Chris Tackaberry, founder and CEO of Clinithink, a software company tackling some of the biggest challenges facing healthcare, explains why a left shift is needed and how AI will play a key role as we move into 2023.
And while the impact of this began to be seen in 2022, it will be over the coming 12 months that the full force of the ‘Covid hangover’ will be felt.
Healthcare organisations will not only be contending with an excess of patients seeking care, but also more acutely ill patients, who missed opportunities for earlier intervention and will therefore be presenting with more advanced or complicated disease.
This will put additional stress on hospitals already buckling under the strain of high workloads, overstretched staff and tight budgets.
Healthcare is at a critical juncture, and it’s hard to see a way out of these financial and staffing difficulties without greater use of technology to ease the burden on both frontline and back-office support staff.
Here are five healthtech trends we’ll be closely watching in 2023.
1. Automation as a way to streamline processes and cut costs
A guiding IT principle is: look to automate systems that are manually intensive.
When done in this way, automation can help relieve staff of repetitive, time consuming tasks – enabling organisations to get more done without hiring more people.
We are already seeing automation being used to good effect across a multitude of healthcare processes – from automated appointment scheduling, to tools that enable hospitals to automatically adjust staffing levels in line with fluctuating patient demand.
For example, digital assistants are being successfully applied to many of the administrative tasks associated with patient visits, freeing up precious human time for the important, higher value person-to-person tasks that sit at the heart of a healthcare encounter.
2. We will start to see a genuine ‘left shift’
Automation on its own won’t be sufficient to solve the Covid hangover.
Processes can be streamlined and made more efficient, but automation can’t (and shouldn’t) replace all of the tasks in a domain as complex and human-centred as healthcare.
Healthcare needs a genuine ‘left shift’ – a move from focusing on treating patients in hospitals, to treating patients in the out-patient and community settings.
This model enables earlier, more effective interventions and treatment, improving patient outcomes while significantly reducing the burden on healthcare systems’ clinical resources and budgets.
Artificial Intelligence will play a key role in accelerating this left shift.
For example, AI technology is starting to be used to flag up patients with early-stage, treatable chronic diseases, when they are feeling unwell, but before they have symptoms that can be linked to an underlying cause.
If we take lung cancer, which is the third biggest cause of cancer death in the UK, we see that survival rates drop significantly if the disease is caught in later stages.
Thus, AI supports a left shift that results in earlier disease detection and diagnosis – improving patient outcomes and reducing healthcare costs.
3. AI as a predictive tool
Although AI has come on leaps and bounds, we have only scratched the surface of the technology’s potential in healthcare.
The technology is already being used to find people with collections of characteristics that signal early disease, and the next step will be to use AI to predict the people most likely to be at risk and to focus screening efforts on them.
Although this has been the long-standing goal of public health, the accuracy that AI enables means that providers can confidently focus on very specific groups of people who are at highest risk.
The predictive capacity of AI will be a game changer in healthcare, pushing the clinical intervention point even earlier, improving patient outcomes and population health.
4. The breakdown of data silos
In 2023 we are likely to see more data sharing, which will increasingly be patient-led and patient-directed.
When a patient is referred to a different team or changes physician, poor data flows can negatively impact the efficiency of the clinical process and the quality of care.
It’s not uncommon for patients to be asked the same question numerous times or for tests to be needlessly repeated.
At its most problematic, inadequate data sharing can result in critical clinical information being missed, leading at the very least to repetitive information gathering, and at worst to longer stays or more frequent hospital visits, and jeopardising the quality of patient care.
There are significant financial and health incentives for healthcare organisations to look to break down data silos – streamlining the medical process and reducing redundant care and the associated costs.
5. Big data to tackle global health issues
The pandemic demonstrated the potential of large-scale data to help better understand human health.
For example, the ZOE COVID Study, which was launched at the very start of the pandemic, used self-reported data to uncover key symptoms of the virus, including that breakthrough insight that anosmia was a key predictive symptom.
This was all achieved within a few months of the tool launching, highlighting how data capture on topics such as symptoms, diet and day-to-day behaviours can provide invaluable insights into population health.
The tool is also a great example of consumer-led engagement with health records and health data. Without taking a Digital Health approach, this level of insight would have taken years to obtain.
A technology tipping point
It’s no secret that healthcare has been far slower than other sectors to embrace technology, but the overwhelming pressures exerted by the Covid hangover, coupled with skills shortages and global inflation, will act as a catalyst in uptake of healthtech in 2023 and beyond.
It’s increasingly clear that AI can save astonishing amounts of human time, freeing up healthcare professionals to spend more time with their patients, and that the technology can make things possible that are simply impossible any other way.
We need look no further than Amazon or Netflix to see that AI is now commonplace in the consumer experience, and we are seeing this acceptance of AI filtering into the healthcare setting.
Regulatory bodies are beginning to acknowledge the immense value the technology can deliver, and are extending their frameworks to foster safe but rapid innovation.
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