How Data-Driven Entrepreneurship Is Changing the Healthcare Market

Updated on February 24, 2023

Flatiron Health, a U.S.-based healthcare technology startup, has made searching for data on cancer patients a thing of the past. The company’s staff of medical experts and software engineers have created a platform called DocSearch, which aggregates patient data so that doctors, pharmacists, research institutes and others can easily find everything from pathology reports to faxed records. 

Flatiron’s search engine will not only make cancer treatment more efficient, but also more personalized. They’re providing a technology infrastructure that will boost collaboration among medical experts and make it easier to identify trends and best possible treatment options. 

Indeed, data-driven entrepreneurship, like what’s happening at Flatiron, can transform the healthcare industry in amazingly positive ways. In fact, big data solutions just may be the key to making healthcare more effective, less costly, and safer.

Given its potential, it’s imperative that every player in the healthcare industry pay attention to how new data solutions can benefit them. So, let’s dig deeper into how data-driven entrepreneurship will change the healthcare market:

Data-driven solutions have tremendous potential

Big data is a focal point for most healthcare companies. An incredible 95% of healthcare CEOs say they’re exploring better ways to use and manage data, according to a PwC survey. This is largely because of the potential for big data to streamline healthcare tasks and improve patient outcomes. My own company, The Allure Group, has a data analyst on staff for this very reason. 

As a guide published by George Washington University notes, technology is revolutionizing modern healthcare, as “entrepreneurial-minded healthcare professionals are applying predictive data and analytical tools to anticipate healthcare needs in a community, ensure care is adequate and necessary, and make statistical predictions about the care that will be required next.” Additionally, advanced data models are “exposing and correcting inefficiencies” and making the whole system run more smoothly. 

One major company that’s had great success with data management and analysis is Mercy Health, a U.S. provider that serves millions of patients across the Midwest. Partnering with SAP, Mercy carried out a business transformation centered around intelligently deploying big data analytics. Leveraging the SAP HANA platform, physicians and staff are now able to analyze eight years’ worth of data in the same time it took to previously analyze two weeks’ worth of data. 

This obviously has benefited Mercy greatly. Within the first eight years of implementation, they realized $65 million more in revenue thanks to improved clinical diagnosis and documentation, as well as cut nearly $10 million in costs by analyzing data to find best surgical practices. For patients suffering from pneumonia and heart failure, the mortality rate at Mercy is now half the national average. 

Unfortunately, not every company has had the same success as Mercy. That same PwC survey found that only 36% of healthcare companies have come to grips with how big data should be utilized. A gap still exists. 

Closing the gap and making the most of big data in healthcare

Time doesn’t stand still in medicine. Healthcare organizations certainly understand this deeply. What works best today won’t be the best option tomorrow. You have to move with the times—or else competitors will win the future. 

This is part of what makes the gap between grasping the importance of big data and realizing its potential so frustrating. What’s exactly holding medical companies back from unleashing the potential of big data? 

Well, it’s really a mixture of a few things, including: 

  • The speed at which technology is progressing: 57% of CEOs are worried that they can’t adequately keep up with the pace of innovation. 
  • Lack of focus on what to do with data: As Laura B. Madsen, a healthcare business intelligence expert, attests, “stop thinking about data as either our salvation or our end,” as data is neither good nor bad. “It’s what you do with it that matters.” Many companies simply don’t understand how to best use all the information they have. 
  • Data silos and inaccuracies: Claudine Beron, Vice Chair of HIMSS’s Clinical & Business Intelligence (C&BI) Committee, believes data silos are one of the biggest issues in healthcare. Researchers, physicians, and others simply can’t do as good of work for the patient when they can’t readily access all relevant data. When data silos exist, it also makes having conflicting or inaccurate data much more possible. 

For healthcare organizations, it’s worth making the investment to remove these obstacles and implement the latest big data solutions. This requires not only a cultural change to get everyone motivated to transform the way things are done, it also requires a commitment from HR to hire the talents that know how to work with big data. 

