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The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians
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 o...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157758/ https://www.ncbi.nlm.nih.gov/pubmed/34044850 http://dx.doi.org/10.1186/s13075-021-02526-7 |
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author | Richter, Jutta G. Chehab, Gamal Schwartz, Catarina Ricken, Elisabeth Tomczak, Monika Acar, Hasan Gappa, Henrike Velasco, Carlos A. Rosengren, Peter Povilionis, Armanas Schneider, Matthias Thestrup, Jesper |
author_facet | Richter, Jutta G. Chehab, Gamal Schwartz, Catarina Ricken, Elisabeth Tomczak, Monika Acar, Hasan Gappa, Henrike Velasco, Carlos A. Rosengren, Peter Povilionis, Armanas Schneider, Matthias Thestrup, Jesper |
author_sort | Richter, Jutta G. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8157758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81577582021-06-01 The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians Richter, Jutta G. Chehab, Gamal Schwartz, Catarina Ricken, Elisabeth Tomczak, Monika Acar, Hasan Gappa, Henrike Velasco, Carlos A. Rosengren, Peter Povilionis, Armanas Schneider, Matthias Thestrup, Jesper Arthritis Res Ther Research Article 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. BioMed Central 2021-05-27 2021 /pmc/articles/PMC8157758/ /pubmed/34044850 http://dx.doi.org/10.1186/s13075-021-02526-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Richter, Jutta G. Chehab, Gamal Schwartz, Catarina Ricken, Elisabeth Tomczak, Monika Acar, Hasan Gappa, Henrike Velasco, Carlos A. Rosengren, Peter Povilionis, Armanas Schneider, Matthias Thestrup, Jesper The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
title | The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
title_full | The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
title_fullStr | The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
title_full_unstemmed | The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
title_short | The PICASO cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
title_sort | picaso cloud platform for improved holistic care in rheumatoid arthritis treatment—experiences of patients and clinicians |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157758/ https://www.ncbi.nlm.nih.gov/pubmed/34044850 http://dx.doi.org/10.1186/s13075-021-02526-7 |
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