Person-generated health data: How can it help us to feel better?
Person-generated health data:
How can it help us to feel better?
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
• 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
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. http://www.slideshare.net/HINZ/ehr-the-killer-app
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
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.
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
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
REF: Prabhu D, Gray K, Borda A, Cyarto E. Independent
living on WHIMS. Information Technology in Aged Care
(ITAC) Conference, Melbourne, November 2016.
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
REF: Gray K. Like, comment, share: Should you share your genetic
data online?. Australasian Science. 2016 Jul;37(6):24.
• 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.
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.
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
hopes for better health for the individual
• Perform at your best
• Prevent avoidable health issues
• Participate more actively in your
• Enable personalization of your care
hopes for better health for all
• Precision medicine based on
big data and data analytics
• Population health measures
that respond rapidly to
• A health system that ‘learns,’
from the status of all its
patients, how to improve its