How Big Data Can Identify At-Risk, Potential Patients

Marianne Aiello, July 23, 2014

Carolinas HealthCare System is using predictive modeling to identify high-risk patients who might benefit from preventative care. In Ohio, Dayton Children's Hospital is using Google products to target potential patients.

I've found, over the years, that many hospital CEOs are visual thinkers—especially when it comes to marketing campaigns. It's the CEOs who tend to push for that extra highway billboard or that additional magazine ad-buy; it's something they can glance at on their drive to work or flip past when they're perusing articles.

Of course, this penchant for the tangible can be problematic for data-driven marketers.

I recently came across a Forbes article listing ten things about social media and marketing that every hospital leader needs to know. The most important, in my opinion, is buried down in the eighth spot:  "Targeted, content marketing costs 62% less than traditional marketing, and, per dollar spent generates about three times as many leads. "

Those are some concrete statistics every CEO should be able to get behind. Here's a look at two organizations using targeted data to their advantage.

Targeting High-Risk Patients with Big Data
Patients in the Carolinas who use their credit cards to purchase junk food, cigarettes, or other unhealthy items may soon receive targeted advice from their doctors.

Carolinas HealthCare System, which has 900 care locations and 7,460 licensed beds in North and South Carolina, has begun purchasing consumer spending data in order to analyze purchases and anticipate patients' future healthcare needs.

For example, a patient who buys a lot of alcohol may be at risk for depression, a patient who eats a lot of fast food may be at risk for diabetes, and a patient without a vehicle registration may have a difficult time making it to scheduled appointments.

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