By Philip Wickline, Co-Founder and Chief Technology Officer, Zus Health
LinkedIn: Philip Wickline
LinkedIn: Zus Health
For all of the technological advancements that have unfolded in healthcare over the past several years, one relic of the past still seems to sum up today’s patient experience.
The clipboard.
It’s a potent symbol of just how much responsibility and redundancy healthcare providers continue to thrust onto patients when it comes to gathering and sharing data.
And it highlights one of the biggest issues in healthcare today: While a lot of data is available, very little of it is being used to directly improve patient care.
Think about it. Pharmaceutical companies, research organizations, and doctors themselves all use data to develop, study, or test new treatments. But for the patient at the point of care, it’s the same old story: “Take this clipboard and fill it out.”
Using and sharing data more efficiently can help redefine the patient experience and deliver more longitudinal care that follows a patient throughout their life. Day to day, this would involve…
- Closing care gaps and adjusting patient risk assessments.
- Proactively following up on acute transitions in care.
- Managing specialist referrals and medication regimens.
But making the shift to longitudinal care has been a struggle. Here’s why, and how practitioners can facilitate change.
Why Healthcare Data Is So Hard to Use
Historically, hospitals and other providers have struggled to translate patient data to better patient care, and particularly to longitudinal care. But it’s not their fault. Often, they don’t have the tools to merge data from the many sources they access. In other words, they lack interoperability.
It’s understandable. They’re working with fantastically complicated data that applies to a fantastically complicated subject, the human body and how it works, which makes an already hard job even harder.
The average primary care doctor setting up their own practice, for example, probably doesn’t have the know-how to integrate themselves into a nationwide network of providers. As much as they might want to take advantage of technology and data to deliver better patient care, it’s just not their specialty.
And those individual doctors aren’t alone.
A Tall Task: Bridging the Data Divide
The goal of the healthcare system should be a more longitudinal care model, one in which data allows providers to follow their patients throughout the care process. Unfortunately, that’s not where we are today.
Right now, there are huge amounts of data available from a wide array of sources, national and state health insurance exchanges, prescribing networks, lab networks, to name a few, all of which have only a partial view of a given patient. As a result, the system lacks normalization when it comes to describing patient conditions, prescriptions, lab results, etc.
For example, a hospital may use one system with a specific set of codes to describe a patient’s issue. Meanwhile, a specialist may use an EHR that describes the same condition with a completely different set of codes. Even if the primary care doctor is connected to both of those sources (not always a given), figuring out how they relate to one another is nearly impossible.
That leads to the question at the heart of this data divide: How do you summarize data from dozens of networks into something that’s relevant for the patient at a particular moment in time? The answer involves gathering all of that data and normalizing it, de-duplicating it, and interpreting it.
If that sounds like a big job, that’s because it is. And that’s why providers are struggling to do it.
Data Interoperability Can Lead to Better Patient Outcomes
The healthcare world, of course, isn’t unique in this dilemma. Siloed and fragmented data is a problem across many organizations and industries.
But healthcare providers have more data, and more complicated data, than most of their peers. And the practice of sharing that data is often centered around things that aren’t directly beneficial for the patient, like processing an insurance claim.
A shared national data platform, on the other hand, would allow every provider and organization to see a common patient record at the same time. No lags, no diversions, no silos. In other words, a data ecosystem built around the patient, not the provider, one that would lead to better patent outcomes.
Building such a system, however, requires a few key things:
- A shared vision: It can’t be overstated, normalizing healthcare data is a massive job. That’s why most people have shied away from it. And it’s why any breakthrough will require intense coordination and a shared sense of purpose among all participants.
- Trust and transparency: It doesn’t get much more sensitive than healthcare data, which is why safeguards, accountability, and transparency need to be built in across every stage of any shared system. And as AI continues to become a bigger piece of the puzzle, reliable tracking and linking to source material will be even more important.
- Patient focus: Above all, every effort has to be grounded in a desire to provide better patient care. That means paying close attention to the nuances that could impact outcomes, and giving doctors everything they need to plan the best course of treatment.
Advanced Insights = Better Patient Care
Imagine a system that allows a primary care physician to review standardized notes and summaries from a patient’s hospital stays, lab work, specialist visits, and more, all in one place. Wouldn’t that make for a more thorough and streamlined continuum of care for the patient?
That’s the promise of data interoperability in healthcare. It’s not about cutting services or processing insurance claims. It’s about using advanced data insights to deliver a better care plan for every patient.
And, ideally, to kill the clipboard once and for all.