Q&A with Ai2: The Role of AI and Remote Patient monitoring in Eldercare

Concinnity Partners Jennifer Ayres and Samantha Collins sit down with Algorithmic Intuition, Inc. AI2 CEO Dan Brown and CRO William Glover to discuss how sensors and machine learning will transform Remote Patient Monitoring for the growing elder care market. 

AI2 provides an Eldercare monitoring system that combines machine learning / artificial intelligence software and specialized sensors to create an all-in-one solution identifying specific risks to seniors that can be curtailed with early intervention, including fall detection, early septicemia risks, heartrate, and location monitoring. AI2 aims to deliver cost savings and improve outcomes for clients and facilities. 

Q: In what ways do you see AI changing patient care in the US? 

A: These technologies will bring more sophisticated insights for caregivers to provide better care. Individuals will be empowered with the information they own and can share with whom they choose, as needed. Caregivers will be better informed about their patient or a loved one to make appropriate health decisions, especially about focused interventions. Provider or payers will have access to population data that will inform plan and policy decisions. 

Q: How do advances in AI improve the patient experience? 

A: We believe it improves the patient experience in three ways. 

  1. Many individuals are reassured by knowing they have continuous monitoring. If something happens to them, their loved ones will know about it. 
  2. There will be more appropriate and informed interventions. They will occur more quickly after a negative health event or even before an event occurs due to early detection trends. 
  3. This type of monitoring provides a level of discretion and patients own their data. 

Q: Among the biggest contributors to the high cost of healthcare in the U.S. are the inherent complexities and misaligned financial interests of payers, providers, and patients. How can Artificial Intelligence (AI) and machine learning (ML) not only improve patient monitoring but tackle some of the systemic challenges improving outcomes for payers, providers, and patients? 

A: First, it will help drive out unnecessary costs, creating greater opportunities for enhancements to health programs. Second, AI is better at detecting patterns that predict these problems. This allows a far less expensive and invasive intervention than an emergency hospitalization after the fact. Predictive consistency is one of the biggest benefits that AI brings to market across all users of the technology. 

Q: What about data and data security concerns? 

A: Anyone that has used wearable technology to monitor a patient, whether they are in the hospital, the home or in a facility, knows that data security is foundational. It is the same with remote patient monitoring. The individual’s data is owned by that individual, and they have control over who gets access. The industry has gone to great lengths to secure data with AWS, Microsoft, and other cloud technologies – remote monitoring uses the same secure mechanisms. Data goes into the secure data cloud that’s an industry standard. 

Q: How far away are we from realizing some of those improvements? 

A: There are good products (ours and others) in the market now that should be thought of as 1st generation eldercare AI remote monitoring tools that are better than the non-AI powered devices. They are the first step of several, and improvements will happen rapidly. Within a few years, not using AI-technology of some sort to take care of your elderly parents could be viewed as a form of neglect or malpractice. Some states have elderly abuse laws that criminalize inadequate care. We believe in the future there will be a tipping point where not using this technology will be considered irresponsible. 

Q: What are the greatest barriers to the advancement of AI and Remote Patient Monitoring? 

A: Acceptance. All great technology has to be accepted before it takes off. Ease of use and minimizing admin time for care providers is important for example. If it helps them and doesn’t create more work, they’re generally receptive to it. Improvements happen quickly which will drive acceptance. 

It’s also important to fit into existing systems that support health programs to reduce the friction of adoption. Education of health care providers and institutional providers about how this technology improves patient experience and mitigates the rising cost of healthcare plays a big role. The AMA and CMS for example, see the benefits which led to the release of new reimbursement codes in 2019. 

Q: What else will promote acceptance? 

A: Practitioners at large hospital systems with influence could advance the cause by prescribing the technology to get it covered by insurers. The billing codes are broad – any solution that leads to “better assessment or better care” that is prescribed could be covered. 

Q: Who stands to benefit the most in the end? 

A: Patients - who get earlier intervention and continuous remote monitoring. Care providers – who get rich analytical data to augment care once they learn to trust and accept the technology. Payers - who are concerned with technology investments that make financial sense. 

Q: Do you have partnerships with Payers to help them more quickly see or understand how these technologies will serve them? 

A: Yes, we do, and they’ll evolve very quickly. For example, homecare services are paid privately out of pocket. The benefits of our technology outweigh the incremental cost and they’re willing to pay for it. 

On the care facilities side, we’ll begin to see partnerships between those who are already billing Medicare against existing codes – ex) telemedicine, Physical therapy. For example, Medicare has allowed an additional $70/month if additional information can be used to assist with “predictability”. That’s where AI and our solution fits. Medicare understands where this is going and is ready; Insurance companies are the next to embrace these technologies. 

Q: When will insurance companies embrace these types of devices? 

A: We won’t know how to quantify the tipping point, but the more data the better. Insurance companies typically are trying to get specific data on a specific age group. For example, they want data on pre/post joint repair on females ages 68+. Having access to large data sets provides them predictive insights and informs health care programs offered. 

Q: If you were to take yourself out multiple years, where does this evolve to? 

A: I believe our solution and technology will be on the forefront driving market change. Consolidation has begun within the market starting with the back-office software providers. Going forward, I see the large corporations already selling point solutions in the medical market expanding into a more robust offering and moving into complementary markets such as chronic care, telemedicine, or consumer applications such as wellness or performance. We fit nicely into this environment, we are hardware agnostic, capture heart rate, respiratory, activity, temperature, and fall detection along with analytics. Users of our technology have been astounded by our reporting capability and identification of trends.