Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

20191203 DOE Data Driven Healthcare- Expert Event

937 views

Published on

DayOne Experts - Data-driven healthcare – are we ready?
Data is transforming healthcare. Health data from multiple sources such as electronic health records, genomic testing, imaging and digital tools, combined with advanced analytics can be used to deliver more personalised care, improve outcomes, empower patients and make healthcare more sustainable and efficient. But is the industry ready for these new approaches? What is needed on the policy level and in the regulatory field to enable a new era of data driven health solutions? How will their business models look like?

This is what we discussed at this DayOne Expert Event, which was proudly presented in close collaboration with the Embassy of the Netherlands, fostering the exchange between two world leading healthcare innovation ecosystems.

Published in: Healthcare
  • Diabetes Cure? You'll Be Shocked What It Is! Gov't Threatens to Shut Down Site. ★★★ https://tinyurl.com/yx3etvck
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Be the first to like this

20191203 DOE Data Driven Healthcare- Expert Event

  1. 1. DayOne Experts December 3rd, 2019, Basel Data Driven Healthcare – are we ready?
  2. 2. #DayOneBasel
  3. 3. Thomas Brenzikofer, Co-Founder DayOne BaselArea.swiss
  4. 4. An initiative managed by BaselArea.swiss in close collaboration with the Canton of Basel-Stadt.
  5. 5. Core Team Alain Bindels Roche Andre Moeri Impact Hub Basel Andreas Wicki Kantonsspital Baselland Bejal Joshi T4 Communications Bhupinder Bhullar Consultant Bram Stieltjes University Hospital Basel Christian Bosshard CSEM Christian Schneider University Basel Douglas Haggstrom BaselArea.swiss Enkelejda Miho FHNW Erik Schkommodau FHNW Fabian Streiff BaselArea.swiss Frank Kumli BaselArea.swiss Laurenz Baltzer Karger Publishing Melissa Penny Swiss TPH Michael Rebhan Novartis Nicole Probst- Hensch Swiss TPH Peter Groenen Idorsia Thomas Brenzikofer BaselArea.Swiss Torsten Schwede Swiss Personalised Health Network Viktor Bullain Global coach Andrea Huber- Brösamle ETH Zurich Dr. Niko Beerenwinkel ETH Zürich, D-BSSE Rocco Falchetto President Swiss Society for Porphyria 5
  6. 6. MANAGED BY SUPPORTING PARTNERS KNOWLEDGE PARTNERS IN CLOSE COLLABORATION WITH DayOne Partners Public and Industry
  7. 7. 7 A growing community of 1500+ healthcare innovators…
  8. 8. 8 working together to shape the future of health
  9. 9. To create a world-leading hub for healthcare innovation, built on the strength of the Basel region respected for its impact and collaboration across disciplines and industries with a focus on precision medicine – the convergence of diagnostics, treatment and digital health. Our Mission and Vision 9
  10. 10. 10
  11. 11. shaping the future of health
  12. 12. - Data = Private Good - Controlled by market incumbents - Privacy? We are not evil! - Data = Public Good - Controlled by the government - Privacy? We are not evil! Health Data Ecosystem
  13. 13. - Data = Private Good - Controlled by market incumbents - Privacy? We are not evil! - Data = Public Good - Controlled by the government - Privacy? We are not evil! Europe ?
  14. 14. - Data = Private Good - Controlled by market incumbents - Privacy? We are not evil! - Data = Public Good - Controlled by the government - Privacy? We are not evil! Europe - Data = Citizen “owned” - Regulation - Privacy first
  15. 15. 26 Co-Host Maurits-Jan Prinz Consulaat (Hon.) van het Koninkrijk der Nederlanden te Bazel
  16. 16. Agenda 18.15 Welcome and Introduction 18:30 Presentations by: Ron Roozendaal, Director of Information Policy & CIO, Dutch Ministry of Health Peter Indra, Head Healthcare, Department of Health, Canton of Basel-Stadt Niels Chavannes, Founder of the National eHealth Living Lab, Leiden University Medical Centre Katrin Crameri, Director Personalized Health Informatics at SIB Ulrich Muehlner, Co-Founder and CEO Docdok 19:20 Panel discussion with speakers joined by Maria Hahn, Co-Founder and CEO of Nutrix Nico van Meeteren, Executive Director Health~Holland 20:00 Wrap-up and networking with refreshments
  17. 17. Panel discussion Ron Roozendaal, Director of Information Policy & CIO, Dutch Ministry of Health Peter Indra, Head Healthcare, Department of Health, Canton of Basel-Stadt Niels Chavannes, Founder of the National eHealth Living Lab, Leiden University Medical Centre Katrin Crameri, Director Personalized Health Informatics at SIB Ulrich Muehlner, Co-Founder and CEO Docdok Maria Hahn, Co-Founder and CEO of Nutrix Nico van Meeteren, Executive Director Health-Holland
