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Digitalizing Healthcare- Ralph Wiegner, Siemens Healthineers for mHealth Israel
The document discusses the challenges and trends in digitalizing healthcare, emphasizing the need for CEOs to adapt to financial pressures and enhance productivity through digital tools accelerated by the COVID-19 pandemic. It highlights the importance of integrating clinical and non-clinical data for improved patient outcomes and outlines the future of stroke treatment through advanced technologies like AI and telehealth. The focus is on creating a connected health system that empowers decision-making, optimizes care delivery, and supports patient-centered rehabilitation.
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Digitalizing Healthcare- Ralph Wiegner, Siemens Healthineers for mHealth Israel
- 1. 1 Unrestricted © SiemensHealthineers, 2021 Unrestricted © Siemens Healthcare GmbH, 2021 mHealth Israel – Webinar Digitalizing healthcare March 2, 2021
- 2. 2 Unrestricted © SiemensHealthineers, 2021 COVID-19 pandemic has created new challenges for CEOs Financial pressure and economic recovery Resilient emergency preparedness Care delivery transformation C-Level customer CxO ?!?!?!?!?! Focus on productivity Small? Distressed? - Consolidate or exit CAPEX-constrained Balance central and near- patient testing Meet the surge capacity Strengthen Public Health Accelerate Virtual Health adoption Migrate from inpatient to outpatient
- 3. 3 Unrestricted © SiemensHealthineers, 2021 Acceleration of digitalization in healthcare – are healthcare decision makers well prepared for this? 4 of 10 CEOs have no digital component in their strategic plan2 1 269 survey participants, Economist study 2020 2 PWC Study 2019 https://www.pwc.com/us/en/industries/health-industries/assets/pwc-us-health-top-health-issues.pdf >80% C-level leaders say the investment into digital tools and systems significantly changed as a result of covid-191
- 4. 4 Unrestricted © SiemensHealthineers, 2021 Connect caregivers and patients for better coordination and knowledge sharing. Strengthen integrated care across the health system. How to digitalize healthcare? Integrate accurate data from frag- mented sources. Create a holistic understanding of patients and en- terprise visibility with digital twins. Continuously optimize, expand and advance digital adoption, enterprise performance and patient outcomes. Leverage analytics, benchmark insights and use digital companions to simplify workflows and to enable decision support. Build a learning health system Manage data as a strategic asset Connect care teams and patients Empower data-driven decisions
- 5. 5 Unrestricted © SiemensHealthineers, 2021 What are the right measures and technologies to ensure sustainable digital transformation? Clinical decision support Performance monitoring Operational decision support tools Data integration Patients access to data Remote caregiver support Communication tools Virtual care E-scheduling Cybersecurity Simple user experiences Organizational structures Outcomes dashboards Build a learning health system Manage data as a strategic asset Connect care teams and patients Empower data-driven decisions
- 6. 6 Unrestricted © SiemensHealthineers, 2021 The integration of clinical and non-clinical data and patient outcome sharing is seen most critical globally Source: Economist survey, Dec 2020, 269 C-level decision makers from 10 countries; Questions asked: 1. “To what extent are the following (technologies/digital tools) implemented in your hospital – Topic X”; 2. “How do you believe your hospital rates under the following measures – Topic X” Build a learning health system Manage data as a strategic asset Connect care teams and patients Empower data-driven decisions How would you rate the status of digital technology implementation/readiness of your hospital? Higher than regional average +/- around regional average Lower than regional average Clinical decision support Performance monitoring of departments Operational decision support Integration of clinical data Integration of non-clinical data Patients access to personal health data Remote digital caregiver support Digital communications Virtual care to patients E-scheduling Cybersecurity measures Free up time of caregivers Organizational governance structures Shared patient outcomes AM | RoW Europe | RoW AM, Europe | Asia Europe | RoW Europe | RoW
