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1000 Titel
  • The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians
1000 Autor/in
  1. Richter, Jutta G. |
  2. Chehab, Gamal |
  3. Schwartz, Catarina |
  4. Ricken, Elisabeth |
  5. Tomczak, Monika |
  6. Acar, Hasan |
  7. Gappa, Henrike |
  8. Velasco, Carlos A. |
  9. Rosengren, Peter |
  10. Povilionis, Armanas |
  11. Schneider, Matthias |
  12. Thestrup, Jesper |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-05-27
1000 Erschienen in
1000 Quellenangabe
  • 23(1):151
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13075-021-02526-7 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157758/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Sacherschließung
lokal Female [MeSH]
lokal Physician-Patient Relations [MeSH]
lokal User experience design
lokal Humans [MeSH]
lokal Rheumatoid arthritis
lokal Usability engineering
lokal ICT platform
lokal Middle Aged [MeSH]
lokal Cloud Computing [MeSH]
lokal eHealth
lokal Artificial Intelligence [MeSH]
lokal Male [MeSH]
lokal Chronic Disease [MeSH]
lokal Research Article
lokal Cloud
lokal Arthritis, Rheumatoid [MeSH]
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0001-8194-3243|https://frl.publisso.de/adhoc/uri/Q2hlaGFiLCBHYW1hbA==|https://frl.publisso.de/adhoc/uri/U2Nod2FydHosIENhdGFyaW5h|https://frl.publisso.de/adhoc/uri/Umlja2VuLCBFbGlzYWJldGg=|https://frl.publisso.de/adhoc/uri/VG9tY3phaywgTW9uaWth|https://frl.publisso.de/adhoc/uri/QWNhciwgSGFzYW4=|https://frl.publisso.de/adhoc/uri/R2FwcGEsIEhlbnJpa2U=|https://frl.publisso.de/adhoc/uri/VmVsYXNjbywgQ2FybG9zIEEu|https://frl.publisso.de/adhoc/uri/Um9zZW5ncmVuLCBQZXRlcg==|https://frl.publisso.de/adhoc/uri/UG92aWxpb25pcywgQXJtYW5hcw==|https://frl.publisso.de/adhoc/uri/U2NobmVpZGVyLCBNYXR0aGlhcw==|https://frl.publisso.de/adhoc/uri/VGhlc3RydXAsIEplc3Blcg==
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