Industry executives and experts share their predictions for 2023. Read them in this 15th annual VMblog.com series exclusive.
How the pandemic will accelerate adoption of healthtech in 2023
By Chris Tackaberry, co-founder and CEO of
Clinithink, a software company tackling some of the biggest challenges facing
health systems
A left shift is needed, and AI will play a key
role as we move into 2023.
During the pandemic, around 4 in 10 adults delayed or avoided
medical care because of concerns around Covid-19. 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 pandemic and the ‘Covid
hangover' will be felt. Health systems 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
organizations 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. Streamlining systems and cutting costs using automation
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 organizations 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. How we treat patients needs a ‘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 business as
complex and human-centered as healthcare.
Healthcare needs a genuine ‘left shift' - a
move from focusing on treating patients in hospitals, to treating patients in
the ambulatory and community settings. This model enables earlier, more
effective interventions and treatment, improving patient outcomes while
significantly reducing the burden on health 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 biggest cause of cancer death in the US,
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. Harnessing the predictive power of AI will be a game changer
Although AI has come on in 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 reducing the cost of health insurance.
4. Improving data flows to
enhance patient care and health system efficiency
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 jeopardizing the
quality of patient care.
There are significant financial and health
incentives for health systems to look to break down data silos - streamlining
the medical process and reducing redundant care and the associated costs.
5. Ongoing moves towards a value-based care
model
For the past decade, value-based care has been
presented as the silver bullet for healthcare. Certainly, alternative payment
models have been part of the landscape for some time and dual-risk models are
now a reality, but when we look at healthcare spend in the US, it only makes up
a fraction of the fee-for-service model.
That being said, it's possible that the Covid
hangover will propel takeup of value-based care at a much higher rate. Those
organizations carrying the economic healthcare risk for their members - be that
CMS, commercial insurers or large self-insured employers - will all gravitate
towards value-based models precisely because they deliver better value, and no
one has money to waste.
Post-pandemic
pressure could cause 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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ABOUT THE AUTHOR
Chris Tackaberry, founder and CEO at
Clinithink
Dr Chris Tackaberry is
a qualified physician and MSc Computer Science graduate who spent nine years in
medical practice in anaesthesiology and intensive care before embarking on a
career in healthcare IT.
He is co-founder and
CEO of Clinithink where he and his colleagues develop AI software to enable the
healthcare and life science ecosystem to extract value from rich unstructured
data in clinical narrative.
Before co-founding
Clinithink, Chris built a successful consulting practice focused on technology
strategy, product management and major systems implementation for clients such
as Silver Lake Partners, the UK Department of Health and Skype.