- 7. 7 Unrestricted © SiemensHealthineers, 2021 Imagine…
- 8. 8 Unrestricted © SiemensHealthineers, 2021 Future vision: Digital Twin – management of complex medical scenarios by patient centered data integration and modelling This feature is based on research, and is not commercially available. Due to regulatory reasons its future availability cannot be guaranteed Cognitive Load Outcome prediction of an intervention… Therapy decision Support… A B Cardiology Oncology Neurology …along patient pathway
- 9. 9 Unrestricted © SiemensHealthineers, 2021 Stroke is the second leading cause of death worldwide Source: Party, I.S.W., 2012. National clinical guideline for stroke (Vol. 20083). London: Royal College of Physicians | Image courtesy of Rost Stroke Research Group Two major types of stroke Interruption in the blood supply to a part of the brain. Impairment in brain function due to deprivation of oxygen and nutrients. Caused by blood vessel rupture Haemorrhagic (13%) Blood begins to fill the space inside the brain Caused by blockage of blood vessel Ischemic (87%)
- 10. 10 Unrestricted © SiemensHealthineers, 2021 Major challenges and trends for stroke – Facts and figures 1 Statistics from United States of America Lack of stroke specialists Expert shortage of 61,800 by 20301 Urgent demand for early detection technologies 80% of the cases are preventable Time is brain 10% lose functional independence per 1h delay Lack of post-stroke monitoring Recurrence rate of 25% in stroke survivors Disability-induced care cost $45,000 p.a. Limited patient outcomes and high stroke-related costs $240.7 billion by 20301
- 11. 11 Unrestricted © SiemensHealthineers, 2021 Decentralized setting – Micro clinic (spoke), mobile vs. center (hub) Automated (telehealth) platform AI-based real-time decision making Vision: Connected intelligence in stroke – Self-learning real-time network of intelligent machines = Decision points = Orchestrated pathway with dynamic real-time decision making (level 5 automation) through machine-to-machine communication tPA = Tissue Plasminogen Activator | This slide describes possible future ideas and concepts. It is not intended to describe specific performance and/or safety characteristics of currently planned or future products. Future realization and availability cannot be guaranteed. Rapid recovery vs. spending the rest of your life in long-term care Home Home Pre-hospital diagnosis and care Screening Late treatment: Outpatient rehab Early treatment: Home Rehab Thrombectomy Endovascular coiling Micro surgical clipping Thrombolysis Small vessel occlusion Small-neck aneurysms Wide-neck aneurysms Large vessel Occlusion Hemorrhagic 13% Ischemic 87% ≤4.5h → tPA Stroke Early alert Automated intervention suite AI-based, tele-supervised, surgery suite Integrated & digitalized clinical decision support In-hospital diagnosis and treatment Post treatment
- 12. 12 Unrestricted © SiemensHealthineers, 2021 Proactive risk evaluation and early detection Access to integrated systems for individualized stroke-care delivery Enablers Screening 12 Unrestricted © Siemens Healthineers, 2021 Secure open platforms Connectivity and Edge computing Smart monitoring systems AI algorithms Health digital twin This slide describes possibly future ideas and concepts. It is not intended to describe specific performance and/or safety characteristics of currently planned or future products. Future realization and availability cannot be guaranteed.
