The challenges, and opportunities, brought about by moving progressively towards a personalised health and precision medicine agenda, will test the mettle of the digital foundations within the Australian healthcare system revealing that many systems are not yet up to scratch in terms of handling complex data flows and enormous data sets. The interoperability agenda is key, and this must be pursued vigorously if we are to realise the potential that precision medicine presents.
Electronic patient records in Australia, have done well in recording what happens to patients – encounters, diagnoses, pathology and prescriptions, and Share by Default legislation is proving very effective in progressively expanding this functionality in the My Health Record.
Precision health however, extends this proposition by posing the question: “What might happen to that patient, and by extension, how can we either prevent that from happening, or intervene earlier in the course of any disease or illness?” To answer these questions, we need to combine the clinical data from healthcare delivery organisations, with genomic (and increasingly other “-omic”) data, with data derived from wearable devices, and data about environmental and social factors, producing real-time, dynamic risk assessments that reflect the evolution and changes over time of a person’s health status. The current approach – designed as a filing cabinet for what has happened so far – doesn’t, and won’t cut it, in terms of a learning platform that shifts the dial from episodically reacting to patient presentations, to progressively predicting and preventing the onset and/or progression of disease states.
Australia’s infrastructure challenge
Australia is relatively advanced in precision health. Numerous genetic therapies aligned to genome analysis are already being used, genetic screening is becoming routine, and there are ambitious programmes in place in fields such as child and adult cancers. But significant equity challenges exist in the application of genomic technology and knowledge for First Nations Health purposes, and ensuring people in rural and remote areas have access to these highly specialised services which are inevitably concentrated in cities, exacerbated by the shortage of specialist staff such as geneticists and genetic councillors.
To achieve precision health’s aims, significant investment in electronic health records, secure data centres, biobanks and integration layers will be required. This will not only come from public expenditure but will also necessarily come from public-private partnerships involving state and Commonwealth governments, industry, and research organisations and funding bodies.
These platforms will be working with high-dimensional data: whole-genome sequences, biomarkers and other data derived from advancing imaging technologies, as well as longitudinal wearable and social care phenotype data. All of these data will be FAIR: Findable, Accessible, Interoperable, Reusable – and will be connected through My Health Record APIs and integrated into predictive models that are updated by new data from initiatives such as clinical trial and “-omic” studies.
AI in the future EHR
AI and precision health are inextricably linked. AI systems, properly managed and explained, will be critical to the analysis of the huge datasets involved, detecting patterns beyond human cognitive detection. However, it is no longer sensible to simply bolt AI tools into our static systems. The future of EHRs must support risk-based decision-making and must be able to seamlessly integrate AI tools and the outputs from these tools. This is much more complicated than our current rules-based alerting systems.
Designing for what is beyond the walls of the hospital
Much of the data that will power precision health will come from genomic and other -omic testing facilities, community providers and organisations, sensors in the environment, and wearable devices. In other words, non-traditional sources of health data. The future EHR and linked healthcare provider digital systems must therefore recognise this networked (and therefore by necessity interoperable) ecosystem that facilitates exchange and linkage of this data, agnostic of its primary collection source.
Data about our health must flow in ways that allow insights to move with the patient, in and through time. This means that national support and processes for interoperability, open standards, and shared frameworks, is not simply nice to have, but essential for the success of the precision health and precision medicine agendas.
Equity and trust must come first
Precision health will fall short of expectations, or fail from a moral standpoint, if the data it is founded upon does not include significant representative proportions of our population. Minority groups are underrepresented in genetic studies and biobanks, and some of these may be more sceptical about taking part in data-driven medicine because of the distrust engendered by history.
What needs to change at this point
The business cases for investing in digital technology should account for the value over the life of the EHRs and associated systems, and support the roadmap towards precision health. Open APIs, genomic and imaging integration, and the integration of AI are “mission critical” considerations in procurements as we progress this agenda.
Clinicians must recognise the value of data in clinical practice. To achieve success in precision health, clinicians who work with these systems on a day-to-day basis should view data collection not only as part of an administrative task, but also an integral part of their own clinical practice. The challenge for health systems is then to ensure that the efforts of clinicians to improve the accuracy of data collection are translated tangibly into improvements in the ability of clinicians to deliver better care.
A turning point in digital health
The electronic health record has been considered the epicentre of electronic healthcare from the beginning of the modern digital health age. Precision health will however challenge this paradigm, requiring the input of data from multiple sources, of which an EMR (or EHR) is a necessary and critical player, but is not sufficient in and of itself to prosecute this much wider agenda.
The Australian government and the wider health sector must understand that precision health is not so much a technical problem, but rather a strategic issue and direction. This is because the future of precision health will depend on the strategies that we adopt in the design and investment in digital infrastructure in Australia now, and into the future.
Realising the potential of precision health requires a sustained effort by all governments, regulators, system leaders, providers, academia and the private sector. A recent report from the Beamtree Global Impact Committee looks at the potential of precision health – and calls out the risk of poor implementation on the costs of healthcare, inequalities in health outcomes and access to services. Realising the benefits of precision health requires concerted action by governments, system and community leaders and industry. It is also vital that we make sure that the systems we build not only record what happens in the provision of episodic care, but also increasingly provide us with the ability to look ahead to what could happen, enabling us to act pre-emptively.
Professor Keith McNeil
Professor McNeil brings a broad and deep experience across healthcare and is passionate about leveraging the digital agenda to transform patient outcomes and embed sustainability in the Australian healthcare system.
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