In healthcare there is an opportunity for better care through more and better information. Patients often assume that information flows around the healthcare system to support their care. But often patients are asked the exact same question five times. What are you allergic to? What medications do you take? etc. Because all patients don’t know the answers, having that data can improve care and care continuity.
As part of our series about “How To Use Digital Transformation To Take Your Company To The Next Level”, I had the pleasure of interviewing John D’Amore, the president and co-founder of Diameter Health.
Under D’Amore’s leadership, Diameter Health is becoming the standard for health data optimization, transforming raw patient information into the highest quantity and quality of interoperable data for healthcare organizations. The Diameter Health technology enables organizations that depend on multi-source clinical data streams, such as health plans, Health Information Exchanges (HIEs), healthcare IT, life insurers, and health systems. D’Amore has over fifteen years of experience providing informatics and strategic insight to healthcare organizations and is an esteemed thought leader and published researcher in field of health information technology.
Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
I have worked in health care my entire career. I like to joke that I’m a failed pre-med candidate who was supposed to go to medical school, but instead focused on undergraduate work in biochemistry and spent time shadowing physicians. They advised me to try something in health care and see if it scratches the itch to contribute to the field and improve patient lives, well-being, quality, and efficiency of care. So, I started out in health care consulting. I did that for several years and then joined the largest nonprofit health care system in Texas at the time, Memorial Hermann, and worked with large datasets and got down into the weeds of dealing with health data and trying to make sense of it all. I came to really understand the ins and outs of how medical information is recorded, how doctors and other clinicians think, and how to put that information together in a rational and easy to use way. That experience led me to the field of informatics, which is where I got my graduate degree. And those experiences focused me on being able to make health data actionable, accessible, and universally organized.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?
After my wife and I had our first child, which is now six or seven years ago, I was sleep deprived and often travelled to conferences without having a full night’s sleep. Everyone forgets something while packing occasionally. But I was scheduled to speak at a major conference where I arrived late the evening before and needed to present early the next morning and I forgot to pack dress shoes or any appropriate shoe wear. The only store open early that morning was a Target and the only footwear I could find were black slippers.
No one noticed my slippers at my big presentation. There’s always a solution available to a problem if you look hard enough!
None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story?
Certainly, my academic advisor for my graduate studies, Dean Sittig, is one person I consider as a mentor and I continue to publish and work with him today. At Memorial Hermann, Dr. Michael Shabot was another mentor and the CMO for the health system. He was an inspiration for his willingness to dive headfirst into data. And I’d say that, what being a doctor means has historically been organized around the art of medicine, where you learn the craft by doing an apprenticeship- which is what a residency is. And even though it’s a craft driven by science; the actual execution is not necessarily rigorously scientific. By that I mean, the way you learn to diagnose a patient isn’t by reading a bunch of peer review articles, it’s by doing it over and over. And Dr. Shabot had an incredible passion to use data to inform decisions and illuminate trends in an organization that would not be evident, would not be clear, would not be possible to see as an individual doctor treating a patient. He was the inspiration for me to get my graduate degree in informatics.
I also encourage others to take the leap into health care data. It’s immensely complex. But even though it’s complex, it doesn’t mean it is impenetrable if you are willing to put in the time and the effort. You can find meaningful things within health care data that can inform improvement of care quality and the ability to operate more efficiently.
Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?
I recommend anything written by Atul Gawande; certainly, his Checklist Manifesto. He is a physician with incredible skills not related to the practice of medicine. He can express ideas, concepts and a world view in vivid language using great stories. Fundamentally what the Checklist Manifesto says is we should use a checklist because it ensures that we operate as part of a system rather than as individuals. Humans are error prone, whether we are 90 percent accurate or 99 percent accurate, we cannot be a machine. But we can incorporate systems to protect against potential faults.
Extensive research suggests that “purpose driven businesses” are more successful in many areas. When your company started, what was its vision, what was its purpose?
Our vision has always rotated around a common core: that we could see the pain that poor quality data had on professionals (and also on their patients) who besides providing medical care are tasked with developing reports, analytics and quality measurements.
Initially, I thought we’d use data standards and then develop apps to empower those downstream analytics. But the more we got into it as a company, we found that the core of the problem was just being able to make the data usable. It was the hardest thing to do and it provided the most value because — and IBM and other companies may not want to hear this- when you have clean data, writing a good algorithm to predict something like readmissions or patient acuity is not that hard. It’s really hard, though, when you don’t have clean data.
