The Use of Mobile Health Apps in Clinical Practice Remains Challenging

According to several international recommendations, disease activity should be regularly monitored with validated outcome measures in patients with axial spondyloarthritis (axSpA), and therapy should be adapted accordingly.^1-3 Increasingly, healthcare providers are encouraged to also use patient-reported outcomes (PROs) for this purpose, to capture valuable data from the patient's perspective.

Smartphones for musculoskeletal research - hype or hope? Lessons from a decennium of mHealth studies

BACKGROUND

Smartphones provide opportunities for musculoskeletal research: they are integrated in participants' daily lives and can be used to collect patient-reported outcomes as well as sensor data from large groups of people. As the field of research with smartphones and smartwatches matures, it has transpired that some of the advantages of this modern technology are in fact double-edged swords. BODY: In this narrative review, we illustrate the advantages of using smartphones for data collection with 18 studies from various musculoskeletal domains. We critically appraised existing literature, debunking some myths around the advantages of smartphones: the myth that smartphone studies automatically enable high engagement, that they reach more representative samples, that they cost little, and that sensor data is objective. We provide a nuanced view of evidence in these areas and discuss strategies to increase engagement, to reach representative samples, to reduce costs and to avoid potential sources of subjectivity in analysing sensor data.

CONCLUSION

If smartphone studies are designed without awareness of the challenges inherent to smartphone use, they may fail or may provide biased results. Keeping participants of smartphone studies engaged longitudinally is a major challenge. Based on prior research, we provide 6 actions by researchers to increase engagement. Smartphone studies often have participants that are younger, have higher incomes and high digital literacy. We provide advice for reaching more representative participant groups, and for ensuring that study conclusions are not plagued by bias resulting from unrepresentative sampling. Costs associated with app development and testing, data storage and analysis, and tech support are substantial, even if studies use a 'bring your own device'-policy. Exchange of information on costs, collective app development and usage of open-source tools would help the musculoskeletal community reduce costs of smartphone studies. In general, transparency and wider adoption of best practices would help bringing smartphone studies to the next level. Then, the community can focus on specific challenges of smartphones in musculoskeletal contexts, such as symptom-related barriers to using smartphones for research, validating algorithms in patient populations with reduced functional ability, digitising validated questionnaires, and methods to reliably quantify pain, quality of life and fatigue.

Using patient-reported data from a smartphone app to capture and characterise real-time patient-reported flares in rheumatoid arthritis

Objective

We aimed to explore the frequency of self-reported flares and their association with preceding symptoms collected through a smartphone app by people with RA.

Methods

We used data from the Remote Monitoring of RA study, in which patients tracked their daily symptoms and weekly flares on an app. We summarized the number of self-reported flare weeks. For each week preceding a flare question, we calculated three summary features for daily symptoms: mean, variability and slope. Mixed effects logistic regression models quantified associations between flare weeks and symptom summary features. Pain was used as an example symptom for multivariate modelling.

Results

Twenty patients tracked their symptoms for a median of 81 days (interquartile range 80, 82). Fifteen of 20 participants reported at least one flare week, adding up to 54 flare weeks out of 198 participant weeks in total. Univariate mixed effects models showed that higher mean and steeper upward slopes in symptom scores in the week preceding the flare increased the likelihood of flare occurrence, but the association with variability was less strong. Multivariate modelling showed that for pain, mean scores and variability were associated with higher odds of flare, with odds ratios 1.83 (95% CI, 1.15, 2.97) and 3.12 (95% CI, 1.07, 9.13), respectively.

Conclusion

Our study suggests that patient-reported flares are common and are associated with higher daily RA symptom scores in the preceding week. Enabling patients to collect daily symptom data on their smartphones might, ultimately, facilitate prediction and more timely management of imminent flares.

Investigating characteristics of idiopathic inflammatory myopathy flares using daily symptom data collected via a smartphone app

OBJECTIVE

The objective of this study was to use daily data collected via a smartphone app for characterization of patient-reported and symptom-based (using an a priori definition) flares in an adult idiopathic inflammatory myopathy (IIM) cohort.

METHODS

UK adults with an IIM answered patient-reported outcome measurements (PROMs) daily via a smartphone app during a 91-day study. Daily symptom PROMs addressed global activity, overall pain, myalgia, fatigue, and weakness (on a 0-100 visual analogue scale). Patient-reported flares were recorded via a weekly app question. Symptom-based flares were defined via an a priori definition related to increase in daily symptom data from the previous 4-day mean.

RESULTS

Twenty participants (65% female) participated. Patient-reported flares occurred on a median of 5 weeks (IQR 3, 7) per participant, out of a possible 13. The mean of each symptom score was significantly higher in flare weeks, compared with non-flare weeks (e.g. mean flare week myalgia score 34/100, vs 21/100 during non-flare week, t test P-value <0.01). Fatigue accounted for the most symptom-based flares [incidence-rate 23/100 person-days (95% CI 19, 27)], and myalgia the fewest [incidence rate 13/100 person-days (95% CI 11, 16)]. Symptom-based flares typically resolved after 3 days, although fatigue-predominant flares lasted 2 days. The majority (69%) of patient-reported flare weeks coincided with at least one symptom-based flare.