  18. 18. 29 Co-Host Kees Smit Sibinga Deputy Head of Mission, Embassy of the Kingdom of the Netherlands
  19. 19. DayOne Agenda 2020 February 18th: Measuring the unmeasurable – bringing mental health to a next level April 28th: Value based healthcare – the new industry standard? June 17th: MDR, GPR and Co. – how to navigate the regulatory landscape August 26th: Smart Prevention November 6th to 8th: DayOne Health Hack November 10th: DayOne Conference December 8th: Public Health
  20. 20. DayOne Experts December 3rd, 2019, Basel Data Driven Healthcare – are we ready?
  21. 21. Digital health in The Netherlands Ron Roozendaal Director of Information Policy
  22. 22. System of managed competition Insured individuals are free in their choice of insurer; possibility to change every year Providers compete for contracts with insurers on price & quality of care Insurers compete for insured on premium, quality, service level Insured individual Provider Insurer Healthcare purchase market Government is responsible for organising accessibility, defining basic package and supervising market and quality Public private partnership
  23. 23. Dutch ambitions  80% of the chronically ill have direct electronic access to some of their medical data, such as medication data, vital functions and test results, and is able to use this data in mobile apps or internet applications.  Of the chronically ill (diabetes, COPD) and vulnerable elderly, 75% who are willing and able can take their own measurements, mostly in combination with remote monitoring by a professional.  Everyone in need of care at home will be able to communicate by video with their care professional remotely 24 hours a day. Also, smart home technology will be used to support home care.  The next 4 years: > 50% of healthcare value based
  24. 24. Electronic Paper Electronic + Paper Digital EHRs Effects (eHealth Monitor) GPs 98% Specialists 60% Use of EHR by specialists Medication interaction warning - Higher quality of care 72% - Increased safety 67% - Less administration 33% GPs 99% Specialists 90% Nurses (cure) 75% Nurses (care) 31% eHealth in NL - digitization of patient records
  25. 25. The right care at the right place Therefore the right information at the right place at the right moment Empowered citizens • Everyone CEO of their own health • Shared decision making • Make informed healthy decisions in daily life  MedMij: National Trust Framework for Personal Health Environments  Outcome data for value based shared decisions for 50% of disease burden Empowered healthcare professionals • Mandatory electronic exchange • Unity of language • Unity of technology • Reducing administrative burden: let doctors doctor
  26. 26. MedMij allows you to collect, share and manage your health data in your own personal health environment • Copy of own data by law • Nationwide FHIR implementation • Based on Health and Care Information Models (semantical and technical standards) • Certified PHE’s
  27. 27. 2017 2018 2019 2020 2021 2022 2023 (and further) Care Provider Individual GGZ (VIPP GGZ) (mental healthcare) Care (InZicht) Primary Care (OPEN) Structural financing PHE use Stimulus financing PHE suppliers Hospitals (VIPP) Maternity care (Babyconnect) Investing in patient empowerment 8 Hospitals (VIPP 5) Stimulus financing PHE use 15 million 90 million 75 million 50 million 105 million 75 million 25 suppliers €160.000 each €7,50 per user
  28. 28. Semantic unification Standards Fertile Soil Registries Sustainable Health Information ‘The right information at the right place at the right time’ Authentication Monitoring Basic Infrastructure Patient access Monitoring Safe Communication Indicators Funding Enforcement Seed Capital Health deals Health Innovation School eHealth week Public Campaigns
  29. 29. Whole system in the room: National Health Information Council
  30. 30. Health and Care Information Models  Functional definition of small clinical information objects  As small as possible, as large as needed – keep it simple!  Linked to terminologies: SNOMED, LOINC  Independent of use case or technology  Based upon Detailed Clinical Models  Harmonized with eHN Guidelines  Technically specified in CDA and in FHIR
  31. 31. Example HCIM: Heart Rate Specification of Concept Specification of Data Elements Specification on how Data Elements are recorded
