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How to innovate in healthcare through digital technologies and informatics

How to innovate in healthcare through digital technologies and informatics. Theodoros N. Arvanitis, RT, DPhil, CEng, MIET, MIEEE, AMIA, FSIM, FRSM Professor of e-Health Innovation Institute of Digital Healthcare, WMG, University of Warwick Birmingham Children’s Hospital NHS Foundation Trust.

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How to innovate in healthcare through digital technologies and informatics

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  1. How to innovate in healthcare through digital technologies and informatics Theodoros N. Arvanitis, RT, DPhil, CEng, MIET, MIEEE, AMIA, FSIM, FRSM Professor of e-Health Innovation Institute of Digital Healthcare, WMG, University of Warwick Birmingham Children’s Hospital NHS Foundation Trust

  2. Digital Healthcare • Digital healthcare is the application of appropriate digital technologies to the promotion of • wellbeing & prevention; • management of disease; • and delivery of health services that are effective, efficient and of high quality • Challenges • Healthcare is the slowest adopter of digital technology • Big Data is coming – West Mids population 5.6m. • Fragmented landscape: many standalone digital applications from academia, industry, NHS • Need for interoperability • Need for translation and adoption

  3. WM AHSN Digital Work Streams • On-line Healthcare and Clinical Delivery • real and tangible impact by delivering crucial on-line healthcare interventions • Digital Innovation Management • an environment within which all innovations can be efficiently researched, prototyped, invested in, evaluated, commercialised and distributed • Enabling Digital Communications • leverage the skills and abilities of its various partners, customers and consumers at scale • Enabling Technology and Informatics • local, national and international innovations • Digital investment, Commercial and Wealth Management • ability to attract new finance for digital investment, as well as create innovative partnerships

  4. Exemplars of healthcare innovation • Two local exemplars with international impact • Translating research knowledge to practice • TRANSFoRm • Working with Big Data • Multimodal Imaging for Childhood Cancer Research and Practice • Institute of Digital Healthcare

  5. The Institute of Digital Healthcare • A world-class £4M 5-year funded partnership between the NHS, WMG, WMS and other relevant organisations • Aims: to improve people’s health and wellbeing through the use of innovative digital technologies and methodologies • We do this through high quality research, education and training capabilities

  6. Our USP • WMG: Industry engagement • NHS: Reality check & ‘needs’ • WMS: Clinical need and relevance

  7. IDH – innovation and research I

  8. IDH – innovation and research II • Neuro-degenerative disease • (epilepsy, • sleep disorders) • In vivo metabolomics & • Functional Imaging • (childhood cancer, metabolic disease) Human Brain Connectome

  9. IDH – innovation and research III

  10. IDH – innovation and research IV

  11. IDH – innovation and research V

  12. translating research into clinical practice • Development of Clinical Trial Management Systems that provide, through an integrated infrastructure, a wide-ranging set of modular, interoperable and standards based tools designed to meet the needs of clinical trials • Objectives of e-trials system implementation • To define a “computable” model representationthat supports the entire life-cycle of clinical trials protocol, • To developappropriatetools that use the model representation.

  13. knowledge in healthcare • Clinical trials • Controlled populations • Well-defined questions • Distilled scientific findings • Usable in clinical practice • Decision support • EHR systems • Wide coverage • Vast quantity • May lack in detail and quality

  14. ePCRN and TRANSFoRm: US/UK perspective

  15. Informatics tower of Babel: the grand challenge • Overwhelming volume of data • Multitude of sources • Each part of the health community speaks its own scientific “dialect” (e.g. lab values, genetic profile, clinical data) • Lack of consensus on common standards and terms • Lack of coordination across, and collaboration within, the cancer research enterprise • Integration is critical to achieve promise of molecular medicine (personalised medicine) Slide courtesy of caBIG™

  16. TRANSFoRmItegrated VS • The TRANSFoRm Integrated Vocabulary Service is designed to allow end users to search and retrieve clinical vocabulary concepts and associated content • a web interface and a web service API • the service uses the LexEVS (version 5.1) technology to access a backend UMLS vocabulary database • the service uses direct Java Database Connectivity (JDBC) to access other vocabulary databases (e.g. Read Codes V2, ICPC2)

  17. RCD v2/ICPC2 UMLS Metathesaurus SNOMED CT Codes • Read Codes (RCDv2) and International Classification of Primary Care (ICPC2) corpus of terms and their associated mappings • created to cater for the initial need of the existence of specific primary care oriented terminologies. • The UK NHS Connecting for Health Terminology Centre - mappings from Read Codes version 2 to SNOMED CT. • The Read Codes v2 database in Transform VS is set up based on this mapping so that Read Codes 2 concepts can be linked to a UMLS search. Similar approach for ICPC2. • ICPC2-ICD10 Thesaurus and mappings - Transition Project @ University of Amsterdam • The TRANSFoRm team is updating the ICPC2-ICD 10 mapping and Thesaurus • ICPC3: new initiative Read Codes v2 Codes UMLS Metathesaurus ICD-10 Thesaurus/Codes ICPC2 Codes

  18. TRANSFoRm Integrated VS Server Architecture

  19. A screenshot of the vocabulary service web-based interface

  20. Finding prevalent cases for trials

  21. acknowledgments: TRANSFoRmConsortium

  22. BIG Data: multi-modal imaging Quantitative imaging Diffusion imaging Metabolite profiles Investigating children’s cancer using functional imaging Tractography Metabolite maps Perfusion

  23. Powerful Computation

  24. large data sets HR-MAS Cho Lip+Lac mI NAA Cr w113C 1H-13C HSQC w21H

  25. agent-based classifiers

  26. acknowledgments: cancer research • Investigators • Andrew Peet – UB PI, oncology, MRS • Theo Arvanitis – UW bio-informatics • Richard Grundy – UN oncology, biology • Martin Leach – ICR MR Physics, perfusion • Chris Clark – ICH MR Physics, diffusion • Franklyn Howe – StGUL MR Physics, MRS Collaborators • Professor Dr Dorothee Auer University of Nottingham • Dr Thomas Barrick St George's Hospital Medical School • Mr David Collins Royal Marsden Hospital • Dr Daniel Ford University Hospital Birmingham • Dr Darren Hargrave Royal Marsden Hospital • Mr Donald Macarthur Nottingham University Hospitals NHS Trust • Dr Lesley MacPherson Birmingham Children’s Hospital NHS Trust • Dr Paul Morgan University of Nottingham • Dr KalNatarajan University Hospital Birmingham • Dr Oystein Olsen Great Ormond Street Hospital • Dr Geoffrey S Payne The Institute of Cancer Research • Professor Andy Pearson Royal Marsden Hospital • Dr SuchetaVaidya St George's Hospital Medical School • Dr Tim Jaspan, University Hospital, Nottingham • Dr Dawn, Saunders, Great Ormond Street Hospital Research Group: Nigel Davies, Martin Wilson, KalNatarajan, Yu Sun, EleniOrphanidou, Lisa Harris, Greg Reynolds, Sim Gill, Alex Gibb, M. Saleh, Suchada Tantisatirapong, Ben Babourina-Brooks, Jan Novak

  27. Digital Healthcare research and innovation

  28. realising our imagination: facing challenges "Leave the beaten track occasionally and dive into the woods. Every time you do so, you will be certain to find something that you have never seen before. Follow it up, explore all around it, and before you know it, you will have something worth thinking about to occupy your mind. All really big discoveries are the result of thought." Alexander Graham Bell: "electrical speech machine" of 1876

  29. Thank you t.arvanitis@warwick.ac.uk

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