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Blog   |   1.14.19

Healthcare’s Great Data Problem

Healthcare's great data problem

The U.S. healthcare system has a major problem—but it’s not what you might think.

When most people talk about how healthcare is broken, they focus on the outrageous cost of prescription drugs and medical devices. They talk about a lack of access to affordable healthcare and good doctors. They rant about rapidly rising insurance premiums and long wait times.

While all these problems are very real, there’s an underlying issue that, if resolved, could have a profound effect on the cost and quality of healthcare. That issue is data. Healthcare professionals aren’t able to effectively mine the plentiful data that’s already been captured about their patients’ conditions, risk factors, and prior treatments.

Healthcare’s data problem is pervasive, complicated, and costly—to the tune of billions of dollars a year. By finding efficient ways to mine the available data, providers and health plans will be better prepared to address other issues such as poor quality, rising costs, care gaps, and lack of access.

Why does healthcare have a data problem?

Each year, over 1.2 billion clinical documents are produced in the U.S., and this number is growing at a rate of 48% per year. That’s a ton of data. Unfortunately, 80% of that healthcare data is sitting around in unstructured formats and locked away in myriad Electronic Health Record Systems (EHRs). This unstructured text is largely unused in the provision of care, but often holds valuable information about how a patient was feeling, their past or family medical history, and other issues and conditions not related to their most recent visit.

Another contributing factor is the burden of documentation placed on clinicians by Electronic Medical Records (EMRs). While EMRs are great in theory, in practice, providers must dedicate a significant amount of time—up to half their working hours—to maintain accurate information. Even when EMR data is correct, it isn’t easily searchable or shareable between healthcare organizations.

When doctors don’t have access to all of their patients’ existing information, misdiagnosis and redundant treatment is common. This affects patients on both a financial and personal level—they’re paying more but receiving lower quality care. And health plans are on the hook for covering these ineffective services, which contributes to over $750 billion spent each year on unnecessary treatments.

The biggest consequence of these data issues is that millions of patients aren’t receiving proper care. When clinicians don’t have the right data, patients don’t get the services they need or the right treatment plans to deal with the medical issues they’re facing. This isn’t just a money issue—it’s a life-threatening problem that can only be solved by changing the way healthcare data is managed and used.

A three-part data problem

There are three parts to healthcare’s data problem: access, processing, and insights.

Access. Medical professionals don’t have access to the patient data they need at the time of treatment because it’s too difficult to access. Patient data lies within paper charts, electronic records, and other sources. These sources are often incompatible, which makes it nearly impossible for clinicians to access a patient’s entire medical profile. This leads to wasted time, duplicative care, inefficient patient visits, and misdiagnosis. It also prevents payers from effectively managing risk for their patient population. As a result, members often aren’t routed to the appropriate care intervention programs, which has a negative impact on their health and medical costs.

Processing. It’s expensive and time consuming to manually process unstructured data. Traditionally, healthcare companies have had to rely on humans to read charts and pull out data for quality measurement and risk adjustment programs. This process leaves organizations at risk of incomplete or inaccurate data.   

Insights. Medical professionals often don’t have access to the necessary insights to make accurate diagnoses. As a result, patients aren’t getting the care they need, they aren’t getting better, and they’re forced to come back to the doctor to re-evaluate their condition and treatment plan.

The solution to healthcare’s data problem

What if providers and health plans could achieve complete access to all that unstructured healthcare data? What if they could process it efficiently? What they had the insights they needed to care for patients properly?

Correcting these three issues would save time and money, allow doctors to spend more quality time with patients, and eliminate the waste that’s been plaguing the healthcare system for years. If we put all this data to use, we could create accurate patient profiles that would allow us to deliver truly personalized care. This would allow for:

  • Earlier identification of medical conditions and appropriate intervention
  • Quicker remediation of care gaps for existing conditions
  • Fewer misdiagnoses and unnecessary treatments
  • Lower costs to treat each patient
  • Healthier patients, happier clinicians, and more effective health plans

How can we make this vision a reality? Given the sheer volume of healthcare data, we can’t rely on medical professionals and coders to unpack it all. To transform this data into a usable format and glean insight from it, we need to turn to technology.

AI’s role in healthcare

The answer to healthcare’s data problem— lies in artificial intelligence and machine learning. With artificial intelligence, plans and providers can quickly and accurately mine patient records to inform care management and risk adjustment. AI will allow healthcare companies to take on what is currently a time-consuming and virtually impossible task, which will ultimately allow us to:

  • Process and validate healthcare data faster and more accurately
  • Analyze data and create individual care summaries
  • Create accurate and actionable insights from care summaries
  • Give medical professionals better access to more accurate data so they can spend more time with patients and drastically reduce misdiagnoses
  • Reduce healthcare waste, improve patient access, and drive down healthcare costs

We’ll dive into the details of how AI can help unlock the power of healthcare data in our next article. Sign up for our mailing list to get the piece delivered to your inbox.

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