Is Big Data Causing a Big Brother System in Healthcare?
As we approach the landmark Supreme Court decision next month of whether Obamacare’s individual mandate for health insurance is constitutional or not, we’re seeing a move from health insurance companies, hospitals and pharmacy plan providers to cut costs with data analytics.
But there’s a looming question in all of this – is big data causing a big brother system in healthcare? Let’s explore.
What’s with All the Data?
Healthcare companies including insurers, hospitals and pharmacy plan providers have access to loads of data on their customers and patients, and they’re now leveraging that data to lower costs and project the future health of those individuals.
According to a recent article in the Wall Street Journal, “Several insurers including UnitedHealth Group Inc. and WellPoint Inc. are seeking to pinpoint who will develop conditions such as diabetes.”
In addition to using predictive analytics to see who may be a riskier patient, these companies are looking at data such as which patients go to the hospital most often and which of these patients will be readmitted, according to the report. With this information, the insurers and other healthcare companies plan to “adjust care” to “prevent such return visits.”
Does it sound a little like big brother? You decide. Let’s look at for/against arguments of this practice.
Are You Taking Your Medication?
This is a common question from your physician and now from insurers and pharmacy benefits management companies including United Healthcare, WellPoint, Express Scripts and CVS Caremark as well, reports the WSJ. The rationale is that if you don’t take your medication, they’ll intervene to “improve care and prevent further expensive health problems.”
While it does sound a bit like big brother, the predictive analytics and interventions companies like Express Scripts are implementing can help patients a great deal. Dr. Bob Nease, the chief scientist behind the program at Express Scripts, says they can predict noncompliance in about 90% of cases.
Typically, noncompliance falls into two categories – patients who forget and those who aren’t sure how to take their medications. These patients receive “tailored interventions” including calls from their pharmacists on setting up services such as auto-refill. Or if they can’t remember to take their pills, they receive timers on their medicine bottles that beep at the appropriate times.
Nease tells the WSJ that these steps increased compliance about 16% in the control group.
Watson’s Role in Predictive Analytics
We all know that Watson, the IBM supercomputer that beat humans in Jeopardy, has gone to medical school. His medical education and analytics abilities allow him to “suggest treatment options to doctors, based on medical records, research databases and other sources,” reports the WSJ.
The advantage: Machines can help doctors keep up with the latest research to treat conditions and diseases.
The Human Element
WellPoint, the company behind the Watson project, also relies on the human element to help patients with chronic conditions. Nurses and case managers are using data from patient records and claims to determine whether patients are “following doctor’s orders.”
Could this be the next frontier in data analytics – giving the clinical team access to advanced analytics tools to speed the research process on chronic patients and speed preventive care, which is much more cost-effective than pharmaceutical and surgical interventions?
According to recent research, it seems more patients are racing to make more reservations for hospital visits in the next year. We doubt it’s the exciting food and luxurious accommodations that are drawing them there. The reality is that more patients are seeking care and the costs to everyone involved (insurers, hospitals and patients) are skyrocketing.
The super hero who will solve this escalating problem? Predictive analytics. This mission is so critical to some healthcare providers such as Heritage Provider Network, a California-based physician group, that there’s a $3 million prize being offered for the algorithm that best predicts which patients will go to the hospital in the next year.
Health Management Associates (HMA), a 71-hospital network spanning much of the Southeast and a few other states, is also in the hunt for patient admissions analytics. However, this company wants to predict which services patients will demand in the future such as ER and lab. The firm’s interest is in ensuring adequate staffing.
Eric Waller, chief marketing and strategy officer for HMA, says that the industry can benefit from predictive analytics. He says, “We’re being incentivized as an industry to improve clinical care and increase satisfaction and improve margins with lower reimbursements. It’s driving people to be much more interested in the use of analytics.”
Big data is touching every aspect of our lives. And while data analytics in healthcare could seem a bit like big brother, the intentions are better treatment, lower costs and more prevention.
Next Steps: See how Spotfire version 4.5 empowers users to discover actionable insights hidden in big data and unstructured information in our upcoming webcast, “What’s New with Spotfire 4.5,” taking place Thursday, May 31 at 1 p.m. Eastern.
Spotfire Blogging Team
Other Posts by Brett Stupakevich
The moderated business community for business intelligence, predictive analytics, and data professionals.