- 13. 13 Unrestricted © SiemensHealthineers, 2021 Real-time stroke response and diagnosis This slide describes possibly future ideas and concepts. It is not intended to describe specific performance and/or safety characteristics of currently planned or future products. Future realization and availability cannot be guaranteed. Fast emergency response by automated stroke- relevant data analysis and an orchestrated decentralized network Enablers Pre-hospital diagnosis and care 13 Real-time tracing and tracking Rapid, highly sensitive blood testing Transportable devices Virtual assistance systems and apps Automated telehealth platform Unrestricted © Siemens Healthineers, 2021
- 14. 14 Unrestricted © SiemensHealthineers, 2021 Precise stroke treatment Integrated intervention suites consisting of imaging systems and intervention robotics for precise diagnosis and treatment Enablers In-hospital diagnosis and treatment 14 Open telehealth platform IoMT Edge computing Remote real-time interventional robotics AI algorithms for automation Digital twin This slide describes possibly future ideas and concepts. It is not intended to describe specific performance and/or safety characteristics of currently planned or future products. Future realization and availability cannot be guaranteed. Unrestricted © Siemens Healthineers, 2021
- 15. 15 Unrestricted © SiemensHealthineers, 2021 Seamless integrated patient-centered rehabilitation and aftercare Rehabilitation and digital home care services are integrated into the entire stroke pathway to shorten the recovery times Enablers Post treatment 15 AI-based algorithms Autonomous robotic systems Smart implants, wearables and prosthetics Local monitoring & medical home devices Multi-physical modeling and simulation This slide describes possibly future ideas and concepts. It is not intended to describe specific performance and/or safety characteristics of currently planned or future products. Future realization and availability cannot be guaranteed. Unrestricted © Siemens Healthineers, 2021
- 16. 16 Unrestricted © SiemensHealthineers, 2021 Stroke supervision platform orches- trates the overall patient workflow Stroke supervision centers to orchestrate the entire patient-centered care pathway from stroke alert over localization, first response, management of a stroke network, to rehabilitation Enablers Integrated & digitalized clinical decision support 16 Data transfer with cybersecurity Virtual and augmented reality AI algorithms Real-time digital twin Automated (wireless) connectivity This slide describes possibly future ideas and concepts. It is not intended to describe specific performance and/or safety characteristics of currently planned or future products. Future realization and availability cannot be guaranteed. Unrestricted © Siemens Healthineers, 2021
- 17. 17 Unrestricted © SiemensHealthineers, 2021 Siemens Healthineers Insights Series https://www.siemens-healthineers.com/insights/
- 18. 18 Unrestricted © SiemensHealthineers, 2021 Thank you for your enthusiasm! Dr. Ralph Wiegner Digitalizing Healthcare ralph.wiegner@siemens-healthineers.com
Editor's Notes
- #4 They have Improved electronic communications between healthcare professionals (eg e-communication tools like apps) (57.4% mentionings), use more e-prescriptions (51.3%), More use of e-observation tools of patients on wards (50.2%), Improved electronic storage of patient records (47.5%), Digital triage being used as a first approach for identifying and prioritising patients coming to emergency rooms (46%), Improved interoperability of electronic data between secondary and primary care (46%), and last but not least have a Greater use of telemedicine or e-consultations with patients (45%)
- #5 We believe healthcare will be digital. But unstructured data and a lack of analytical capability keep providers from unlocking the full potential of their organizations. By managing data as a strategic asset, providers will gain unprecedented insight into clinical and non-clinical processes. They will be able to leverage powerful analytical tools, including AI technologies, to improve decision making. Virtual access, telemedicine, and secure knowledge exchange will strengthen bonds between patients and care teams. A cultural shift to a digital mindset, coupled with new technology, will enable development of a continuously improving learning health system. Digitalization is a key enabler for high-value care. Technologies like AI-powered decision support will pave the way for expanding precision medicine. Increased automation and care coordination will transform care delivery. Patient portals and mobile apps will improve patient experience.
