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

Authors: Jutta G. Richter; Gamal Chehab; Catarina Schwartz; Elisabeth Ricken; Monika Tomczak; Hasan Acar; Henrike Gappa; +5 Authors

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

Abstract

Abstract Background Multimorbidity raises the number of essential information needed for delivery of high-quality care in patients with chronic diseases like rheumatoid arthritis (RA). We evaluated an innovative ICT platform for integrated care which orchestrates data from various health care providers to optimize care management processes. Methods The Horizon2020-funded research project PICASO (picaso-project.eu) established an ICT platform that offers integration of care services across providers and supports patients’ management along the continuum of care, leaving the data with the owner. Strict conformity with ethical and legal legislations was augmented with a usability-driven engineering process, user requirements gathering from relevant stakeholders, and expert walkthroughs guided developments. Developments based on the HL7/FHIR standard granting interoperability. Platform’s applicability in clinical routine was an essential aim. Thus, we evaluated the platform according to an evaluation framework in an observational 6-month proof-of-concept study with RA patients affected by cardiovascular comorbidities using questionnaires, interviews, and platform data. Results Thirty RA patients (80% female) participated, mean age 59 years, disease duration 13 years, average number of comorbidities 2.9. Home monitoring data demonstrated high platform adherence. Evaluations yielded predominantly positive feedback: The innovative dashboard-like design offering time-efficient data visualization, comprehension, and personalization was well accepted, i.e., patients rated the platform “overall” as 2.3 (1.1) (mean (SD), Likert scales 1–6) and clinicians recommended further platform use for 93% of their patients. They managed 86% of patients’ visits using the clinician dashboard. Dashboards were valued for a broader view of health status and patient-physician interactions. Platform use contributed to improved disease and comorbidity management (i.e., in 70% physicians reported usefulness to assess patients’ diseases and in 33% potential influence on treatment decisions; risk manager was used in 59%) and empowered patients (i.e., 48% set themselves new health-related goals, 92% stated easier patient-physician communications). Conclusion Comprehensive aggregation of clinical data from distributed sources in a modern, GDPR-compliant cloud platform can improve physicians’ and patients’ knowledge of the disease status and comorbidities as well as patients’ management. It empowers patients to monitor and positively contribute to their disease management. Effects on patients’ outcome, behavior, and changes in the health care systems should be explored by implementing ICT-based platforms enriched by upcoming Artificial Intelligence features where possible. Trial registration DRKS—German Clinical Trials Register, DRKS00013637, prospectively registered. 17 January 2018.

Keywords

Male, User experience design, Diseases of the musculoskeletal system, Arthritis, Rheumatoid, Artificial Intelligence, Humans, ICT platform, Rheumatoid arthritis, Physician-Patient Relations, Female [MeSH] ; Physician-Patient Relations [MeSH] ; User experience design ; Humans [MeSH] ; Rheumatoid arthritis ; Usability engineering ; ICT platform ; Middle Aged [MeSH] ; Cloud Computing [MeSH] ; eHealth ; Artificial Intelligence [MeSH] ; Male [MeSH] ; Chronic Disease [MeSH] ; Research Article ; Cloud ; Arthritis, Rheumatoid [MeSH], Cloud Computing, Middle Aged, Usability engineering, RC925-935, Chronic Disease, eHealth, Female, Cloud, Research Article

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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
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gold