Health Catalyst entered the life sciences space because we strongly believe that the three major entities in the U.S. healthcare industry—life sciences, healthcare delivery systems, and insurance—need to collaborate more effectively to lower healthcare costs while simultaneously improving care. I’ve said for years that an enterprise is never integrated until its data is integrated and leveraged for analytics. Integrated, shared data is a proxy for trust—and all parties must establish mutual trust before they can share and integrate data for a common interest. In this case, that mutual interest should be patient outcomes (i.e., lower costs and higher quality of care).
As an enterprise, U.S. healthcare is a mess, in large part because there is essentially no trust between the three entities, leaving the data and analytics among the three parties also a mess. It all boils down to patient data at some level, with patients suffering because the three entities can’t get their trust and data acts together. Hoarding is the norm, as if the data belonged to the corporate entity. In reality, however, as an artifact of patient care and clinical trials, data belongs to the patients and should be fully leveraged on their behalf.
In addition to our data management and analytics capabilities, Health Catalyst has two other cultural brands we cherish and will never forgo—patient outcomes and trust. We are entering the life sciences space to bridge the data and trust gaps between healthcare delivery systems and life sciences, particularly pharma, to benefit patient outcomes.
U.S. healthcare can’t keep operating in the separate and selfish worlds of the three Ps: payers, providers, and pharma. Health Catalyst has no interest in tarnishing our brand by being yet another patient data profiteer among the three. Frankly, that’s repulsive to our culture. We are applying common sense and human decency in pursuit of lower cost, higher quality healthcare for all of us. If we maintain that motive of better, more affordable care, business profits for everyone will naturally and fairly accrue.
We will never sell patient data. That’s a short-term market anyway. Data is becoming a commodity. It’s the analytics derived from that data, combined with the cultural willingness to take action on the insights, that spells long-term success. We are building a brand with a 50-year vision for enabling the mental, physical, and emotional fulfillment of human life.
Someday, the Health Catalyst brand will be associated with athletic and academic achievement and the selfless charity of human spirit. Someday, patients and physicians will both say, “Let’s see what Health Catalyst has to say about your condition.” As a step on that journey, we will integrate deidentified patient data with pharma data and leverage the analytics insights to improve patient outcomes.
The buzz phrase in pharma is real-world evidence (RWE), but that RWE is based on clinical trials. Guess what? Clinical trials are not the real world of patient lives. Real-world evidence comes from real-world patient care, and that’s where Health Catalyst lives with our current client base. Bringing life science and providers together is a fundamentally important step in our 50-year vision.
Make no mistake about it—we are not blind to the distrust of the pharma industry and how some might see our entry into this market as shaking hands with the devil. I read a recent Gallup survey that ranked pharma and life sciences at the bottom of consumer trust. Only the federal government was lower. But someone who is trusted needs to at least attempt to bring the parties and data together.
As a country, we can’t keep operating in healthcare like we are now. Healthcare costs are crumbling the economy and underlie much of the economic disparity and social unrest that exists today. Call us naïve. We don’t care. We’re going to try and make a difference. We will not engage in this life sciences market unless it raises our brand of trust and patient outcomes. If our entry looks like it will tarnish our brand, or even begin to, we’ll exit.
At a tactical level, when I was leading the data warehouse at Intermountain Healthcare in the late 1990s, I collaborated with several pharma companies to better understand the post-market safety and effectiveness of their drugs. They paid to cover the analytics services and technology fees. They learned while we learned, and it all rolled back into better patient outcomes.
This collaboration was unprecedented at the time because EHRs and healthcare data warehouses essentially didn’t exist. But I could see that, by partnering with pharma rather than distrusting them, our local community of patients and broader society would benefit. I did the same thing at Northwestern, and I’ve consulted on similar initiatives in Canada and the U.K. I taught graduate-level classes at Northwestern on the legal and ethical issues of data, analytics, and decision support in healthcare.
I’ve spent thousands of hours in this space, debating and pondering the pros and cons of integrating and analyzing deidentified patient data versus not doing so because of patient privacy issues. As a former Air Force officer and analyst for the NSA tasked with protecting the country’s most sensitive data, I can assure you, we can protect the privacy of patients. Don’t let the fear mongers convince you otherwise. Our deidentified healthcare data has enormous societal value. Contributing de-identified data for clinical and healthcare operations research is the digital equivalent of donating blood and organs for the benefit of others.
More than privacy, patients and the public—that’s you and me—should concern ourselves with the economics of this data. If we share our data with healthcare providers and pharmaceutical companies, then we should expect to benefit from the economic value of that data through lower healthcare costs and improved outcomes. The economic value of our data should flow back to us, every time we have a clinical encounter.
If corporations profit more from our data and analytics than patients do, we should protest in the streets. By endorsing the use of our deidentified data for analytics purposes in a fair economic model, we are helping ourselves, our families, friends, community, and country. We all stand to benefit. Let’s hold the corporations involved accountable for that benefit.
A particularly passionate area of interest of mine is associated with “small n,” or rare, diseases. I’ve seen firsthand the impact of diseases like multiple myeloma, ALS, and hemangiopericytoma and pediatric diseases like Ehlers-Danlos syndrome can have on patient lives and their families.
In the U.S., we spend a disproportionate amount of our time and money on chronic diseases, many of which are largely lifestyle driven. At the same time, we turn a relatively dismissive eye toward the total societal impact of rare diseases that have nothing to do with lifestyle choices. The patients and families who suffer from rare diseases did nothing by choice to acquire them, and yet their lives are often devastated.
The ripple effect in our economy and social fabric from small n diseases is much, much bigger than the population of patients who are diagnosed. If we don’t bring together the trust and the data from life sciences, insurance, and healthcare delivery to address these rare diseases, we should hang our heads in shame as a country.
While there is certainly value in addressing the pandemic of chronic disease in the U.S., our entry into the life sciences market is particularly motivated by our passion to improve the diagnosis and treatment of rare diseases. We want to enable breakthroughs. Someday soon, I want Health Catalyst to provide direct-to-patient analytics and AI so that all patients, particularly those with rare diseases, can query our databases to learn more about patients like themselves:
Unlike the many data profiteers in healthcare, it’s time for a trusted brand with proven expertise to take a different run at collaboration—as an advocate for the patient, not the corporation. What many companies don’t understand is that if you align yourselves to the purest motive—in this case, human health fulfillment—corporate success follows naturally. By bringing pharma and providers together through analytics as a trusted intermediary, we can improve clinical trial design and execution, stimulate clinical innovation, support population health through medication adherence and health economics and outcomes research, reduce pharmaceutical costs by optimizing prescribing and adherence, and improve drug safety and pharmacovigilance. And that’s just the beginning.
Would you like to learn more about this topic? Here are some articles we suggest:
Would you like to use or share these concepts? Download the presentation highlighting the key main points.