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Hall Plan

Hallenplan Biomedica 2017

Day 1 // Opening Session, Blauwe Zaal

Keynote 1

Prof. Dr. Philippe Coucke

11:15 - Evidence based to intelligence based medicine

Prof. Dr. Philippe Coucke

CHU of Liège, BE

Head of Radiation Therapy

Curriculum vitae

Dr. Coucke Philippe is born in Ghent in 1959.

He accomplished his medical degree at the State University of Ghent Belgium in 1984. He has been trained in radiation oncology at Ghent University Hospital  and University Hospital of of Besançon in France till 1987. He was board certified in radiation oncology in 1988 and and ledt France in 1989.

From 1989 on, he became senior member of the staff at the University Hospital in Lausanne (CHUV), Switzerland. In 1996, he obtained the Academical degree of “Privat Docent & Maître d’Enseigment et de Recherche” at the same university. He was also trained in managerial skills at CHUV and made a thesis on “organisational learning and resistance to change”.

He left Switzerland in 2005 and became head of the Department of Radiotherapy at Hopital Maisonneuve Rosemont, Montreal Canada. He was appointed as clinical professor at the University of Montreal.

In 2006, he became head of the Department of Radiotherapy at the University Hospital in Liège and Professor of Radiation Therapy at the same university.

His interest is focused nowadays on breast cancer, radiation biology, metabolic imaging in treatment planning and sensing of treatment, dynamic tumor tracking, and quality management. He has been granted 5 times by MWQ (Mouvement Wallon pour la Qualité) for the application of the EFQM excellence model (European Foundation for Quality Management) in his department. He has been appointed as Chief Quality Officer of the new integrated cancer center (under construction and to be opened in 2018 in Liège).

More recently, he focuses his attention “connected health”, evaluation of health literacy of patients, patient empowerment, and the potential of artificial intelligence.

He is author and co-author of more than 240 publications, most of these publications in peer reviewed journals.

Abstract

More than half of published research cannot be replicated. Even considering evidence based medicine, it is staggering that reanalysis of raw patient data results in 35% divergence in the type or numbers of patients that should be treated and or conclusions compared to the published trials. Moreover, researchers do insist on the “internal validity” of the trial but do obviate “external validity”. It is at astonishing that in real life, the conclusions of a randomized controlled trial (RCT) - obtained in a well-defined and selected patient population - are simply extrapolated on a larger cohort of patients most of them not even eligible for that particular study.

This population-wide extrapolation of results from RCT is one of the reasons for the global inefficiency level (cost/efficiency) in health care, reaching 42% (OCDE report 2013). A recent evaluation of pharmacy prescription in the US, especially done on the ten “blockbusters”, results at best in a therapeutic effect in one upon four patients, and at worst in one upon 25 patients. For other treatment interventions, this ratio can even be one upon two hundred! This health policy is not affordable at the long run.

At most, 20% of what is done nowadays is supported by solid research and very often (in 10 to 50% of cases) physicians do not agree on treatment proposal. Why is there such a divergence? Most of the physician’s work is done in a data-free environment (paucity of data and data of poor quality in unstructured and incomplete medical files), devoid of data-driven feedback (poor information on the effect – whether positive or negative – of the given treatment and virtually no information at all on patient’s experience). Most of the physicians practice “the art” of medicine, which is more linked to training, culture and personal experience than hard data. Therefore, it is high time to claim together with Eric Topol leading the Scripps Research institute in California: “Medicine for the common good is not good enough”.

The three buzzwords in modern healthcare are: Big Data (BD), Artificial Intelligence (AI) and platform solutions.

One of the driving forces behind the paradigm shift is the internet of thing (IoT). Connected objects do provide the opportunity of a continuous flux of information (24/7), leading to knowledge and increasing intelligence. Patients become a connected “object” within this IoT. This is not the only source of information. Medical sensor data, data in hospital information systems, data from medical imaging (inclusive ultrasound), medical publications, clinical studies, registries, human genome data (and other omics), together with data from the “exposome” (the environmental factors influencing health) yield zettabytes of digital information.

Facing such a deluge of data, there is no other option than AI. According to Barack Obama, synthetic intelligence will totally transform our future. AI will profoundly change every single aspect of health care in research and from diagnosis to decision making.

To exploit the potential of BD and AI, we need a change in “ecosystem”. Too often, the IT solutions in health care are heavily fragmented and poorly integrated. There is an urgent need for platform solutions, with integration of several techniques for data acquisition, storage and exchange of information. Platforms address common root problems by common solutions.

Transition from “old”, mostly curative medicine, to “new” predictive preventive, personalized and participative medicine (4P medicine) is accelerating. Big data, AI and platforms are the technical requirements for this metamorphosis, but the real driving power behind the scenes to enable and install this paradigm change is the crowd, well aware that a new form of health care is well within reach!

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