Digital health and precision prevention: shifting from disease-centred care to consumer-centred health
Oliver J. Canfell
A B C D F G , Robyn Littlewood D , Andrew Burton-Jones C and Clair Sullivan A D E
A Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Qld, Australia. Email: c.sullivan1@uq.edu.au
B Digital Health Cooperative Research Centre, Australian Government, Sydney, NSW, Australia.
C UQ Business School, Faculty of Business, Economics and Law, The University of Queensland, Brisbane, Qld, Australia. Email: abj@business.uq.edu.au
D Health and Wellbeing Queensland, Queensland Government, Brisbane, Qld, Australia. Email: hwqld_exec@hw.qld.gov.au
E Metro North Hospital and Health Service, Department of Health, Queensland Government, Brisbane, Qld, Australia. Email: clair.sullivan@health.qld.gov.au
F Present address: Level 5, Health Sciences Building, Faculty of Medicine, The University of Queensland, Herston, Qld, Australia.
G Corresponding author. Email: o.canfell@uq.edu.au
Australian Health Review 46(3) 279-283 https://doi.org/10.1071/AH21063
Submitted: 26 February 2021 Accepted: 4 August 2021 Published: 10 December 2021
Journal Compilation © AHHA 2022 Open Access CC BY
Abstract
Digital disruption and transformation of health care is occurring rapidly. Concurrently, a global syndemic of preventable chronic disease is crippling healthcare systems and accelerating the effect of the COVID-19 pandemic. Healthcare investment is paradoxical; it prioritises disease treatment over prevention. This is an inefficient break–fix model versus a person-centred predict–prevent model. It is easy to reward and invest in acute health systems because activity is easily measured and therefore funded. Social, environmental and behavioural health determinants explain ~70% of health variance; yet, we cannot measure these community data contemporaneously or at population scale. The dawn of digital health and the digital citizen can initiate a precision prevention era, where consumer-centred, real-time data enables a new ability to count and fund population health, making disease prevention ‘matter’. Then, precision decision making, intervention and policy to target preventable chronic disease (e.g. obesity) can be realised. We argue for, identify barriers to, and propose three horizons for digital health transformation of population health towards precision prevention of chronic disease, demonstrating childhood obesity as a use case. Clinicians, researchers and policymakers can commence strategic planning and investment for precision prevention of chronic disease to advance a mature, value-based model that will ensure healthcare sustainability in Australia and globally.
Keywords: eHealth, preventive medicine, public health, public health informatics, medical informatics, noncommunicable diseases, childhood obesity, healthcare systems.
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