  32. 32. Electronic exchange between care providers gets mandatory • Usecase by usecase (Medication, Images, Discharge to and from nursing homes, Patient summary exchange) • Based on mandatory use of semantic and technical standards • Incorporating same HCIM’s as in MedMij • Certification of ICT systems used 1 3
  33. 33. Interoperability is a world wide effort
  34. 34. Data in Healthcare: it’s all about trust  Maximum control over data for citizens  No competition on the possession of data. Compete on the analysis  People who opt not to use digital tools still catered to in healthcare  Healthcare professionals become coach, though still responsible for the care provided  Data solidarity: making data available for the greater good  Interoperability  Federated learning, no central data where possible
  35. 35. • Think Big • Act Small • Start Now
  36. 36. DayOne Experts December 3rd, 2019, Basel Data Driven Healthcare – are we ready?
  37. 37. Kanton Basel-Stadt Data-driven healthcare – are we ready? Peter Indra, MD, PhD, MPH Director of Healthcare Health Department of the Canton of Basel
  38. 38. Data is transforming healthcare. Health data from multiple sources such as electronic health records, genomic testing, imaging and digital tools, combined with advanced analytics can be used to deliver more personalised care, improve outcomes, empower patients and make healthcare more sustainable and efficient. But is the industry ready for these new approaches? What is needed on the policy level and in the regulatory field to enable a new era of data driven health solutions? How will their business models look like? • Is the healthcare system ready? The insured persons, the patients, the healthcare professionals? • Are the hospitals ready? • Is our community ready? • Are the politicians ready? Laws? Data protection? • …and: are we ready? (willingness) DayOne Experts - Data-driven healthcare – are we ready? | 2
  39. 39. What is Digitalization for a healthcare professional? | 3
  40. 40. | 4 Switzerland 2019
  41. 41. «Status quo of the use of information technology in Swiss medical practices.“ • 11.7 percent of physicians in private practice use an electronic medical history application • Although 84.3 percent have a practice computer, but without full functionality for electronic medical history. The computer is therefore primarily for administrative purposes. • 3.5 percent of GPs are still completely paper-based Source: MEDINSIDE.CH 2017 CH 2007 | 5
  42. 42. «Status quo of the use of information technology in Swiss medical practices.“ • 35.2 (11.7 in 2007) percent of GPs use an electronic medical history application • 59.1 percent have a computer in the office, which they only use for administrative purposes • 4.5 (3.5 in 2007) percent do not even own a practice computer - that's about one out of 22. Source: MEDINSIDE.CH 2017 CH 2015 | 6
  43. 43. Status Quo: Few Coordination in the Treatment-Chain
  44. 44. Better Lead? | 8 H + and doctors say NO! «The health coaches in In our system are the family doctors, the specialists in private practice and the hospital physicians, who deal with the daily patients problems» Health experts are largely agree: better coordination which leads to medical treatments to higher quality and ideally also at lower costs. NZZ December 2019
  45. 45. | 9
  46. 46. | 10 Primary Care 4.0 ?
  47. 47. | 11 New digital «Pampa»-Doctor
  48. 48. | 12
  49. 49. | 13
  50. 50. | 14
  51. 51. | 15
  52. 52. | 16
  53. 53. Medical data in Switzerland belong to the Patient… | 17
  54. 54. But there is a world beyond… | 18
  55. 55. | 19
  56. 56. | 20
  57. 57. | 21
  58. 58. | 22
  59. 59. | 23
  60. 60. | 24
  61. 61. DayOne Experts December 3rd, 2019, Basel Data Driven Healthcare – are we ready?
  62. 62. A project of Enable use and exchange of interoperable health data for research Swiss Personalized Health Network (SPHN) initiative A Swiss Government Initiative Mandate holder Organisational and Technical Implementation SPHN Management Office (SAMS) and Personalized Health Informatics Group (SIB) State Secreteriat for Education, Research and Innovation (SERI) Federal Office of Public Health (FOPH) 1
  63. 63. A project of Aims of the Swiss Personalized Health Network • Getting data out of silos: Working towards a FAIR use of health data for research; “democratic” access to data: breaking the monopoly • Connecting and harmonizing systems: Establishing a national infrastructure network, consisting of various modules and components • Reaching interoperability of data: structuring, standardisation, harmonisation; across systems, across projects, over time, internationally aligned 2
