AiThority Interview With Rick Halton, VP of Product and Marketing at Lumeon

How did your career start in Healthcare? What associated you with Lumeon?

My career started not in healthcare, but in the field of telecommunications at the dawn of the digital mobile age, where I worked through waves of innovation that took us from brick-style cellphones to the launch of the mobile Internet. I entered the world of healthcare in 2010 when I co-founded my first health startup in Chicago to address the frustration that doctors and care teams experience every day using skeleton clinical guidelines. This type of heavy cognitive processing leads care teams to take different routes or even miss steps, often leading to inconsistent, costly care and variable patient outcomes.

Over time, I recognized that healthcare an industry that’s been slow to adopt new technology is now on the verge of this digital revolution. Instead of guidelines, we have pathways that become the cognitive processor behind everything clinicians need to do, allowing clinicians to focus on what they do best. With most health systems that have adopted Electronic Health Records (EHRs), patient data is now digitally available. But while EHRs have helped hospitals, to date patients haven’t noticed a difference – EHRs aren’t the processor, they are the memory.

I’m passionate about helping the healthcare industry better leverage technologies and learn from other sectors so people can live better longer lives. Lumeon is driving real change in today’s complex healthcare system, helping healthcare organizations automate systems and processes, bringing together the potential of their organization to deliver high performance, team-centered healthcare. I truly believe that greater automation in healthcare can transform the industry and delivery of care, which is why I joined the Lumeon team in 2017.

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How do you relate to AI and other intelligent technologies in your daily life?

I first started working with AI and intelligent technologies in the form of Clinical Decision Support algorithms, or CDS for short. CDS algorithms process patient data and help clinicians make decisions. They can be used for a huge variety of applications, such as simple assessment of severity or acuity, through to intelligent prediction of patient deterioration from organ failure or life expectancy due to cancer.

Lumeon’s Care Pathway Management (CPM) platform orchestrates patient pathways combining multimodal patient engagement and care team coordination, together with intelligent clinical decision support algorithms to deliver optimal organizational performance at a lower cost. By connecting and orchestrating people, processes and existing technology across the enterprise in real time, clinicians can focus on delivering care – versus administrative tasks while providers are empowered to thrive in the era of pay-for-performance and consumerism.

As vice president of marketing and product, I’m exposed to the ins and outs of Lumeon’s technology and how our platform is driving greater automation for health systems. The ability to automate and orchestrate a large variety of elements along the patient journey enables a truly patient-centric process, rather than the fragmented experience many patients and care teams are used to today.

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What drives greater automation in healthcare?

As healthcare transitions to a value-based care model, healthcare organizations are increasingly paid less to do work, but more to achieve results for patients. In other words, the difference between profitability or bankruptcy is how cost efficiently can your organization produce a given result. Healthcare needs to do more with less, and it’s here that care automation and virtualization enter the scene.

Virtualized patient engagement, for example, is creating some unexpected effects. On the upside, it’s creating unprecedented access to healthcare providers and opening the floodgates for patients to initiate contact. But, on the downside, it is creating a burden for healthcare organizations that aren’t prepared to respond to the tsunami of patient communications.

To mitigate this, healthcare organizations are increasingly looking for ways to make patient engagement more agile, including turning to technology to help them manage and automate communication and tasks between the patient and the care team efficiently.

By taking real-time data from disparate systems and aligning it with the patient care journey, doctors can ensure that every patient is following the right protocol at the right time, and in the case of variation, intervene instantly to prevent problems before they get worse.

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How have AI and automation begun to permeate healthcare? What are the common applications of this technology in the industry today?

Within the context of the patient care plan, there are numerous activities that can be automated from automatically guiding patients from their online booking system to digital pre-appointment questionnaires and screening processes, to automatic sending of personalized education materials and appointment reminders, as well as automated outcome tracking and recall after their appointment.

