TY - JOUR
T1 - Artificial intelligence supported patient self-care in chronic heart failure
T2 - a paradigm shift from reactive to predictive, preventive and personalised care
AU - Barrett, Matthew
AU - Boyne, Josiane
AU - Brandts, Julia
AU - Brunner-La Rocca, Hans-Peter
AU - De Maesschalck, Lieven
AU - De Wit, Kurt
AU - Dixon, Lana
AU - Eurlings, Casper
AU - Fitzsimons, Donna
AU - Golubnitschaja, Olga
AU - Hageman, Arjan
AU - Heemskerk, Frank
AU - Hintzen, Andre
AU - Helms, Thomas M.
AU - Hill, Loreena
AU - Hoedemakers, Thom
AU - Marx, Nikolaus
AU - McDonald, Kenneth
AU - Mertens, Marc
AU - Mueller-Wieland, Dirk
AU - Palant, Alexander
AU - Piesk, Jens
AU - Pomazanskyi, Andrew
AU - Ramaekers, Jan
AU - Ruff, Peter
AU - Schuett, Katharina
AU - Shekhawat, Yash
AU - Ski, Chantal F.
AU - Thompson, David R.
AU - Tsirkin, Andrew
AU - van der Mierden, Kay
AU - Watson, Chris
AU - Zippel-Schultz, Bettina
PY - 2019/12
Y1 - 2019/12
N2 - 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.
AB - 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.
KW - Heart failure
KW - Artificial Intelligence
KW - Predictive preventive personalised participatory medicine
KW - Individualised patient profile
KW - Patient engagement
KW - Information and communications technology
KW - Healthcare economy
KW - Patient stratification
KW - Diabetes
KW - Comorbidities
KW - Healthcare digitalisation
KW - Therapy monitoring
KW - Professional interactome
KW - Multi-level diagnostics
KW - Disease modelling
KW - Integrated care
KW - Medical ethics
KW - Societal impact
KW - 2016 ESC GUIDELINES
KW - HEALTH-CARE
KW - EJECTION FRACTION
KW - DECISION-SUPPORT
KW - MANAGEMENT
KW - TRENDS
KW - HOSPITALIZATION
KW - OUTCOMES
KW - BURDEN
KW - TIME
KW - CLASSIFICATION
U2 - 10.1007/s13167-019-00188-9
DO - 10.1007/s13167-019-00188-9
M3 - (Systematic) Review article
C2 - 31832118
SN - 1878-5077
VL - 10
SP - 445
EP - 464
JO - The EPMA Journal
JF - The EPMA Journal
IS - 4
ER -