  64. 64. A project of The SPHN ecosystem 3
  65. 65. A project of Data-types for research Routine data from clinical care Basic (diagnosis, medication, demographics, lab, etc.) and specific routine data (imaging, etc.) from hospital data warehouses Molecular and *omics data Genomics, transcriptomics, proteomics, metabolomics, etc. from hospitals (clinical grade) and research facilities (research grade) 4 Clinical research data Cohorts, registries, clinical trial data, observational study data, etc.  largely unstructured  highly structured  highly structured
  66. 66. A project of University Hospitals: logical architecture 5 Service and user interaction Layer Data Processing and Storage Layer Clinical Routine Data IntensiveCare DataLab Data *omicsData Media Data Biosample Data Oncology Data Pathology Report Data Neonat/KISPI Data Study/Registry Data Data Lake Structured data semi-structured data unstructured data Patient data with all types of consent status, typically identifying data Data Integration Technical quality assurance, referencing, etc. Data Source Systems Data Processing & Modelling Key/Cohort Mgmt, Pseudonymisation, Normalisation, Semantic Interoperability User groups Hospital internal Medical Informatics Other external clientsSPHN Request Workflow Engine Text search tool, data exploration, frontends, links to analysis environment, etc. Adapted according to C. Kruschel, USZ, 2019
  67. 67. A project of University Hospitals: logical architecture 6 Service and user interaction Layer Data Processing and Storage Layer Clinical Routine Data IntensiveCare DataLab Data *omicsData Media Data Biosample Data Oncology Data Pathology Report Data Neonat/KISPI Data Study/Registry Data Data Lake Structured data semi-structured data unstructured data Patient data with all types of consent status, typically identifying data Data Integration Technical quality assurance, referencing, etc. Data Source Systems Data Processing & Modelling Key/Cohort Mgmt, Pseudonymisation, Normalisation, Semantic Interoperability User groups Hospital internal Medical Informatics Other external clientsSPHN Request Workflow Engine Text search tool, data exploration, frontends, links to analysis environment, etc. In Standardisation accordingtoSPHN requirements, structuring(NLP) Adapted according to C. Kruschel, USZ, 2019
  68. 68. A project of University Hospitals: logical architecture 7 Service and user interaction Layer Data Processing and Storage Layer Clinical Routine Data IntensiveCare DataLab Data *omicsData Media Data Biosample Data Oncology Data Pathology Report Data Neonat/KISPI Data Study/Registry Data Data Lake Structured data semi-structured data unstructured data Patient data with all types of consent status, typically identifying data Data Integration Technical quality assurance, referencing, etc. Data Source Systems Data Processing & Modelling Key/Cohort Mgmt, Pseudonymisation, Normalisation, Semantic Interoperability User groups Hospital internal Medical Informatics Other external clientsSPHN Request Workflow Engine Text search tool, data exploration, frontends, links to analysis environment, etc. In Datacollection/ datacaptureina structuredand standardizedway Adapted according to C. Kruschel, USZ, 2019
  69. 69. A project of Impact of SPHN on healthcare system SPHN “rattled” the healthcare system with its requirements concerning data standards and interoperability, and has a major impact on how data and data collection is handled in the hospitals (already now and in the future) • Process-innovation: instead of getting structured data out of unstructured reports, aim for structured data capture and automatic creation of the report • Smart incentives: offer HCPs a helpful tool that introduces structuring and standards though the backdoor • Harmonisation: standardization of data regarding diagnoses, treatments and outcomes at the front-end 8
  70. 70. A project of Conclusions Healthcare and research must go hand in hand in the digital learning healthcare system of tomorrow Higher quality of routine data at the beginning saves a lot of money on the back-end and introduces the possibility for large real-world observational studies 9
  71. 71. A project of www.sib.swiss/phi www.sphn.ch dcc@sib.swiss @CrameriKatrin @SPHN_ch @PHRT_CH

×