DIGITAL HEALTH The impact of Big Data & AI on EU healthcare systems Public conference, Tuesday 5 th December European Parliament – Room JAN 6Q1, Rue Wiertz, 60 B Bruxelles
eHealth and mHealth
Challenges in healthcare The growing demand for care needs innovative solutions that can better cure diseases than previously used diagnostic solutions and Ageing treatments . Chronic Diseases The cost of innovative products crashes with Comorbidity the presence of limited financial resources, creating a different access to care. Limited Resources You need to create value by managing resources differently, through the collaboration between the differents parts of the healthcare system, to promote better patients outcomes by introducing innovative solutions and eliminating obsolete products. To do this it is necessary to start from correct collection, transmision and analysis of data . 3
The mHealth market Germany is expected to be The number of mHealth apps Global mHealth app downloads the largest market in available to consumers now have nearly doubled in just four Europe with revenues of exceeds 258,000. Most apps years. Total number of about US$ 1 billion in 2017. are published on Apple App downloads worldwide reached Other large markets for Store or Google Play. 3 billion in 2016, with an mobile health in Europe are increase of 7% compared to France, Italy and UK. 2015 Number of mHealth apps displayed in Mobile health revenue* in Europe in Total downloads of mHealth apps app stores 2017, by country (in billion U.S. dollars) (billions) 4,0 140.000 4,5 4 120.000 3,5 3,0 100.000 3 80.000 2,5 2,0 2 60.000 1,5 40.000 1,0 1 20.000 0,5 0 0 0,0 Rest of Germany France Italy United 2013 2014 2015 2016* Europe Kingdom 4 Source: Research2guidance (2016) and Statista (2017) Note: *estimates
5G features and use cases Data rates up to 100 times faster (more than 10 Gbps) • Mobile data volumes 1.000 times greater than today’s • Network latency lowered by a factor of five • • Number of devices connected to the network (1 mln per 1 sq km) • Battery life of remote cellular devices stretched to 10 years or more Possibility of use of several bands (from 400 MHz to 100 GHz) • 5 Source: 5G empowering vertical sectors, 5G PPP
The importance of digitalization and Big Data for outcomes-based, sustainable healthcare
Big data in Healthcare Symptoms, medical exams, tests, referral patterns, prescriptions, death records, pharmacy Pharmacovigilance (medicines safety) data records,diagnostic procedures, hospitalizations PHARMACEUTICAL DATA EHR (electronic health records) DATA MOBILE APPS, Data from patients forums on Health data disaggregated TELEMEDICINE AND by location health topics SENSOR DATA GEOSPATIAL HEALTH DATA SOCIAL MEDIA, WEB DATA Genomics, transcriptomics, proteomics, Nature of service usage, insurance and other epigenomics, metagenomics, administrative hospital data metabolomics, nutriomics CLAIMS DATA OMICS DATA AMBIENT DATA FROM “SMART” CLINICAL TRIALS DATA ENVIRONMENTS Who needs it? Occupational records, WELL-BEING, SOCIO- sociodemographic profiles or Researchers ECONOMIC, environmental BEHAVIOURAL DATA Industry OTHER RECORDS Healthcare professionals Patients and the public Regulators Payers Policymakers 7
The Outcomes-Based Healthcare “The arc of history is increasingly clear: health care is shifting focus from the volume of services delivered to the value created for patients, with “value” defined as the outcomes achieved relative to the costs. But progress has been slow and halting, partly because measurement of outcomes that matter to patients, aside from survival, remains limited. And for many conditions, death is a rare outcome whose measurement fails to differentiate excellent from merely competent providers. (Standardizing Patient Outcomes Measurement n engl j med, February 11, 2016.)” = Data Digitization allows to collect, share and analyze rapidly and precisely a large amount of output and health outcomes, facilitating the transition to a system based on outcomes. 8
The role of artificial intelligence in healthcare
Artificial intelligence and robotics: the tools to a healthcare revolution NEXT DECADE CURRENT DECADE LAST DECADE Medical Solutions Medical Platforms Medical Product (Robotics, AI, Augumented (Wearables, Big Data, (Equipment, Hardware, reality) Consumables) Health Analytics) Differentiation via intelligent Solutions Differentiation is solely through Differentiation by providing services to for evidence/outcome based health. product innovation. Focused on historic key stakeholders. Focused on real time Focused on prevetive care outcome based-care and evidence based-care 10 Source: PWC, Sherlock in Health How artificial intelligence may improve quality and efficiency, whilst reducing healthcare costs in Europe , 2017
