The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment-experiences of patients and clinicians

Design of a Self-Measuring Device Based on Bioelectrical Impedance Analysis for Regular Monitoring of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic disease, in which permanent joint deformation is largely preventable with the timely introduction of appropriate treatment strategies. However, there is no consensus for patients with RA to monitor their progress and communicate it to the rheumatologist till the condition progresses to remission. In response to this unmet need, we proposed the design of a self-measuring device based on bioelectrical impedance analysis (BIA) for regular monitoring of inflammation levels. Twenty joints of both hands were measured to monitor trends in inflammation levels. Three electrodes were used to measure two joints of each finger. A central electrode was used for two consecutive measurements. A suitable form factor for the device was proposed for the vertical placement of the hand. To ensure the stability of measurements, an air cushion was incorporated into the back of the hand, hand containers were designed on both sides, and a mobile application was designed. We conducted a convergence-assessment experiment with five air pressures to validate the consistency and convergence of bioimpedance measurements. A heuristic evaluation of the usability around the product and mobile application was conducted in parallel by six subject matter experts and validated the design. This study underscores the significance of considering patients' disease activity during intervals between hospital visits and introduces a novel approach to self-RA care.

Toward an Interdisciplinary Approach to Constructing Care Delivery Pathways From Electronic Health Care Databases to Support Integrated Care in Chronic Conditions: Systematic Review of Quantification and Visualization Methods

BACKGROUND

Electronic health care databases are increasingly used for informing clinical decision-making. In long-term care, linking and accessing information on health care delivered by different providers could improve coordination and health outcomes. Several methods for quantifying and visualizing this information into data-driven care delivery pathways (CDPs) have been proposed. To be integrated effectively and sustainably into routine care, these methods need to meet a range of prerequisites covering 3 broad domains: clinical, technological, and behavioral. Although advances have been made, development to date lacks a comprehensive interdisciplinary approach. As the field expands, it would benefit from developing common standards of development and reporting that integrate clinical, technological, and behavioral aspects.

OBJECTIVE

We aimed to describe the content and development of long-term CDP quantification and visualization methods and to propose recommendations for future work.

METHODS

We conducted a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) recommendations. We searched peer-reviewed publications in English and reported the CDP methods by using the following data in the included studies: long-term care data and extracted data on clinical information and aims, technological development and characteristics, and user behaviors. The data are summarized in tables and presented narratively.

RESULTS

Of the 2921 records identified, 14 studies were included, of which 13 (93%) were descriptive reports and 1 (7%) was a validation study. Clinical aims focused primarily on treatment decision-making (n=6, 43%) and care coordination (n=7, 50%). Technological development followed a similar process from scope definition to tool validation, with various levels of detail in reporting. User behaviors (n=3, 21%) referred to accessing CDPs, planning care, adjusting treatment, or supporting adherence.

CONCLUSIONS

The use of electronic health care databases for quantifying and visualizing CDPs in long-term care is an emerging field. Detailed and standardized reporting of clinical and technological aspects is needed. Early consideration of how CDPs would be used, validated, and implemented in clinical practice would likely facilitate further development and adoption.

TRIAL REGISTRATION

PROSPERO CRD42019140494; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=140494.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2019-033573.

Evaluation of the use of video consultation in German rheumatology care before and during the COVID-19 pandemic

Background

The COVID-19 pandemic led to transformations in healthcare infrastructures and increased use of (innovative) telemedicine (TM) tools. Comparison of the use of video consultation (VC) in rheumatology in the pre-pandemic period and during the pandemic might allow for evaluating this new form of consultancy in healthcare due to changing conditions and possibilities.

Materials and methods

Cross-sectional nationwide online survey among German rheumatologists and rheumatologists in training between March and May 2021 promoted by newsletters and Twitter posts.

Results

Results refer to 205 participants. The majority was male (59%), older than 40 years (90%). Thirty-eight percent stated to have employed TM before ("digital users"), 27% were using VC as part of their TM expertise ("VC-users"), 10% stated to have experience with TM but not VC ("TM-users"). Those negating the use of any TM (62%) were designated as "digital non-users." TM-Knowledge was self-rated as 4 [median on a Likert Scale 1 (very high) to 6 (very low)] with a significant difference between digital users (VC-user 2.7 ± 1.2, TM-user 3.2 ± 1.1) and digital non-users (4.4 ± 1.3). The reported significant increase of VC use during the lockdown periods and between the lockdowns compared to the pre-pandemic phase was regarded as a proxy for VC acceptance in the pandemic. Reasons for VC non-use were administrative/technical efforts (21%), lack of technical equipment (15%), time constraints (12%), time required for individual VC sessions (12%), inadequate reimbursement (11%), lack of demand from patients (11%), data security concerns (9%), poor internet connection (8%), and lack of scientific evaluation/evidence (5%). Physicians considered the following clinical situations to be particularly suitable for VC: follow-up visits (VC-user 79%, TM-user 62%, digital non-user 47%), emergency consultations (VC-user 20%, TM-user 33%, digital non-user 20%), and patients presenting for the first time (VC-user 11%, TM-user 19%, digital non-user 8%).