Instead of addressing the root cause, the industry often tries to compensate for poor data in odd ways. For example, statistical techniques we’ve had for decades, like logistic regression, perform exceptionally well on clean data. But they perform badly on poor data. So, we invent new techniques to try and cover up for the poor data instead of fixing the data. You can apply machine learning and neural nets and get a model that might be half as good as a logistic regression model using clean data. Because neural nets allow for more dynamic interaction between variables, they deliver some of the effect of cleaning up the data. But operating on clean information from the outset delivers better results.
Are you working on any new, exciting projects now? How do you think that might help people?
We have peer reviewed research in the final stages on more effective quality measurement through the use of digitally transformed data in EHRs, and new approaches to look at patient data longitudinally to deal with the fragmentation of data across multiple systems supporting different clinicians documenting care in different ways.
Ultimately, we say we’re “counting a belly button” in quality reporting- that is, we’re evaluating whether a person received the right care based on their consolidated health records. Was their hypertension under control? Were their diabetes and glucose levels managed appropriately? Did they get the right cancer screenings that year? When you think about reporting from a belly button perspective, that’s not how patient data is stored. And we’re working on some really innovative research with some of our clients to be able to bring data together on a consolidated basis to enable better population health, quality measurement, and analytics.
Thank you for all that. Let’s now turn to the main focus of our discussion about Digital Transformation. For the benefit of our readers, can you help explain what exactly Digital Transformation means? On a practical level what does it look like to engage in a Digital Transformation?
Healthcare is one of the largest and most complex industries; it represents nearly 20% of the nation’s GDP. But it requires years of training and the accumulation of a tremendous amount of knowledge. It’s the ultimate knowledge industry in some respects. There is a lot of complexity that needs to be documented about medical care. And historically, that complexity prevented health data from being truly electronic and digital and liquid, as we think about the bits and bytes and being able to transmit data with meaning from point A to B.
Consider the use cases that were first to go digital, like banking, credit cards, and email. The complexity of medicine defies the definition of a simple transaction. It’s not just ordering a pill. It’s about ordering a pill for a condition diagnosed through certain lab results as evidence, due to the presence of certain symptoms, that has evolved over a series of encounters over time. And the clinician is trying to craft a plan of care around all that. It doesn’t consolidate to a single number. It is a complex, interwoven set of concepts in medicine. So, it was one of the last industries to become digital. About ten years ago, the Meaningful Use legislation as part of the Affordable Care Act introduced EHRs (electronic health records) to the wider industry. That was Wave 1 in the digital transformation of healthcare.
But I believe the more significant effect of digital transformation will take place in Wave 2. As you look at the evolution across industries, the most common Wave 1 transformation is taking what you were doing in one mode and transforming it into a format that you can deliver digitally. Only after that, do you begin to do things that you could have never done before had you not had all the digital inputs to that system. And that’s really what we are seeing right now in health care, where we can aggregate and analyze patient information in ways that were not possible when you had 10 or 20 different paper charts spread across different practices, health systems and hospitals.
And that is really the opportunity of a digital transformation; to do things with the support of computers that would have been impossible on paper.
Which companies can most benefit from a Digital Transformation?
It’s the companies that aren’t in health care today that desperately want to be and should be in health care. Digital transformation is going to enable companies that have been long circling the health care ecosystem, like Microsoft, Google, Amazon, and Big Tech in general. Ultimately, it will no longer be just a human making decisions about a patient, but a human enhanced by computer power. We often confuse the future with what we see in sci-fi. The first evolution of computers that fundamentally digitally transform medicine are not going to be through a computer like IBM Watson diagnosing a patient. It’s going to be a clinician who now has the insight at their fingertips to do things they never could have done alone.
What I see in the next 10 years is computers that are no longer looked at as an ancillary part of performing medicine, but as a critical component to performing enhanced medicine; just as physicians wouldn’t perform surgery without anesthesia and the right tools.
We’d love to hear about your experiences helping others with Digital Transformation. In your experience, how has Digital Transformation helped improve operations, processes and customer experiences? We’d love to hear some stories if possible.