CONCLUSIONS

IIM flares are frequent and associated with increased symptom scores. This study has demonstrated the ability to identify and characterize patient-reported and symptom-based flares (based on an a priori definition), using daily app-collected data.

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

OBJECTIVE

Utilizing patient-generated health data (PGHD) in clinical consultations and informing clinical and shared decision-making processes has the potential to improve clinical practice but has proven challenging to implement. Looking at consultations between people with rheumatoid arthritis (RA) and rheumatologists, this study examines when and how daily PGHD was discussed in outpatient consultations.

METHODS

We conducted a secondary qualitative analysis of 17 audio-recorded research outpatient consultations using thematic and interactional approaches.

RESULTS

Clinicians decided when to look at the PGHD and what symptoms to prioritise during the consultation. When PGHD was introduced early in consultations, it was usually used to invite patients to collaborate (elicit new information). When introduced later, PGHD was used to corroborate patient accounts and to convince the patient about proposed actions and treatments. Clinicians occasionally disregarded PGHD if it did not fit into their clinical assessment.

CONCLUSION

The time that PGHD is introduced may influence how PGHD is used in consultations. Further research is needed to understand how best to empower patients to discuss PGHD.

PRACTICE IMPLICATIONS

Educating patients and clinicians about the importance of timing and strategies when using PGHD in consultations may help promote shared decision-making.

Patient Reported Outcome Measures for Rheumatoid Arthritis Disease Activity: a systematic review following COSMIN guidelines

BACKGROUND

The current standard of care in rheumatoid arthritis (RA) requires regular assessment of disease activity (DA). All standard RA DA measurement instruments require joint counts to be undertaken by a healthcare professional with/without a blood test. Few healthcare providers have the capacity to assess patients as frequently as stipulated by guidelines. Patient Reported Outcome Measures (PROMs) could be an efficient and informative way to assess RA DA, which is highlighted by the SARS-COV-2 pandemic, as most consultations are remote rather than face-to-face. We aimed to assess all PROMs for RA DA against the internationally recognised COSMIN guidelines to provide evidence-based recommendations to select the most suitable PROMs.

METHODS

Review registered on PROSPERO as CRD42020176176. The search strategy was based on a previous similar systematic review and expanded to include all articles up to January 2019. All identified articles were rated by two independent assessors following the COSMIN guidelines.

RESULTS

668 abstracts were identified, with 10 articles included. A further 21 were identified from a previous review. Ten PROMs were identified. There was insufficient evidence to place any of the identified PROMs into recommendation for use category A due to lack of evidence for content validity, as stipulated by the COSMIN guidelines.

CONCLUSION

Lack of evidence of content validity limits suitable PROM selection, therefore none can be recommended for use. It is acknowledged that all included PROMs were developed before the COSMIN guidelines were published. Future research on PROMs for RA DA must provide evidence of content validity.

Collecting and sharing self-generated health and lifestyle data: Understanding barriers for people living with long-term health conditions - a survey study

Background

The growing popularity of collecting self-generated health and lifestyle data presents a valuable opportunity to develop our understanding of long-term health conditions and improve care. Barriers remain to the effective sharing of health and lifestyle data by those living with long-term health conditions which include beliefs around concepts of Trust, Identity, Privacy and Security, experiences of stigma, perceptions of risk and information sensitivity.

Method

We surveyed 250 UK adults who reported living with a range of long-term health conditions. We recorded data to assess self-reported behaviours, experiences, attitudes and motivations relevant to sharing self-generated health and lifestyle data. We also asked participants about their beliefs about Trust, Identity, Privacy and Security, stigma, and perceptions of risk and information sensitivity regarding their health and lifestyle data.

Results

Three-quarters of our sample reported recording information about their health and lifestyle on a daily basis. However, two-thirds reported never or rarely sharing this information with others. Trust, Identity, Privacy and Security concerns were considered to be 'very important' by those with long-term health conditions when deciding whether or not to share self-generated health and lifestyle data with others, with security concerns considered most important. Of those living with a long-term health condition, 58% reported experiencing stigma associated with their condition. The greatest perceived risk from sharing with others was the potential for future harm to their social relationships.

Conclusions

Our findings suggest that, in order for health professionals and researchers to benefit from the increased prevalence of self-generated health and lifestyle data, more can be done to address security concerns and to understand perceived risks associated with data sharing. Digital platforms aimed at facilitating the sharing of self-generated health and lifestyle data may look to highlight security features, enable users to control the sharing of certain information types, and emphasise the practical benefits to users of sharing health and lifestyle data with others.

Towards an effective framework for integrating patient-reported outcomes in electronic health records

Background

In the past decade, electronic modalities are increasingly deployed to integrate patient-reported outcomes into electronic health records. Most popularly, patient portals are used for remote questionnaires, and tablets are provided to patients in-office in case they need help. They are both useful. But some barriers are still in the way, which place burdens on patients and clinicians in the process of routine data collection.

Objective

This study aims to describe a portable and scalable framework which can simplify the patient-reported outcome integration by mitigating the related burdens.

