How AI is Increasing Healthcare Access

Q: How do Lumiata models and tools translate to a better decision-making process for hospital administrators?

A: One of the challenges we are addressing with hospital systems is determining who is in most need of urgent care. We are working with US hospitals to reduce the number of repeat emergency visits by helping them determine which patients are more likely to come back and when. We can help these hospitals to improve the patient’s health before there is an emergency. We have dozens of models that track the progress of different diseases, such as heart or kidney failure. These disease models help administrators manage the patient flow in hospitals and reduce the cost of care. This also helps them provide care to those who need it most, especially now that we are living under a global pandemic and so much of a hospital’s capacity is taken up by those who are in the ICU due to COVID-19 complications. These tools are critical considering the strain that COVID-19 has placed on so many healthcare systems.

Q: What are the main lessons hospitals and healthcare systems have learned from this pandemic?

A: Public healthcare systems have realized that their capacity to handle so many patients is limited. Hospitals need better support systems to manage their capacity. Many hospital systems invest in technology but do not prioritize how they manage their capacity.

One of the positives that has come from this otherwise tragic experience is the use of telemedicine. Hospitals and healthcare systems used to be reluctant about telemedicine but now patients are seeing the advantage of attending a doctor’s appointment from the safety of their homes, offices or cars. This should have happened years ago but we were behind in regulation and hospitals and clinics were not ready. In the US, for example, about half of patients who had a doctor’s appointment during the nine months used telemedicine. Before the pandemic, the average was only 5 percent. The increased use of telemedicine impacts how Lumiata can help hospitals. The visits are generating a large amount of data that we can use to better engage with patients.

Q: What are the main areas in which Lumiata supports hospital management following the COVID-19 pandemic?

A: After COVID-19, some of our existing solutions became even more relevant. Data is the fuel for our technology; the more data there is, the smarter our models can be. With COVID-19, we have started to receive a lot more data. The two key areas we focus on are risk and cost management. Providers and insurers can use Lumiata to better underwrite a health plan. Risk management solutions become even more crucial in this pandemic because the risk has only increased. Millions now have a pre-existing condition after contracting COVID-19. For that reason, managing risks has become even more critical. Also, the risk volatility is up as we still do not know how long the pandemic will last and how many more will be infected, even after vaccines have arrived. Underwriting and managing the increased risk and risk volatility will require a decision support system and data science technology, which means AI will become increasingly relevant. We saw an increase in demand for Lumiata before the pandemic, but it became even more relevant after COVID-19 hit.

Q: How are you tailoring your products to the local market?

A: The country has a large population and limited resources, so the healthcare system has to prioritize who comes in at what time. The main challenge we are facing in the US is that the cost of care has risen to unacceptable levels, so cost management has become a priority. The US has the means to provide care but services have become too expensive and out of reach for many. In Mexico, the cost maybe less of an issue. The major problem in the country is providing access to quality care. Lumiata products can help systems determine which patients to prioritize. For example, we can monitor diabetes Type 2 patients using AI and determine who might need medical attention sooner. Lumiata can help the government effect better public policy.

One of the things I am most excited about in Mexico is that we get to work with a new, diverse population, which will enrich our data and models. In the US, the impact of COVID-19 was highest on minority communities because, generally speaking, they are often the frontline workers who were carrying our economy forward in the middle of the pandemic. These communities paid the highest price during this pandemic. There is an opportunity to put data science to use to address these communities’ needs in the manner that they deserve.

Q: What challenges do you foresee in expanding your services into Mexico?

A: A challenge we might face in the country is ensuring there is enough data digitized to generate a solution. Our models are directed toward larger health systems but we can also help individual clinics that are part of a larger system. We would need to ensure access to sufficient healthcare data to measure trends regarding access to care and cost management.

Q: What will be the long-term role of AI and data science in healthcare systems?

A: Healthcare systems all over the world have totally been transformed by the COVID-19 pandemic. In advanced economies, this pandemic has proven that even if a health system has the available capacity, if hospitals do not use of technology to provide attention at the right time, the patient flow will surpass them. Technology can empower healthcare in these unprecedented times. After the global pandemic, data science and AI will be the backbone of healthcare systems. They will influence how we are doing analyzing patients, how we are targeting care and to whom. We had the technology before the pandemic but there was resistance from the status quo in the industry that frankly has often profited from intrinsic inefficiencies of the systems . Healthcare organizations can no longer afford to resist or be slow to change. Many US hospitals will be insolvent after this crisis and many healthcare plans have been strained by the cost of treating this virus. We are seeing more openness from hospitals and health plans to adopt this technology. AI and advanced data science will to become an essential tool in managing public health and the delivery of healthcare services all over the world.

Lumiata uses AI and machine learning to develop technological solutions for the healthcare sector. The company operates in the US but is entering the Mexican market through its offices in Guadalajara.