As vice president of insights, I’m responsible for bringing my background as a clinician and my knowledge in healthcare IT and data analytics together to help both the company and our clients. Right now, that means I’m focused on helping Ursa develop standard measures sets, and then working with clients to build their libraries of custom insights to drive improvements within their organizations.
I’m a critical care pharmacist by training. I spent a decade at the bedside in ICUs, in cardiac surgery, and more, and I have taught other healthcare professions both didactically and at the bedside. I always strove to give back and have an influence beyond the patients I cared for, which typically occurred through teaching, research, and publishing around my sweet spots of complex hemodynamics, mechanical circulatory support, and applied pharmacokinetics, as well as other favorites such as anticoagulation, thrombosis, and hemostasis.
Although I enjoy that work, I began to think about and have access to opportunities where I could influence healthcare at a different level. First, I was able to help lead efforts to align the systems and operations necessary to jump into CMS’s Bundled Payments for Care Improvement initiative at one of my previous organizations. Through my successes there, I then led enterprise efforts into alternative payment models across multiple payers.
As I worked with all the stakeholders to put together those frameworks, it became clear that healthcare technology married to clinical operations was key to the ability to scale. I just kept seeing a bigger and bigger need for someone to come from the bedside to actively translate and inform the development that’s going on in this area.
I then joined the parent company of a large pay-vider organization as director of clinical transformation. I was often involved in navigating the muddy waters of claims versus clinical/EHR data, data integrity, and attribution, looking for opportunities to align payer and provider in new solutions. Often, the biggest obstacle was getting all parties to agree on the fact that there was indeed a problem to solve in addition to aligning on the respective roles of the parties in formulating the solution. Once we achieved a cohesive vision of healthcare delivery innovation, we could blaze forward with strategic initiatives, including a hospital-to-home program, clinical decision support development, and working to “quiet the chart”—getting rid of unnecessary alerts. I also represented the clinical arm of our interoperability strategy, with a focus on the tackling the administrative burden that utilization management brings.
At every organization, I aspire to make things better than they were before I arrived: better for my colleagues, my partners, and the people or patients we collaboratively serve. To do this, I continue to be a life-long student, learning how best to support alignment and cultural shifts among clinical and business teams as well as payers and providers—all by grounding this work in the foundational truths held in their own data. Fundamentally, this means building relationships around the same values, bringing new ideas while keeping it simple, measuring what matters (to each respective audience), delivering and iterating faster, and helping the healthcare system own the change it wants and needs to see.
To me, that’s really where healthcare is hung up. Payers, by way of HIPAA, are only allowed to see certain data. They can see what comes through on claims and whatever else they need to know to be able to authorize care and pay for a claim, but nothing more than that. From the provider perspective, I might do things clinically that are never going to be represented in a claim. Likewise, the risks and decisions that are made in managing patients are often underrepresented in a claim or in the data that arrives in front of the payer from the provider.
Therefore, it is not uncommon for payers to see variability in care represented in their claims data sources, and they can’t really delineate whether it’s appropriate variation in care that’s needed to manage a particular patient or if it’s inappropriate care variation where clinicians are just not adhering to standards.
I like to keep things grounded in the data, the facts we have in front of us. In my prior role at the parent company of the pay-vider organization, we could see and blend both sides of the data, payer and provider, which enabled you to ask very different questions. I personally feel that to transform healthcare, we have to start at the foundation, which is the language between providers and payers where we ensure that the data is translated and represented in a manner that is both clinically and operationally defensible.
That’s what really fascinated me then, and what still drives me now. In healthcare, we have to figure out how to do the right thing for the patient, how to keep it simple for the provider, and also how to ensure that payers put the right reimbursement model in place that doesn’t stifle efficient care but does minimize the risk of waste, fraud, and abuse. In the meantime, while those pieces are not aligned, you force a patient and a provider to potentially spend time on something that generates more wasteful activity than if you just let them do what they intended to do.
The classic example is this. Consider that the clinical guidelines written by professional organizations generally take three to five years to truly get baked into daily practice. All the while, payers may or may not keep up with these changes and their nuances, so the guideline recommendations aren’t reflected in their policies governing reimbursement, or there may be additional lag time before changes are made. This can lead to long phone calls, prior auths, and a bunch of other activities that may delay a patient getting care. In addition, it can cause unnecessary time and expense on the provider side that in the end just feeds the losing engine of administrative costs in that don’t really contribute to healthcare value.
This may sound pessimistic about the healthcare system, but what’s very exciting right now is that we’re at a critical point in the journey toward interoperability in healthcare in which data is beginning to be shared more readily. When data is shared, you can strip away opinions and start talk about the facts that are in front of you. That’s what really compels me in this space! We can then treat the system defects, like I treat a patient: define the problem; understand, analyze, and study it with data; establish your treatment plan; and optimize the therapy based on the response (i.e., based on data analysis). Simple enough, right?
I heard about Ursa through Aaron Mock, and it really tugged at my heart strings with its focus on healthcare improvement through data and data insights. Aaron and I worked together elbow to elbow for over a year when he was at a prior company and I was in my prior role. He had shared his change and the reasons for it, and we had kept in contact since he joined Ursa. Some of the things that Ursa was doing were just fascinating. If you look at what’s behind Ursa, what we’re tackling, and where the company’s been, I think it’s really successfully following its mission and the vision of what the founders wanted to do.
Ursa Studio starts with the right foundation, assembling and cleansing the data. It focuses on the right measures that help move a provider or payer organization to value, not just the standard metrics that are out there defined by the ecosystem. Different types of organization have different operational models, so although those external quality measures, for example, are good to have as a benchmark, in the end you really have to get into the weeds to define and measure the specific processes that contribute to your performance.
That’s what Ursa does. We’ve created a framework that allows anyone to look under the hood of what’s contributing to those leading or lagging measures, determine the contributors, and create a plan for tackling them. Ursa’s spent a ton of time on that framework, and I’m just excited to help shape its next steps.
A lot of people put a lot of time into a lot of things here. I’ve worked with other small companies in the past just as a partner, and even in big organizations this can happen: When someone has put in a lot of time and effort into something, it’s easy to get defensive about what you did and why you did it, and not be able to hear other ideas.
What I’ve found thus far is we bring people in from many different perspectives in healthcare and with difference experiences, and everyone keeps an open mind. There’s really a team here and collaboration around how we can do something, regardless of what was done in the past. We apply similar concepts internally as we hope to encourage in our clients because, in the end, the playbook is simple: We have to figure out what’s working, what’s not working, and how we can do better together.
By way of my paternal grandmother’s family, Ralph Waldo Emerson is a relative. I am a sucker for some profound, compelling, or motivational quotes, and he had a lot of them. Specific to the data and analytics domain is a quote that caught my attention recently from the late Senator Daniel Patrick Moynihan: “Everyone is entitled to his own opinion, but not his own facts.”
On the lighter side, if you asked my family, friends, and colleagues, I am known for dropping some “unique” Appalachian metaphors and colloquialisms from my West Virginia roots, which are always good for a few laughs.