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Person-generated health data: How can it help us to feel better?

  1. Person-generated health data: How can it help us to feel better? Presentation to IEEE International Conference on Orange Technologies (ICOT 2016) Melbourne, Australia 20 December 2016 Associate Professor Kathleen Gray Health and Biomedical Informatics Centre, University of Melbourne
  2. Outline • The discipline of Health and Biomedical Informatics • The phenomenon of person-generated health data • Research at the University of Melbourne • Better health for one and all
  3. Health and Biomedical Informatics Health and Biomedical informatics is the interdisciplinary field that advances the effective use of data, information and knowledge in scientific inquiry, problem solving, behaviour change, decision making and service design so as to improve human health. Across the spectrum from molecular medicine to population health, whether the work is labelled ehealth, mhealth, digital health, medtech, etc., health and biomedical informatics provides the scientific and scholarly foundation for: managing raw health data, organising it into meaningful health information, and systematising it as health knowledge. Hammond, W. E. 2012.
  4. History of health and biomedical informatics 1879: Index Medicus 1928: American Association of Medical Record Libarians 1949: Deutsche Gesellschaft fur Medizinische Dokumentation, Informatik und Statistik 1950s: Computers in dental projects 1960s: Hospital management systems 1970s: Expert systems for diagnosis 1980s: Clinical information systems /EHR, RIS / Unified Medical Language System 1990s: Clinical workstations / Visible Human Project / Internet health information 2000s: Bioinformatics / Human Genome Project / ontologies / modeling and simulation 2010s: Health social media / health analytics / omics medicine / healthcare IoT John Shaw Billings Gustav Wagner Dave deBronkart Stephen & Sally Damiani & family
  5. Person-generated health data
  6. Health self-tracking aids
  7. Direct-to-consumer lab tests
  8. Health online social networks http:// http://
  9. HaBIC 2011 : The University of Melbourne established a Health and Biomedical Informatics Research Unit and defined its research agenda in three main areas: • Precision Medicine • Participatory Health (Social Media and Self-Quantification) • Translational Research Informatics. 2014: The Health and Biomedical Informatics Centre (HaBIC) was officially launched as a University level Centre with research, teaching and engagement activities: • Research collaborations across the Faculty of Medicine, Dentistry and Health Sciences, the School of Engineering, and the Department of Computing and Information Systems • A range of postgraduate education and training, from short courses and a Graduate Certificate through to Masters and PhD programs • Engagement with hospital-based clinical groups, primary and community care providers, public health agencies, the ehealth industry and peak professional bodies
  10. HaBIC research: wearables for healthy ageing • The number of products that are commercially available to consumers in this cohort is relatively low; many are directed at “loved ones”. • Products are unevenly matched with the common disease profiles and health management requirements of independent living seniors. REF: Prabhu D, Gray K, Borda A, Cyarto E. Independent living on WHIMS. Information Technology in Aged Care (ITAC) Conference, Melbourne, November 2016. ons/1D%20Deepa%20Prabhu.pdf
  11. HaBIC research: DTC personal genomic tests • Biosocial behavior: Social relationships and group identities can form – over the Internet, with strangers - based on beliefs about common genetic ancestry or common genetic susceptibility to disease. • Autobiology: Youtube videos show a new genre of biological wayfarer stories, with dramatic elements such as scientific exploration, historical discovery, taking chances and confronting risks. • Citizen science: It feels good to donate personal data to biomedical research and it is empowering to direct research in which your data is used, toward your personal concerns. REF: Gray K. Like, comment, share: Should you share your genetic data online?. Australasian Science. 2016 Jul;37(6):24.
  12. HaBIC research: health self-quantification • A health SQ plan is more than merely tool settings and timers. To fulfil the users’ motivations and health objectives it should be based on standards and evidence-based practice guidelines. • Factoring in the levels of IT skills among different types of health SQ users could lead to a better understanding of who is likely to benefit from these activities and achieve associated health outcomes. REF: Almalki M, Sanchez F, Gray K. Quantifying the activities of self-quantifiers: management of data, time and health. Stud Health Technol Inform. 2015 Aug 12;216:333-7.
  13. HaBIC research: health social networks • Affordances of social media that may help explain the therapeutic effects reported by users include: self- presentation, connection, exploration, narration and adaptation. • Most people are not using social media sharing of personal health data to the extent that they might; some of the reasons for this reflect prudent personal decisions but others reflect social disempowerment. REF: Merolli M, Gray K, Martin-Sanchez F, Lopez-Campos G. Patient-reported outcomes and therapeutic affordances of social media: findings from a global online survey of people with chronic pain. J Medical Internet Research. 2015; 17(1):e20.
  14. Person-generated data: what could go wrong? • Accuracy? Do-it-yourself health data devices and services do not usually undergo the same degree of safety and quality governance as those used in clinical-grade care. • Usability? Person-generated data from a narrow range of devices and testing services are increasingly likely to be accepted in some electronic health record systems but integrating multiple data sets that you generate, in a readily interpretable way, is still immature. • Cyberchondria? “if you think you could get a report that you could get breast cancer, then you spend the next x number of years with sleepless nights thinking ‘oh am I going to get breast cancer or not, is today the day?’ … that sort of uncertainty is a little bit of a drawback” • Anonymity? It is possible to re-identify supposedly de-identified personal data using computing power that is now widely available. • Your best interests? It is legal in most jurisdictions for someone making a decision about your work, civic or financial status to search online social networks for information that you make public there. • Who else’s interests? In most commercial services’ terms of agreement, your data belong to them and they may sell it to third parties without your consent. • Over-spending, over-testing, over-diagnosis
  15. Person-generated data: hopes for better health for the individual • Perform at your best • Prevent avoidable health issues • Participate more actively in your clinical care • Enable personalization of your care
  16. Person-generated data: hopes for better health for all • Precision medicine based on big data and data analytics • Population health measures that respond rapidly to crowdsourced data • A health system that ‘learns,’ from the status of all its patients, how to improve its operations
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