The Reuters Digital Health 24 event in San Diego brought together over 300 digital leaders from across healthcare to discuss the future of digitally enabled care. Hosted in San Diego, California the topic of conversation began with the lack of sunshine in a city that's meant to be 72 and sunny 365 days of the year because even sunny San Diego isn't immune to cloudy days during late spring. Discussion of "May Grey" and "June Gloom" quickly transitioned into how to innovate and drive digital transformation in healthcare. As the conversations got rolling one thing was abundantly clear: Artificial intelligence is here to stay and will only become more embedded into healthcare operations and delivery. But that doesn't mean the future is all mapped out. There are still a range of key questions the industry is solving. Here are some key outtakes.

The shifting tides of AI  

Healthcare leaders are witnessing a seismic shift in how artificial intelligence is viewed. What was once considered a "maybe" – an experimental technology to approach with caution – has rapidly transitioned into a "must-have." AI is a critical imperative for healthcare organizations looking to stay ahead of the curve.

In the near future, we expect to see an "AI-first" mindset take hold across the healthcare landscape. Innovative AI solutions will become the driving force behind virtually every initiative, from operational workflows to clinical decision-making and patient care delivery.

AI has the power to address some of health’s most pressing issues

Labor shortages, clinical burnout, profitability declines, and deteriorating value – these are just some of the most pressing issues healthcare leaders face while striving to maintain high-quality patient care.

Amid these challenges lies an opportunity for innovation, and artificial intelligence is emerging as a powerful tool to help bridge the gap. For example,

  • Dr Markus Blank from Bayer AG spoke about its partnership with Google Cloud’s AI to build a radiology AI innovation platform to combat imaging misdiagnosis.
  • Evie Cunningham, Chief of Virtual Care & Digital Health from Providence spoke about solving patient flow issues by using virtual experts to meet capacity demands.
  • Laura Wilt, SVP and Chief Digital Officer from Sutter Health discussed their use of augmented response technology to decrease the cognitive load on clinicians.

For the best value creation, begin with the problem, not the solution

Here’s an interesting stat: Healthcare systems are managing on average 800 solutions within their technical stacks. It's no surprise finding consolidated, multi-pronged AI solutions is a priority for digital leaders.  

One point was crystal clear: the criteria for deciding what to invest in shouldn't begin with a solution. Rather, the best way to achieve true value creation is to identify the specific problem. This allows for more flexibility to align with the greater needs of the organization, find efficiencies within the technical stack, or even potentially build more custom solutions.  Beginning with the problem ensures you can minimize bad purchases, costly implementation, and failed adoption.

Digital transformation can only scale when change management is properly accounted for.

Healthcare systems have transitioned from merely considering AI to realizing its necessity. While the acceptance hurdle has been overcome, innovation is now shifting into operation. I.E. how to adopt an AI solution into the day-to-day practice.

The challenges are multifaceted. Digital transformation necessitates changes to clinical workflows, often facing resistance from providers accustomed to traditional methods. Robust governance frameworks are crucial to ensure technology is utilized ethically and responsibly, but it can slow the rate of innovation, particularly across large healthcare systems. User experience and integration obstacles must be addressed. For widespread adoption, solutions must be user-friendly, time-saving, and seamlessly integrated into existing IT infrastructure without excessive complexity or training demands for clinicians.  

Underpinning all of these challenges was the idea that digital transformation can only scale when change management is properly accounted for. For change to stick, the stakeholder pool must run deep - from the frontlines to the executive ranks. Aligning with the real-world experiences of clinicians, patients, and regulatory teams breeds solutions tailored to actual needs. Comprehensive collaboration is table stakes. As is recognizing that baking in incentives may be necessary to spark sustainable adoption.

Hyper-Personalization: Advances in Value-Based Care

One of the panelists at Digital Health boldly said “Hyper-personalization is the future of healthcare.” Moving beyond the one-size-fits-all model, hyper-personalization tailors treatments, preventive strategies, and patient engagement to each individual's unique genetic profile, lifestyle factors, and risk markers.

The potential benefits align squarely with the core tenets of value-based care - improved outcomes, reduced costs through preventive interventions, and more efficient resource utilization. However, clearing the substantive hurdles to realizing hyper-personalization's full impact won't be easy.

Concerns around data privacy, mitigating algorithmic biases, and ensuring transparent AI decision-making processes must be addressed to build trust. Regulations will need to evolve to accommodate the complexities of precision medicine.

Perhaps the biggest challenge lies in democratizing access. Value-based care hinges on delivering better health outcomes while controlling costs - but only if those benefits reach all patient populations equitably. No one can be left behind as healthcare pushes into this hyper-personalized frontier.

If you’d like to learn more about these trends, or how we can partner with you at Significo, be sure to reach out -