The problem worth solving

At Axenya, we frequently get asked about our unique perspective in the healthcare industry. This article delves into our thesis and explains why we're establishing a new category of healthcare player.

Axenya aims to re-imagine the way people choose, purchase and consume healthcare coverage and associated services. We are not going for better, but for radically different.

By definition, this means we believe that things in this market are being very poorly done. This is no secret. Everywhere around the world, costs for healthcare coverage are skyrocketing, plans are losing money, reducing coverage and decreasing quality. Users and their employers (who pay for the plans), are forced to buy supplementary services without clearly understanding what, why or how they should think about them in the context of overall health. Nobody is happy. A market where suppliers lose money and customers are unhappy is the quintessential definition of poorly done. Couple that with the fact that it is a 5T market worldwide and you got a moonshot.

Our central thesis is that the system was designed several decades ago, based on centuries-old practices. The reality of life in the 21st century is fundamentally different and, thus, require a different approach. Let’s explore that.

Disease comes in two flavors: fast and slow. Typically, when you are young, your main issues are of the fast type. You fall, you break a leg, you get a cast, done. You get a flu, you wait a week, drink plenty of fluids, done. Next time, you get a vaccine and maybe you don’t even need to start with it. The system was incredibly good at dealing with that. Now, we live longer, and we have time to develop slow diseases. And this is where trouble starts. No noticeable onset, multiple causes, no clear symptoms, slow progressions. All these factors cannot be addressed by a shot. Multiple solutions need to be applied simultaneously, over long periods of time. Coordinating this mess is a major headache. And for a system that was basically modeled after an arcade game (wait for the alien to appear, shoot, dead, done) this is a nightmare.

This is not, in its surface, very different than the myriads of fragmented offering problem that digital marketplaces, like Amazon, solved. But healthcare is a different beast. Buyers are not users, decision makers are not payers, you bump into regulation at every step and the amount of knowledge asymmetry between actors and the mathematical complexity of the predictive models required makes finance look like a walk in the park.

It is important to notice that this is not a medical problem, but a cybernetic problem. We have the medical knowledge and, somewhere, hidden in thousands of unconnected repositories, we have the data we need. It is just a question of putting it together. Organizations everywhere, from the American CDC, UK’s NHS or PAHO calculate that about 60-80% of healthcare costs are due to this inefficiencies and not to the lack of proper medical solutions. You don’t need to do the math to understand that 60-80% of 5T is a huge number. Or, if you want to put it in concrete terms, it is a number big enough to solve the global access to health problem. World Bank and WHO calculate that today about half the world lacks access to essential health services. You could save money to serve all of them and still get some change to throw into global hunger or other pressing problems.

This is where Axenya comes in. We are building a data-intensive, highly intelligent marketplace that helps users understand, buy and combine the right set of solutions for their specific needs at any given time. In doing so, we are also creating a channel for innovative digital solutions to reach their intended users—a problem that has yet to be adequately addressed.If we are successful (as we have promisingly been so far) we will not only improve people's health but also significantly reduce healthcare spending. By a lot.