However, the best applications of automation in healthcare are the ones that maintain a healthy level of personalization. For instance, through intelligent risk stratification, care teams can effectively tailor patient interactions based on the individual. This means that high-risk patients – like the elderly, or individuals with co-morbidities – could receive a more frequent manual intervention, whereas low-risk patients may receive care that is more hands-off, such as automated engagement and digital coaching.

Patient preference is another way of looking at personalization. For instance, healthcare providers must be able to effectively communicate with each patient the way he or she prefers. This could mean text messages, phone calls, or even postal letters; and if one strategy doesn’t work, detect it and adapt it, and do so automatically.

Using advanced AI techniques, we can start to predict which patients are more or less compliant to care pathways and to adapt to their personality types with different methods of encouragement. In addition, we can leverage AI technologies to have conversations with patients through text and voice, such as via WhatsApp, enabled by an AI brain, to assist in the triage of patients.

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What are the future advanced applications of AI in healthcare?

The next step in AI and automation innovation is orchestrating not just the workflows behind patient interactions, but also orchestrating the actions that need to be performed based on the results of those interactions.

Think of this as adapting care to the patient in real time having already processed lots of patients and gathered lots of past data points. With this approach and techniques like Machine Learning, we can understand how to configure the pathway route and decisions to help the patient achieve the best outcome quickly with the least resources. This is what we might call adaptive care pathways powered by real-world clinical data.

In what ways is the growth of AI and automation in healthcare similar and/or different as compared to other industries?

AI has permeated nearly every industry to date. The greatest difference between healthcare and most other industries is the rate of adoption. Healthcare has historically been slow to adopt new technology – and AI is no exception. While industries like manufacturing have been automating workloads for years, much of healthcare is still done manually. As a result, the industry has been slower to realize the benefits of greater efficiencies; however, I believe that over time we will see the rate of adoption quicken as industry leaders realize how this technology can impact not only their own workload but also the delivery of care to patients as well.

That said, the greatest similarity I’ve seen between the growth of automation within healthcare and other industries is the emphasis on personalization. Previously, we discussed how greater patient personalization has been the primary result of automation in healthcare to date. Similarly, the use of AI and automation in other consumer-facing industries such as retail and entertainment (streaming of music and videos, for example) allow companies to deliver high levels of personalization to end-users. I think that this similarity also speaks volumes to the broader consumerization of healthcare we’re seeing take place as well.

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Where do you see this technology heading over the next 5-10 years?

I see AI and automation taking off in several different ways:

• Always on Care – the ultimate enabler of preventative, precision medicine – it would guide you with the help of AI virtual assistants and clinicians that never leave your side. These assistants gather and intelligently process data and results from multiple medical sensors and devices both at home or in your pharmacy, providing immediate results and guidance about how to improve your lifestyle and wellbeing, and to detect illness much earlier than could be ever imagined.
• Smart Clinical Decision-Making – where clinical decisions are enhanced with AI recommendations that take into account not only your current clinical data, but your overall trend, history, lifestyle, medications adherence, test results, and genetic information to decide what is most likely going to help you recover faster. This capability might be further enhanced by purchasing clinical brain extensions, specialized in different disease areas.
• Adaptive Care Pathways – real-time learning unfolds your unique pathway blueprint as care is delivered by learning from the past patient experiences to understand the probability of which actions are most likely to achieve the best results for you. They have a huge potential to leverage EHR data to assist care teams to focus on what’s important.

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What are the biggest potential benefits of greater automation in healthcare?

For healthcare providers, automated care pathways can pay off in a big way – they will not only see advantages in the short term, but they’ll be well-prepared for the future, as alternative healthcare models focused on value-based care become more widespread.

As one example, they can more effectively coordinate pre-surgical readiness and identify risks that typically lead to delays. Late operating room cancellations, for example, are extremely costly, as a provider is potentially leaving the operating room (OR) vacant or teams are left scrambling to reschedule patients.

Care pathway automation also addresses problems with risk-based payment models. By deploying a platform for care delivery operations, providers can more efficiently use the resources they’ve already got, including their EHR, to deliver care more consistently and ultimately, protect themselves from margin erosion.