- #7 Globally challenges in integrating clinicals and non-clinical data seems There is a more mixed picture with respect to cybersecurity: perceived as high across European countries - In the Americas cybersecurity is seen more critical
- #9 HES 2019: HOOD05162003002979; 386-19
- #13 Picture: Future_of_healthcare_MP4_1080p_20mbit_hood05162003047122 | Access to integrated systems for individualized stroke-care delivery for Risk assessment (ruling out stroke mimics) for automated health alerts and recommendations Automated stroke-onset detection triggering an alert To the patient as an immediate emergency notification To the stroke supervision platform with status and localization On-demand access to stroke experts or/and virtual care assistants Streamlined decision for optimized stroke service delivery Enabling technologies Connected smart monitoring systems like wearables, smart-home devices with advanced sensors, such as “dense phenotyping” based on Atrial Fibrillation with Smart Watch, Diabetes, Hypertension Dedicated AI algorithms to Targeted stroke-relevant multi-source data extraction Risk monitoring and automated stroke detection Health Digital twin of a patient with hemodynamics model predicting the risk Connectivity for data streaming and Edge computing on device level Secure open platforms for comprehensive health data handling and analysis Virtual AI Stroke bot
- #14 Picture: Future_of_healthcare_MP4_1080p_20mbit_hood05162003047122 | The fast emergency response speeds up by automated stroke-relevant data analysis and an orchestrated decentralized network for stroke coverage Integrated first response and triage of treatment options- check eligibility for thrombectomy (ischemic vs. hemorrhagic stroke) Close-to-patient diagnostics: Automated blood test, imaging and non-imaging devices for timely tPA administration1 Highly automated AI- based real-time decision for type of treatment and path Decentralized first response intervention, mobile vs. micro-clinics Telehealth assist and remote therapies options Enabling technologies Mobile IoT diagnosis solutions (mobile CT, Volumetric Impedance Phase-Shift Spectroscopy (VIPS) device, ultrasound-based portable device) Identification and localization by real-time tracing and tracking Rapid, highly sensitive blood testing Virtual assistance systems (AR glasses) and apps for first response Transportable devices integrated into mobile Stroke ambulance and micro clinic Automated telehealth platform with AI-based decision making
- #15 Picture: Future_of_healthcare_MP4_1080p_20mbit_hood05162003047122 | 2’20min Integrated intervention suites consisting of imaging systems and intervention robotics for precise diagnosis and treatments Availability is ensured in the care network with comprehensive hubs, micro-clinics and community hospitals that are connected to remote tele-suites for intervention in real-time, assisted and performed by experts to ensure high-quality stroke treatments Optimized treatment options for patients to access the most-suitable integrated interventional suite Highly autonomous angio-system collaborating with robotic units Automated guidance and navigation for robotic intervention, thrombectomy, thrombolysis or micro-surgery Hemodynamic predictions of risks associated with cerebral aneurysm ruptures Remote intervention, assisted by the global networked expert pool Enabling technologies AI algorithms for automated analysis, triage and interpretation of images Precise dynamic human computational modelling and simulation 3D/4D color imaging technology and realistic cinematic rendering Remote real-time interventional robotics with automated navigation Sensorized smart catheters with wireless communication IoMT Edge computing, E2E (End-to-end) connectivity, M2M interaction High data rate transmission, 5G standards for the stroke network coverage Open Telehealth platform for micro-clinics and community hospitals Digital twin for patient-centered clinical workflow logistics and resource planning
- #16 Picture: Future_of_healthcare_MP4_1080p_20mbit_hood05162003047122 | Rehabilitation and digital home care services are integrated into the entire stroke pathway to shorten the recovery times Remote monitoring of patients, powered by virtual assistance for support and rehabilitation Neurorehabilitation enabled by self-learning robotics Proactive health management by connected home devices, wearables, and apps Online analysis of patient status and automated reporting to remote experts Individualized health prognosis for adaptive regeneration treatments Enabling technologies Smart Implants, Wearables and Prosthetics for improving brain functionality Local monitoring devices connected with remote expert centers Medical smart-home IoT devices with adaptive assistance systems Autonomous robotic systems e.g. robotic exoskeleton with secure human-machine interaction AI-based algorithms for individualized patient treatments and rehabilitation prognosis Multi-physical modeling and simulation for stroke-related digital twins
- #17 Stroke supervision centers will orchestrate the entire patient-centered care pathway from stroke alert over localization, first response, management of a stroke network, to rehabilitation Patient tracking/navigation and digital twin based predictive planning Remote autonomous assistance and decisions, including access to global stroke experts Virtual stroke pathway for predictive decision making for overall workflow optimization Enabling technologies Real-time high-speed data transfer with cybersecurity and open cloud-based platform standardization Data handling and access with blockchain-based platforms, secure digital authentication, and tracking techniques Virtual and augmented reality AI algorithms for autonomous decision making Automated (wireless) connectivity to medical services and experts Real-time Digital twin for logistics and medical assets Seamless integration of information and workflows, smart automation from disease onset to therapy Central control with decentralized high-level automation