Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shift from reactive to predictive, preventive and personalised care

Matthew Barrett, Josiane Boyne, Julia Brandts, Hans-Peter Brunner-La Rocca*, Lieven De Maesschalck, Kurt De Wit, Lana Dixon, Casper Eurlings, Donna Fitzsimons, Olga Golubnitschaja, Arjan Hageman, Frank Heemskerk, Andre Hintzen, Thomas M. Helms, Loreena Hill, Thom Hoedemakers, Nikolaus Marx, Kenneth McDonald, Marc Mertens, Dirk Mueller-WielandAlexander Palant, Jens Piesk, Andrew Pomazanskyi, Jan Ramaekers, Peter Ruff, Katharina Schuett, Yash Shekhawat, Chantal F. Ski, David R. Thompson, Andrew Tsirkin, Kay van der Mierden, Chris Watson, Bettina Zippel-Schultz

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

31 Citations (Web of Science)

Abstract

Heart failure (HF) is one of the most complex chronic disorders with high prevalence, mainly due to the ageing population and better treatment of underlying diseases. Prevalence will continue to rise and is estimated to reach 3% of the population in Western countries by 2025. It is the most important cause of hospitalisation in subjects aged 65 years or more, resulting in high costs and major social impact. The current "one-size-fits-all" approach in the treatment of HF does not result in best outcome for all patients. These facts are an imminent threat to good quality management of patients with HF. An unorthodox approach from a new vision on care is required. We propose a novel predictive, preventive and personalised medicine approach where patients are truly leading their management, supported by an easily accessible online application that takes advantage of artificial intelligence. This strategy paper describes the needs in HF care, the needed paradigm shift and the elements that are required to achieve this shift. Through the inspiring collaboration of clinical and high-tech partners from North-West Europe combining state of the art HF care, artificial intelligence, serious gaming and patient coaching, a virtual doctor is being created. The results are expected to advance and personalise self-care, where standard care tasks are performed by the patients themselves, in principle without involvement of healthcare professionals, the latter being able to focus on complex conditions. This new vision on care will significantly reduce costs per patient while improving outcomes to enable long-term sustainability of top-level HF care.

Original languageEnglish
Pages (from-to)445-464
Number of pages20
JournalThe EPMA Journal
Volume10
Issue number4
Early online date22 Nov 2019
DOIs
Publication statusPublished - Dec 2019

Keywords

  • Heart failure
  • Artificial Intelligence
  • Predictive preventive personalised participatory medicine
  • Individualised patient profile
  • Patient engagement
  • Information and communications technology
  • Healthcare economy
  • Patient stratification
  • Diabetes
  • Comorbidities
  • Healthcare digitalisation
  • Therapy monitoring
  • Professional interactome
  • Multi-level diagnostics
  • Disease modelling
  • Integrated care
  • Medical ethics
  • Societal impact
  • 2016 ESC GUIDELINES
  • HEALTH-CARE
  • EJECTION FRACTION
  • DECISION-SUPPORT
  • MANAGEMENT
  • TRENDS
  • HOSPITALIZATION
  • OUTCOMES
  • BURDEN
  • TIME
  • CLASSIFICATION

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