The positive impact of care pathway automation is especially powerful when it can pair patients with enhanced recovery techniques, allowing patients to achieve a better outcome more quickly. Specifically, improvements in patient education, transportation services, and clinical efficiency can help better engage patients in follow-up care.

Finally, there is an emerging need in today’s market that’s being driven by the prevalence of smartphones, along with patients with high digital expectations who demand care delivery at a distance and want to take advantage of virtual care delivery and digital communication. Using automation, providers can expand the reach of their services to lower acuity and underserved populations. The beauty of this approach is it can be applied to a range of provider issues, from appointment reminders to post-op check-ins via SMS, to help avoid readmissions.

All in all, automated care pathways can help providers overcome a number of hurdles that are all too common from reducing appointment no-shows, increasing revenue through patient recall, and reducing readmissions through deploying enhanced recovery techniques before surgery.

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What challenges will the industry face along the way?

Automation and its potential to create real-time health systems are part of a bigger movement toward the consumerization or “retailization” of healthcare. Much like how Amazon and other retail giants are using customer information to automate their systems, healthcare organizations are leveraging real-time patient data in ways that streamline and improve the patient journey.

Real-time health systems are achievable today. Indeed, the technology exists to enable organizations to orchestrate and automate processes in real-time, personalizing the patient experience while streamlining care team activity. But before all organizations can realize their potential, they must overcome one major industry pain-point: the customer is often not the patient.

This stems from the way physicians have traditionally been paid. In many of today’s U.S. healthcare systems, even though it isn’t explicitly stated, the patient isn’t actually considered the “customer.” In reality, it’s the external physician that is truly the customer, as they own the relationship with the patient upset the physician and they can practice elsewhere, taking their referrals and patients with them. The employment status of its affiliated physicians is one of the core reasons why some hospitals are able to implement system-level change quickly, and why others simply can’t.

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How can industry leaders best prepare to overcome these challenges?

The good news is that the notion of the physician as the customer is already beginning to change. New payment models are shifting the value to focus on the end-to-end process and outcome, as we are seeing with hip and knee and cardiovascular bundled payment models. This means that rather than IT infrastructure being built around the physician, it must instead be designed to enable care teams to collaboratively engage the patient across the end-to-end journey. The industry must accept the idea that organizational re-design is going to be necessary before achieving a real-time future that truly consumerizes the healthcare experience.

What are the regulatory implications of AI in healthcare, including compliance with the FDA and HIPAA, for instance?

While automation and AI assist clinicians to process data and make better decisions, the risk to patient safety can be considered low, as the human is always in control of the final recommendation, decision or course of action. As AI has greater influence and starts to make patient recommendations and perform actions on behalf of humans, there will clearly need to be more checks and balances in place by firms and regulatory bodies, such as the FDA. An early example of this would be AI-assisted image recognition for bone or organ scans. While a radiologist makes the final decision and signs off on the conclusion, the risk remains low; however, technology is taking over fast. AI can be applied to many problems, so different AI applications will need to take into consideration HIPAA and HiTech rulings appropriately. AI may actually be assisted by other technologies to help secure patient data, such as biometrics using voice imprint or facial recognition, or multiple methods in parallel to secure and unlock personal health information.

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What excites you the most about the growth of AI and automation in healthcare?

I am most excited to see how the growing use of these technologies transforms both the patient experience and how it’s delivered on the back-end. Care teams including doctors, nurses and numerous important players work hard and are often overwhelmed with high amounts of administrative tasks. Automating their workloads can help free up their time spent on administrative work and enable them to do what they love: care for their patients. This will not only improve the quality of work for care teams but also opens doors for their own career development by enabling them to focus on higher level tasks and responsibilities. Meanwhile, this will also vastly improve the delivery and quality of care, as well as outcomes for patients.

Embracing automation and AI in healthcare means all parties win and I look forward to seeing how technology can further transform the delivery of care.

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Thank you, Rick! That was fun and hope to see you back on AiThority soon.