Methods

A framework was proposed to use a modular approach to replace the tethered approach. The framework was open-sourced on GitHub. After development and testing, it was evaluated on an instrument with 24 questions in a real clinical setting. Patients were randomly selected in every modality-based group. For objective analysis, completion time and response rate were collected. No-show data was collected and analyzed. For subjective analysis, the NASA Task Load Index was used to measure workload, and the Net Promoter Score was used to assess user satisfaction.

Results

The model could contain 46,656 questions. A quick response code could store 1120 encoded items. For remote visits, the response rate was improved compared to the portal group (76.6% vs. 61.1%). The completion time was reduced by 37.5% when compared to the tablet group and was reduced by 43.4% when compared to the portal group. The workload for clinicians and patients was both reduced significantly (p < 0.001). A higher Net Promoter Score was rated by both clinicians (89.3%) and patients (86.5%). Compared to the portal group, the no-show rate was reduced (11.7% vs. 8.6%).

Conclusions

Collecting patient-reported outcomes over a quick response code appears to be an alternative modality to enable a simplified integration. This study provides new insights to collect patient-reported outcomes with interoperability and substitutability in mind.

TELERA-Asynchronous TELEmedicine for Patients With Rheumatoid Arthritis: Study Protocol for a Prospective, Multi-Center, Randomized Controlled Trial

Innovative strategies are needed to adequately assess and monitor disease activity of patients with rheumatoid arthritis (RA) in times of scarce appointments. The aim of the TELERA study is to evaluate the feasibility and performance of asynchronous telemedicine visits based on patient-generated data and patient's drug history. RA patients use a medical app, ABATON, that captures the results of a self-performed quick CRP-test, joint-count, and electronic patient-reported outcomes in between visits. This is a prospective, multi-center, randomized controlled trial performed in four German university centers. The estimated sample size is 120 patients. The main outcome is the agreement of rheumatologists' treatment decisions based on asynchronous telemedicine patient-generated data with traditional in-person rheumatology clinic-based decisions and with patient suggestions. The TELERA trial will provide evidence regarding the implementation of remote care in rheumatology. Clinical Trial Registration: This clinical trial was registered at German Registry for Clinical Trials (DRKS). http://www.drks.de/DRKS00016350, identifier: DRKS00024928.

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.

[Telemedical care and IT-based systems in rheumatology]

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic and also the ever-increasing demands on the healthcare system, have led to a focus on the further development of telemedical services in rheumatology.

OBJECTIVE

What is the evidence for telemedical services in rheumatology?

MATERIAL AND METHODS

Narrative review of existing literature on telemedicine in rheumatology.

RESULTS

Electronic patient reported outcomes (ePROs) can be determined by patients from their home and sent electronically to the rheumatologist. In future, ePROs may help with the decision whether a patient needs to attend the clinic for a visit or the visit can be rescheduled due to remission and well-being. Telemedicine has already been used for well-controlled patients with rheumatic diseases with good results in terms of safety and disease activity compared to conventional face-to-face visits. Telemedicine represents an interesting tool for appointment prioritization and triaging, while automated algorithm-based applications are currently too imprecise for routine clinical use. The role of smartphone applications in the care of patients with rheumatic diseases is still unclear.

DISCUSSION

Telemedicine represents an interesting option for certain patient populations with rheumatic diseases. Apart from research on the effectiveness and safety of telemedical interventions, decision makers need to set clear rules on how telemedicine should be used to provide the best possible care for the individual patient.

Understanding flare in axial spondyloarthritis: novel insights from daily self-reported flare experience

OBJECTIVES

Our objective was to explore daily self-reported experiences of axial SpA (axSpA) flare based on data entered into the Project Nightingale smartphone app (www.projectnightingale.org), between 5 April 2018 and 1 April 2020.

METHODS

Paired t-tests were conducted for mean_flare_on and mean_flare_off scores for each recorded variable. The mean estimated difference between flare and non-flare values for each variable was calculated with 95% CIs. Mean, S.d. and range were reported for flare duration and frequency. Participants with ≥10 days of data entry were included for affinity propagation cluster analysis. Baseline characteristics and mean flare on vs mean flare off values were reported for each cluster. Welch's t-test was used to assess differences between clusters.

RESULTS

A total of 143/189 (75.7%) participants recorded at least one flare. Each flare lasted a mean of 4.30 days (S.d. 6.82, range 1-78), with a mean frequency of once every 35.32 days (S.d. 65.73, range 1-677). Significant relationships were identified between flare status and variable scores. Two clusters of participants were identified with distinct flare profiles. Group 1 experienced less severe worsening of symptoms during flare in comparison to group 2 (P < 0.01). However, they experienced significantly longer flare duration (7.2 vs 3.5 days; P < 0.01), perhaps indicating a prolonged, yet less intense flare experience. Groups were similar in terms of flare frequency and clinical characteristics.

CONCLUSIONS

Two clusters of participants were identified with distinct flare experiences but similar baseline clinical characteristics. Smartphone technologies capture subtle changes in disease experience not currently considered in clinical practice.