Conclusion

Even though the pandemic situation, with social distancing and several lockdowns, provides an ideal environment for the implementation of new remote care forms as VC, its use and acceptance remained comparatively low due to multiple reasons. This analysis may help identify hurdles in employing innovative digital care models for rheumatologic healthcare.

One year of digital health applications (DiGA) in Germany - Rheumatologists' perspectives

BACKGROUND

Based on given legislation the German approach to digital health applications (DiGA) allows reimbursed prescription of approved therapeutic software products since October 2020. For the first time, we evaluated DiGA-related acceptance, usage, and level of knowledge among members of the German Society for Rheumatology (DGRh) 1 year after its legal implementation.

MATERIALS AND METHODS

An anonymous cross-sectional online survey, initially designed by the health innovation hub (think tank and sparring partner of the German Federal Ministry of Health) and the German Pain Society was adapted to the field of rheumatology. The survey was promoted by DGRh newsletters and Twitter-posts. Ethical approval was obtained.

RESULTS

In total, 75 valid response-sets. 80% reported to care ≥ 70% of their working time for patients with rheumatic diseases. Most were working in outpatient clinics/offices (54%) and older than 40 years (84%). Gender distribution was balanced (50%). 70% knew the possibility to prescribe DiGA. Most were informed of this for the first time via trade press (63%), and only 8% via the scientific/professional society. 46% expect information on DiGA from the scientific societies/medical chambers (35%) but rarely from the manufacturer (10%) and the responsible ministry (4%). Respondents would like to be informed about DiGA via continuing education events (face-to-face 76%, online 84%), trade press (86%), and manufacturers' test-accounts (64%). Only 7% have already prescribed a DiGA, 46% planned to do so, and 47% did not intend DiGA prescriptions. Relevant aspects for prescription are provided. 86% believe that using DiGA/medical apps would at least partially be feasible and understandable to their patients. 83% thought that data collected by the patients using DiGA or other digital solutions could at least partially influence health care positively. 51% appreciated to get DiGA data directly into their patient documentation system/electronic health record (EHR) and 29% into patient-owned EHR.

CONCLUSION

Digital health applications awareness was high whereas prescription rate was low. Mostly, physician-desired aspects for DiGA prescriptions were proven efficacy and efficiency for physicians and patients, risk of adverse effects and health care costs were less important. Evaluation of patients' barriers and needs is warranted. Our results might contribute to the implementation and dissemination of DiGA.

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.

[Digital Transformation of Healthcare: A Delphi Study of the Working Groups Digital Health and Validation and Linkage of Secondary Data of the German Network for Health Services Research (DNVF)]

AIM OF THE STUDY

The digital transformation in healthcare is also of fundamental importance for healthcare research. For this reason, experts should agree on, prioritize and identify key topics for a medium-term strategy of the German Network for Health Services Research and classify the general development of digital health in the context of health services research.

METHODS

Between April and September 2018, the working groups "Digital Health" and "Validation and Linkage of Secondary Data" of the German Network for Health Services Research were asked to submit their expertise online using the methodological approach of a Delphi study. For this purpose, a multi-stage modified Delphi method with quantitative and qualitative approaches was chosen. Initially, a list of theses was drawn from the network's published position papers on digital health applications and medical apps. A total of 131 statements were formulated. The final survey instrument included questions on the biographical background of the participants, 42 developed items (33 statements and 8 open-ended questions), and one free-text field to add further aspects. Items were evaluated with a five-point Likert scale. A statement was accepted if the agreement rate was 75% or higher.

RESULTS

Of the 110 potential participants, 50 (46%) took part in the first round and 39 (36%) in the second round of the Delphi survey. In the first round, there was a clear result for 24 of 33 statements. There were 20 statements "agreed with" and four "disagreed with." Nine statements were between 60 and 75% and were presented to the participants again for evaluation in the second round. In round two, of these nine statements, four statements were "agreed with" and five statements were "disagreed with." Digital Health Literacy" emerged as a particular focus in this Delphi study.

CONCLUSION

In this Delphi study, experts were involved in selecting and prioritizing possible topics for the Digital Health working group and assessing future developments in digital health in the context of health services research. The results reflect both the expectations and interests of the members and are largely consistent with the recommendations of the report "Digitalization for Health" made by the expert council for assessing developments in the health sector.