On a simplified vision, we can divide the history of medicine in three stages. Med 1.0. (from antiquity until roughly the second half of the 19th century) was shaped by a myriad of social, cultural, and technological factors. Early medicine encompassed a plethora of theories, both scientific and non-scientific. Many practices were often inadequate for addressing serious health issues. The plague, which decimated half of Europe's population in just three years, serves as a stark reminder. In the absence of scientific theories explaining diseases, practitioners relied on one-size-fits-all solutions, such as humors, herbal medicine, hydrotherapy, acupuncture, and homeopathy. The 19th-century discovery of germ theory by Louis Pasteur revolutionized the field, laying the groundwork for Modern Medicine. This era saw significant medical advancements, such as vaccines, antibiotics, and improved living conditions, contributing to increased life expectancy. It also led to the emergence of medical specialties, fragmenting the field. Modern Medicine also led to the establishment of healthcare coverage. The first recorded pre-paid insurance system was introduced in 1930 by a group of Dallas school teachers who partnered with Baylor University Hospital. This was followed by companies like Blue Cross, Blue Shield, AETNA, United Healthcare, and Cigna. The UK's NHS began its services in 1948. The turn of the century has brought a shift towards a proactive approach to health, or Med 3.0. This approach emphasizes an evidence-based framework for personalized preventative care, aimed at helping patients live longer and healthier lives. Medicine 3.0 demands alterations across various dimensions. First, the doctor-patient relationship should be long-term, extending over decades rather than minutes (the average doctor consultation is 14 minutes). Second, ongoing monitoring is vital for illness prevention (there are no visible symptoms that will indicate a patient to go to a doctor and, even if there were, which doctor?). Third, addressing a condition often necessitates multiple services or specialties and personalized medicine requires distinct data for each patient. In the ideal scenario, each individual could be viewed as their own unique condition (who is capturing and centralizing this data?). Moreover, the escalating complexity in the field demands deep specialization in specific areas. It is virtually impossible for one person or institution to achieve breadth and depth at the same time. However, these specializations must work together synchronously. Achieving all this necessitates exceptional coordination and continuous monitoring, something not required in Med 2.0. Health coverage, designed for a different era, has started showing its limitations in this new paradigm. The last 20 years have seen a significant shift, with the consequences becoming increasingly apparent.

If we compared the leading causes of death on 1900 vs 2000, the first thing we would notice is staggering progress. Within 100 years, modern medicine has extended our lifespan by approximately 40 years. The main contributor to this change is the reduced number of deaths from infectious diseases, which was the leading cause of death in the early 20th century. Now, chronic diseases such as cancer, heart disease, Alzheimer's, and diabetes are the primary causes of death. These four conditions - heart disease, cancer, metabolic disease, and neurodegenerative disease - generally indicate a longer lifespan. This progress, as it is usually the case, comes with its own set of new problems. In 1900, when people commonly died around the age of 50, disability was not a significant concern. However, as we've extended lifespans, the incidence of disability has increased dramatically. The impact of chronic diseases, which was negligible when people died at 50, is enormous if people can live longer. Half of all adults have at least one of these four conditions, a quarter have two or more, and they account for 86% of all healthcare spending. As a result, healthcare costs continue to rise.

The paradox is that we could reduce approximately 80% of these costs with our current medical knowledge. Organizations like the NHS, PAHO, or the CDC routinely and unequivocally confirm this. This is not a medical problem.  It is an information and coordination problem created by applying and old paradigm to a radically different problem.

What makes chronic diseases so unique that they require system adaptations? Firstly, acute illnesses are "noisy," while chronic conditions are “quiet”. For instance, can you imagine living decades with a broken femur? In contrast, one can live with diabetes or high blood pressure for a decade without noticing. If you're a doctor waiting for a patient to show up, it could take a long time. Secondly, acute conditions have a singular cause. For example, a virus causes the flu. Although your behaviors can marginally affect the conditions, they're not the primary cause. With diseases like diabetes, it's the opposite. Your behaviors are the main cause, with external factors playing a lesser role. Chronic diseases have multiple causes, necessitating a team of care providers working in sync over long periods of time. Since there's no clear enemy, constant vigilance is necessary. Most people can't have a doctor monitoring them daily, so self-care becomes essential. What happens when there are multiple, unclear causes, vague signals, and self-care is left to untrained individuals? Mistakes occur.

To illustrate, let's examine the example of diabetes, as explained by the Pan American Health Organization. Out of every 100 dollars spent in the disease, about a third represents the cost of managing the disease, including doctors, medication, and exams. If diabetes were similar to an infection, that would be the total cost. But it's not. People have to manage a complex regimen of measuring variables, making calculations, and typically using three or more medications. Eventually, they fail to control their disease and end up in an emergency room or hospital, represented by the yellow section. This doubles the cost of managing the disease due to patient mistakes. Over time, these mistakes accumulate, and patients develop complications like neuropathy, vascular disease, and retinopathy, which adds another third. Overall, poor management, information, and coordination triple the cost. It's not because we don't know how to handle it, but because the person who does is far removed from the problem, and the person close to the problem lacks proper training or information. This is why we say it's an information and coordination problem, not a medical problem.