AI applications in Healthcare Keeping well Early Training detection Artificial Research Diagnosis intelligence End of life Decision care making Treatment 11 Source: PWC, Sherlock in Health How artificial intelligence may improve quality and efficiency, whilst reducing healthcare costs in Europe , 2017
AI market size in the healthcare sector Global market of AI applications in Healthcare (2014 vs. 2021) 8.000 6.662,2 According to Frost & Sullivan (2016), the 6.000 global market of AI in healthcare was Revenue ($ million) valued at $ 633.8 million in 2014 and is 4.000 expected to reach $ 6,662.2 million by 2021, at a CAGR of 40%. 2.000 633,8 0 2014 2021 Source: Frost & Sullivan, Trasforming healthcare through artificial intelligence systems, 2016 Five categories of artificial intelligence Top five artificial intelligence use cases revenue - World markets will achieve higher revenues, especially 1600 tools supporting medical image analysis Medical image analysis 1400 and virtual assistants for patients. The 1200 Virtual assistants for patients worldwide revenue of technologies for 1000 $ millions medical image analysis is expected to 800 Patient data processing reach about $ 1,600 million by 2025 600 Computational drug discovery while the global revenues of virtual 400 assistant apps could exceed $ 1,200 200 Converting paperwork into million by 2025. digital data 0 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Source: Tractica, Artificial Intelligence for Healthcare Applications, 2017 12
AI investments Artificial intelligence is certainly a profitable sector for ICT companies and is also fertile ground for startups and scaleups, which are investment targets of Venture Capital, Corporate Venture Capital and M&A. In 2016, European scaleups in the healthcare sector raised € 164 million in financial resources. AI investments in European scaleups (2016, € million) AdTech 442 FinTech 310 Business Intelligence 181 HealthTech 164 Cybersecurity 114 HRTech 73 Automotive 72 Software development 61 eCommerce 39 MediaTech 37 0 50 100 150 200 250 300 350 400 450 500 Source: Sirris, European Artificial Intelligence scaleup report, 2016 13
I-Com Index on the Level of Preparedness for eHealth in the Member States
The barriers to development of digital health The use of digital applications and solutions is becoming increasingly present in our daily lives, offering opportunities to take on several of the challenges of health systems (chronic disease and multi-morbidity, sustainability and efficiency of health systems, cross-border healthcare), but there are some issues, which hamper the development of eHealth and that need to be addressed in order to reap the benefits of a fully mature and interoperable eHealth system in Europe. Interoperability Privacy and between eHealth cybersecurity solutions Lack of available, Digital divide and adequate eSkills infrastructures 15
Methodology A synthetic index was elaborated in order to give an idea of the level of preparedness for eHealth in the Member States. The I-Com index is based on nine variables that are either directly or indirectly related to the development of digital health in Europe. The variables are listed below and refer to 3 categories: Internet use in the healthcare sector, infrastructure development and security and privacy. A. Internet use in the healthcare sector 1. Individuals using Internet seeking information about health; 2. Patients making an appointment with a practitioner via a website; 3. GPs using electronic networks to transfer prescription to pharmacist; 4. GPs exchanging medical patient data with other healthcare providers and professionals; B. Infrastructure development 5. NGA broadband coverage; 6. 4G coverage; C. Security and privacy 5. Individuals that haven’t experienced abuse of personal information and/or other privacy violations; 6. Individuals that haven’t been attacked by a virus or other computer bug resulting in loss of information or time; 7. Individuals using anti-tracking software. Each variable was weighted. It is worth noting that the variables from 1 to 4 are specific to the eHealth. For this reason, a greater weight was assigned to them – 0.5, equally split among the four variables within this category – and 0.25 each to the other two categories (infrastructure development and privacy and cybersecurity). Then, for each country, a compound average of the variables was calculated. The values obtained were normalized relative to the best performer country, so as to establish a ranking from 0 to 100. 16
Recommend
More recommend