Digitalization and disruptive change in rheumatology

INTRODUCTION

Recently, many sectors have seen disruptive changes due to the rapid progress in information and communication technology (ICT). The aim of this systematic literature review was to develop a first understanding of what is known about new ICTs in rheumatology and their disruptive potential.

METHODS

PubMed, LIVIVO, and EBSCO Discovery Service (EDS) databases were searched for relevant literature. Use of new ICTs was identified, categorized, and disruptive potential was discussed. Articles from 2008 to 2021 in German and English were considered.

RESULTS

A total of 3539 articles were identified. After application of inclusion/exclusion criteria, 55 articles were included in the analyses. The majority of articles (48) used a non-experimental design or detailed expert opinion. The new ICTs mentioned in these articles could be allocated to four main categories: technologies that prepare for the development of new knowledge by data collection (n = 32); technologies that develop new knowledge by evaluation of data (e.g., by inventing better treatment; n = 11); technologies that improve communication of existing knowledge (n = 32); and technologies that improve the care process (n = 29). Further assessment classified the ICTs into different functional subcategories. Based on these categories it is possible to estimate the disruptive potential of new ICTs.

CONCLUSION

ICTs are becoming increasingly important in rheumatology and may impact patients' lives and professional conduct. The properties and disruptive potential of technologies identified in the articles differ widely. When looking into ICTs, doctors have focused on new diagnostic and therapeutic procedures but rarely on their disruptive potential. We recommend putting more effort into investigation of whether ICTs change the way rheumatology is performed and who is in control of it. Especially technologies that potentially replace physicians with machines, take control over the definition of quality in medicine, and/or create proprietary knowledge that is not accessible for doctors need more research.

Computer Vision-Based Medical Cloud Data System for Back Muscle Image Detection

The fast development of image recognition and information technology has influenced people's life and industry management mode not only in some common fields such as information management, but also has very much improved the working efficiency of various industries. In the healthcare field, the current highly disparate doctor–patient ratio leads to more and more doctors needing to undertake more and more patient treatment tasks. Back muscle image detection can also be considered a task in medical image processing. Similar to medical image processing, back muscle detection requires first processing the back image and extracting semantic features by convolutional neural networks, and then training classifiers to identify specific disease symptoms. To alleviate the workload of doctors in recognizing CT slices and ultrasound detection images and to improve the efficiency of remote communication and interaction between doctors and patients, this paper designs and implements a medical image recognition cloud system based on semantic segmentation of CT images and ultrasound recognition images. Accurate detection of back muscles was achieved using the cloud platform and convolutional neural network algorithm. Upon final testing, the algorithm of this system partially meets the accuracy requirements proposed by the requirements. The medical image recognition system established based on this semantic segmentation algorithm is able to handle all aspects of medical workers and patients in general in a stable manner and can perform image segmentation processing quickly within the required range. Then, this paper explores the effect of muscle activity on the lumbar region based on this system.

Mobile Responsive App-A Useful Additional Tool for Data Collection in the German Pregnancy Register Rhekiss?

Background: The German pregnancy register Rhekiss is designed as a nationwide, web-based longitudinal observational cohort established in 2015. The register follows women with inflammatory rheumatic disease prospectively from child wish or early pregnancy until 2 years post-partum. Information on clinical and laboratory parameters, drug treatment, and (adverse) pregnancy outcomes are documented in pre-specified intervals. Physicians and patients report data for the same time periods via separated accounts and forms into a web-based application (app). As data entry on mobile devices might improve response rates of patients, a responsive app as a further convenient documentation option was developed.

Methods: The Rhekiss-app is available for self-reported data retrieval since August 2017 from the App stores. For the current analysis, Rhekiss register data were used from the start of the register until 30 September 2020. The analyses were performed for forms containing information on devices. Outcome parameters were compared for mobile and desktop users for the quantity and quality of filled forms.

Results: In total, 5,048 forms were received and submitted by 966 patients. About 57% of forms were sent from mobile devices with the highest numbers in patients with child wishes (63%). Users of mobile devices were slightly younger and often had less high-education level (62 vs. 79%) compared with desktop users. The proportion of forms submitted via mobile devices increased steadily from 48% in the fourth quarter of 2018 to 64% in the third quarter of 2020. The proportion of forms received before and after the Rhekiss-app implementation increased with the highest increase of 12% for forms filled at time point 12 months post-partum. Mobile users submitted significantly more forms than desktop users (2.9 vs. 2.1), data sent via desktops were more often complete (88 vs. 86%).

Conclusion: The responsive app is a valuable additional tool for data collection and is well-accepted by patients as indicated by its increasing use in Rhekiss. Apart from desktop/browser developments, the technological adoptions within observational cohorts and registries should take smartphone requirements and developments into account, especially when patient-reported data in young, mobile patients are collected, bearing in mind that data quality could be compromised and concepts for improving data quality should be implemented.