Now let's consider the situation from the customer's perspective. Med 2.0 was relatively simple to distribute. It involves creating a health coverage system like an insurance plan. It's a one-size-fits-all solution with a single price. Just sell an annuity. Remember the Dallas Schools Teachers? They paid 50 cents a month for unlimited medicine. This model fits perfectly with the insurance industry's sales strategy, which is a widespread distribution system incentivized by the size of the premium and closing transactions. Today, we have brokers who earn a percentage of the premium and get a bonus for closing new accounts. Their focus is on selling high-priced plans and acquiring new clients. Since a new account usually comes from another company, brokers are also motivated to rotate clients among plans. This isn't an issue if your medical needs are temporary, but what if you have a long-term illness? As the system began to unbundle and require additional services, new players emerged. These include labor medicine services, benefits platforms, and more recently, telemedicine services and solutions for mental health, women's health, sleep, obesity, exercise, meditation, and so on. With the growing importance of data, analytics platforms also emerged. However, accessing integrated data is challenging. Each provider has its own data, and regulations hinder data sharing. Employers, who often act as organizers, are also not ideally positioned to convince employees to share personal data. For example, would you tell your employer if you were planning to have a baby, feeling depressed, or struggling with alcohol? Also, the analysis is extremely complex and dynamic. Even if data was available, developing models to deal with the complexity is no easy task. Specially if these models require specificity to the individual level. For the user, and her employer, to analyze and integrate this myriad of disconnected services, is virtually impossible.

Where is the incentive for the suppliers to collaborate and build personalized solutions when each one is trying to maximize volume without being responsible for the outcomes? Is it surprising that we can't orchestrate the system into a comprehensive solution?

Even if we could consolidate all offerings under one roof, as some insurance brokers are attempting, it would require more than that. The complexity goes beyond the supermarket model adopted by marketplaces like Amazon. It's not just about providing a one-stop-shop and transparent pricing. It necessitates the interplay of data analytics, a comprehensive understanding of prevention models, a continuous feedback loop, and most importantly, aligned incentives and a long-term perspective on the partnership model. This is a stark contrast to the short-term, transactional model prevalent today. The healthcare equivalent of “Amazon” cannot simply mirror Amazon's model. This is chiefly why, 30 years after Amazon's inception, we see its equivalent in nearly every industry, except for healthcare.

Axenya is our attempt to innovate the model from its foundation. We believe that merely being "better" is not enough in this market. Simply digitizing brokers doesn't solve the complex analytical needs or the existing conflicts between players. It demands a new type of player that combines elements of what a broker, a TPA, an analytics provider, and a remote monitoring player do, but organizes them in a fundamentally different way.

At Axenya, we offer two essential services. Firstly, a 3-dimensional marketplace-like care offering, allowing customers to customize a comprehensive solution. This solution includes financial risk tools like insurance and related products, population management products ranging from a digital operations platform to complex risk and population analytics, and individual care solutions with care navigation, AI-based coordination, remote monitoring, and personal health programs. Secondly, and perhaps more importantly, this selection is not simply a collection of unrelated tools. Axenya integrates data from all parts of the ecosystem, such as claims data, and patient-level data like wearables data, AI-powered face-scans, AI-powered questionnaires, and human intervention into a single database, permanently powered by AI and Data Science. This ensures appropriate choices at both the employer and individual levels, and then, continuous monitoring, detecting possible deviations from plans and implementing necessary changes at the individual and population levels.

This guarantees three things: customers have access to all the right tools they need, vetted and guaranteed from a single provider (us), they can make selections based on data and not marketing claims, and they get continuous monitoring, timely interventions and adjustments as needed, at the very beginning and at every single point as their care journey goes along.

In other words, we are building an 'Amazon' for healthcare, tailored to the unique needs of the healthcare sector.