Healthcare data analytics: turning data into innovation

Healthcare organizations have access to unprecedented levels of data and processing power, and urgent and complex questions to answer. But despite enormous investments in healthcare data analytics, most organizations still struggle to bring their data to bear on even their most important decisions. 

Why? And, most importantly, how do you get past the common roadblocks to success?



Healthcare is marching steadily from a volume-based system to one that seeks to answer daily the overarching question, “Are we delivering value?”

In other words, what changes will lead to better clinical, financial, and operational outcomes? Once made, are those changes having the desired impact, or do they need further refinement? And how do we accelerate this process of exploration, iteration, and innovation so that good ideas grow into productive solutions?

Integral to the ability to gain answers that are believable and meaningful is a data analytics infrastructure capable of informing emerging value-based models, solutions, and partnerships.

Here, we discuss hopeful progress in the development of these transformative healthcare data analytics.


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New cloud-based database management systems (DBMSs) are powerful and scalable, but it's hard to know which technology will best serve your organization's needs under realistic data processing scenarios, particularly if you're working with healthcare data.

Download our report now to find out which DBMS came out on top when we tested the most popular platforms.


Why is using data for healthcare innovation so difficult?

Water, water, everywhere,
nor any drop to drink.

These famous lines from “The Rime of The Ancient Mariner” have long been repurposed for the data world. But overwhelming volume is just one challenge organizations face on the journey from raw data to the right action.

Data quality and wrangling

With all of the buzz around data scientists modeling analytics and developing machine-learning algorithms, it’s still an accepted rule of thumb that 80 percent of a data scientist’s time is spent on gathering and cleaning the underlying data.

To achieve success with higher-level analytic projects, healthcare organizations must invest in and employ healthcare data solutions that streamline the preparation and maintenance of a rich, complete, and accurate data foundation.

The ability to leverage new data sources

Innovation increasingly means partnering with organizations outside your four walls. Providers and payers, payers and solution vendors … there are almost infinite combinations. New partnerships bring new data that help partners understand the population they co-manage, as well as new logic to govern the business terms. Interoperability standards may ease some of the burden of data exchange, but infusing these external data into the analytics that drive care workflows and decision-making is the greater challenge. Solving this requires deep collaboration between data professionals and business/clinical teams.

Data needs to meet FAIR data principles (findable, accessible, interoperable, reusable), but organizations still struggle with simple data sharing, which means the picture of care for any given patient or population will be incomplete. Data are typically assembled for a one-time use and not built for reusable, general analyses. And changing data standards continue to plague interoperability goals.


It is relatively easy to put a picture to a story you want to tell. Far harder is ensuring that the story informs the audience—that the components incorporate their view of the world enough to make it believable.

Analytics in healthcare are most successful when they accommodate the reality that everything is local, with each provider system, population cohort, geographic market, and more varying to some degree. Transparent and localized data models and rapid iteration between data and business teams build trust—necessary for the team to accept and act on results.

What’s needed

To leverage healthcare data analytics to drive real organizational change, a fresh approach is necessary: one that threads the needle between structure and flexibility while reorganizing stakeholders around a collaborative and innovative process. Download our healthcare data analytics manifesto to learn more.


New approaches to data-driven healthcare transformation

Healthcare, like all living things, adapts to thrive. Whether you are forming new partnerships, optimizing emerging models, or launching new services, you need innovation to grow.

The Ursa Studio analytics development platform transforms and accelerates the way innovation works. Watch our video to learn more.

HubSpot Video


Accelerate your build time with the Ursa Core Data Model:

  • A versatile, reporting-ready data structure intelligently designed to support all healthcare use cases
  • Easy data flow into development-ready tables that inform an extensive library of measures
  • Quick-start content modules in common priority areas

Then, accelerate customization with fully no-code technology:

  • Full transparency into every component of the data model
  • Full control of modifications that improve relevance and utility
  • No-code measure authoring to easily create and iterate
  • Centralized logic to streamline management tasks

Learn more about how Ursa Studio creates a strong yet adaptable structure for analytics-guided innovation and growth.


Unlocking successful healthcare partnerships with shared analytics

New partnerships are constantly forming in healthcare as risk-bearing organizations look to a growing number of companies offering products and services geared to deliver better health and financial outcomes for targeted groups of healthcare consumers. These partnerships are at the heart of value-based care and payment.

But they face a critical problem:

“The healthcare industry recognizes the importance of shifting to value-based care. However, the tools haven’t really been in place to help organizations execute innovative partnerships to deliver greater clinical and financial value. A primary challenge has been authoring the logical rules for the information that guides these partnerships.”

—Robin Clarke, M.D., CEO, Ursa Health

Read more about technology advances in the Ursa Studio analytics development platform enabling organizations to share and reuse logic, helping them collaborate more effectively. 


The seeds of Ursa's own innovation

Frustration is often a powerful motivator. For Ursa Health’s CEO, Dr. Robin Clarke, the practice of medicine, with its focus on the individual, sparked an additional interest in better organizing systems of care to support broader populations.

“I loved getting to know patients and their families, being able to see the immediate relief of symptoms or the way in which the delivery of information provided solace to people at a very important point in their lives. However, in many ways my care was reactive, not proactive. I felt like the workflow of picking up the chart outside the clinic door, seeing who was in the room, and then responding to whatever they told me was not the way for society to achieve optimal health.”

Listen to his story on this podcast, or read more on the Ursa Health blog.

Ursa’s two other founders, brothers Andy and Steve Hackbarth, share their personal stories on our blog as well.

  • Andy, Ursa’s Chief Product Officer, digs deep into the creation of Ursa Studio: the gaps it is meant to fill and how it fills them. You can read more here.

  • And then Steve, Ursa’s Chief Technology Officer, describes how he’d always followed his brother’s career with interest. So when he reached out in the summer of 2014 to say he was starting a company, Steve wanted to hear more. He talks about his decision to join his third start-up here.