Healthcare companies most likely can’t achieve this alone, though. They’ll need to collaborate with agile innovators who have the best new approaches for employing big data in healthcare. This is where data-driven entrepreneurship can step in and move healthcare organizations forward.

Big data startups can build a brighter future for healthcare

MoneyBall Medicine, a book that details the emergence of big data in the healthcare market, argues that having the right data, along with the willingness and know-how to use it, will be key to future success for healthcare firms. The authors note this is why big data healthcare startups launch every week—they’re filling an unmet need and solving pressing problems in the industry with big data. 

You don’t have to look for to see the impact data-driven entrepreneurship has had over the past decade or so. Just look at these amazing companies: 

Lumiata: creating more relevant plans and treatment

Lumiata, a California-based startup, delivers real-time predictive analytics using machine learning and predictive analytics. This enables insurance carriers, hospital networks, and pharmaceutical companies to provide higher quality care and cut down time and costs. 

One great innovation Lumiata has built is its Risk Matrix. This solution creates high-quality stratified chase lists so providers can formulate better plans. Research on the Risk Matrix’s capabilities has shown it produces more accurate assessments of enrollees and then implements more accurate risk adjustments. The platform also gives healthcare providers access to more patient data and the ability to continually analyze and update plans. 

Ambient Clinical Analytics: making decisions more accurate

Ambient Clinical Analytics has stepped up to address the issue of data silos in healthcare. What Ambient Clinical Analytics has developed is a software program that brings together disparate data through easy integration with current systems. The program features algorithms that mine data from electronic medical records, offering doctors and nurses a powerful analytics tool for making decisions in real time. 

Top healthcare networks have improved patient outcomes with Ambient’s tools. For example, Mayo Clinic began using the company’s AWARE Sepsis DART™ software platform, an advanced ICU data display, in 2014. Thanks to the tool’s error prevention feature, surveillance capability, and decision support, Mayo Clinic reduced overall ICU and in-hospital mortality by 7%, while also reducing length of stay by 50% and cost by 30%. 

Medopad: making earlier detection possible

Accumulation of more data could save lives. Just look at these findings: 

  • A mere 18% of people know their body mass index and only 38% know their blood pressure, a Cleveland Clinic survey found. That’s alarming when it’s widely known heart disease is the number one killer.

Big data has the ability to get more people in-the-know about their condition. Medopad, a UK-health startup, is employing mobile technology to collect more data on patients and send information to healthcare providers in real time. The team has made an app that easily integrates with mobile devices. The app uses machine learning to analyze patient data, giving doctors the chance to detect life-threatening medical conditions much more quickly—and treat them before anything bad happens. 

Data-driven entrepreneurship in healthcare is just what the industry needs

A report from McKinsey sums up the big data revolution in healthcare nicely. As the consulting firm states, big data can accelerate value and innovation in healthcare by doing the following: 

  • Encouraging better living through targeted disease prevention and engaging people in their own care (like what Medopad is doing)
  • Ensuring care is not only based on evidence and tailored to the individual, but also that the treatment setting and medical provider are a proper match
  • Reducing costs while improving outcomes and enhancing the patient experience
  • Boosting the productivity of research and development of new medicines and treatment

Without a doubt, data-driven entrepreneurship will be vital to making certain we can unlock all the benefits of big data technologies. The key to that happening is first a willingness of major healthcare networks to embrace this new frontier. Second, a sustainable entrepreneurial ecosystem, like what Mayo Clinic Ventures aims to achieve, must be developed in order to ensure new ideas and players can grow and prosper. 

If those two things can happen, there’s no telling how far data-driven entrepreneurship can take us. All I know is it will definitely be a future where we live longer, happier, and healthier lives.

Joel Landau is the founder and chairman of The Allure Group, a network of six New York City-based skilled nursing facilities. He has also served as a member or an advisor on the Medicaid Managed Care Advisory Review Panel (MCCARP), NYS DOH Preventative Health and Health Services Block Grant, NYS DOH Task Force on Long Term Care Financing, and the Brooklyn Chamber of Commerce.