While the future is here, it’s not evenly distributed. And I am reminded of the collaborations that are evidence of what’s coming in the near future. We are working with the state of Michigan and an organization called the Physician-Payer Quality Collaborative. They have payers, physicians, and health systems all at the same table planning how they can bring data together to enable quality measurement in ways that weren’t previously possible.
We have peer reviewed research coming out in a few months showing that, within a given year, 80 percent of patients visit more than one health care organization. That level of fragmentation requires us to create innovative ways to bring data together and organize it meaningfully. When you have an app that aggregates data from multiple banks or credit cards, it’s pretty easy to process the credits and debits and unify that information. However, when you consider the complexities about how allergies, immunizations, medications, problems, and procedure data are recorded, being able to organize the data within a common infrastructure in a way that makes sense to a clinician (as well as a patient) is challenging.
And we see that happening in the state of Ohio every day. We export thousands of consolidated patient records for providers to deliver more informed care. We also empower the largest health plans nationally to connect to health information exchanges and to providers natively to inbound data so that they can use it for appropriate quality measurement. And then consider the next step in terms of empowering consumers. We’re working with several major health plans to light up the consumer app ecosystem by providing data through APIs.
Has integrating Digital Transformation been a challenging process for some companies? What are the challenges? How do you help resolve them?
Consider the complexity of medical vocabularies and how data is documented. There are only about 8,000 medications that can be prescribed to a patient. But if you count the number of codes for those 8,000 medications, they number in the millions because we have different terminologies. We have medication codes called RxNorm, and NDC that’s put out by the FDA, Multum, First Databank, Micromedex, Medi-Span; all these legacy systems that refer to medications. Organizing that complexity to answer a simple question like, which medications is this patient on? and what medications are they on for diabetes? is tremendously complex when you deal with millions of inbound codes and formats of that data, which can include uncoded free text.
And that is what we enable; we optimize the data so that it can be put in a query format to perform effective analytics; not just for medications, but also for laboratory results, problems, procedures, vital signs, social history, allergies, encounters and immunizations.
If you remember the ad campaign from the chemical company BASF, that’s fundamentally what we enable for our clients. We don’t provide the analytics, but we make the analytics better.
Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Use Digital Transformation To Take It To The Next Level”? Please share a story or an example for each.
First, in healthcare there is an opportunity for better care through more and better information. Patients often assume that information flows around the healthcare system to support their care. But often patients are asked the exact same question five times. What are you allergic to? What medications do you take? etc. Because all patients don’t know the answers, having that data can improve care and care continuity.
Second, being able to use that data effectively to monitor the efficiency and the effectiveness of care. I’m really zeroing in on digital quality measurement here.
Third, is to reduce the cost of care; for example, avoiding duplicate tests. We can avoid doing unnecessary tests and procedures with better access to the right information.
Fourth, to use the data captured during the course of care for advanced analytics, predictive algorithms, machine learning, and uncovering insights that we would not have observed otherwise. As one example, going back to the early 2000s, Vioxx, which was a popular medication for arthritis, was found to cause heart attacks which wasn’t evident in the original clinical trials, but was found through data that took researchers years of effort to confirm. I look forward to a future where insights like that happen interactively and, on the fly, to reduce the time between threats being introduced to the system and our ability to detect them.
Fifth, enabling patients and caregivers to access their own data more easily, conveniently and securely to take a more prime role in their health care.
In your opinion, how can companies best create a “culture of innovation” in order to create new competitive advantages?
The critical factor is passion and a vision for what you want the company to be and then recruiting people who share that vision. Not everybody, but a lot of people, want more than just a job. They want to have a reason that drives them to jump out of bed in the morning. And the biggest thing about innovation isn’t a creative personality or your logo colors. It’s the “blood, sweat and tears” that you and your team are willing to put into the cause. And you can’t pay for that. You have to inspire that behavior.
Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?
A quote that’s been influential in my career is from Gandhi, “If we could change ourselves, the tendencies in the world would also change. As a man changes his own nature, so does the attitude of the world change towards him. We need not wait to see what others do.”
Sometimes we don’t have the option of joining an organization to do what needs to be done. You have to go out and do it yourself. I changed myself into an entrepreneur for Diameter Health.
How can our readers further follow your work?
You can follow me and Diameter Health at
- Twitter @DiameterHealth
- LinkedIn at linkedin.com/in/jdamore
Thank you so much for sharing these important insights. We wish you continued success and good health!