From Personalised Predictions to Targeted Advice: Improving Self-Management in Rheumatoid Arthritis

Ali Fahmi, Hamit Soyel, William Marsh, Paul Curzon, Amy MacBrayne, Frances Humby

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, that can lead to joint damage but also affects quality of life (QoL) including aspects such as self-esteem, fatigue, and mood. Current medical management focuses on the fluctuating disease activity to prevent progressive disability, but practical constraints mean periodic clinic appointments give little attention to the patient’s experience of managing the wider consequences of chronic illness. The main aim of this study is to explore how to use patient-derived data both for clinical decision-making and for personalisation, with the first steps towards a platform for tailoring self-management advice to patients’ lifestyle changes. As a result, we proposed a Bayesian network model for personalisation and have obtained promising outcomes.
Original languageEnglish
Title of host publicationIntegrated Citizen Centered Digital Health and Social Care
Subtitle of host publicationCitizens as Data Producers and Service co-Creators - Proceedings of the EFMI 2020 Special Topic Conference
EditorsAlpo Varri, Jaime Delgado, Parisis Gallos, Maria Hagglund, Kristiina Hayrinen, Ulla-Mari Kinnunen, Louise B. Pape-Haugaard, Laura-Maria Peltonen, Kaija Saranto, Philip Scott
Number of pages5
ISBN (Electronic)9781643681443
Publication statusPublished - 23 Nov 2020

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


  • Bayesian networks
  • Personalised prediction
  • Rheumatoid arthritis
  • mHealth


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