Using Online Data to Predict Patient Behavior

wheelchairPredicting the future ain’t what it used to be. In fact, it’s more real than ever. Social media. Big Data. Predictive Analytics.  These are big buzzwords, to be certain, but also keys to helping your healthcare system or hospital to provide better and more efficient patient care.

There are times in our lives that we wish we had that crystal ball. Picking breakout stocks or NCAA upsets is great, but imagine having insight into the future based on real data. And imagine that insight being actionable. That data can impact your healthcare system directly and help you reach more patients efficiently.

No need to imagine any longer.  Your crystal ball is here with healthcare predictive analytics.

Every one of your potential patients leaves a tremendous digital footprint.  They search Crohn’s disease, arthritis treatments or dementia care. They talk on Facebook about living with diabetes. They tweet about migraines and join forums to learn about concussion prevention.

And you, as a healthcare marketer, can use that data to anticipate patient needs, prepare your staff and provide better care.  Here’s how:

A variety of off the shelf tools can gather and analyze online conversations around keywords. Google and third party tools can track search volume. By marrying this data with your own historical data, you can then start predicting patient needs.

Here are a few examples of how online data can help your healthcare system or hospital.

  • Online conversations and searches around concussion injury tend to spike during the fall high school and college football season.  If you know that come November, your patients and prospective patients are hungry for information around concussion prevention, you can offer workshops, clinics and online information around the topic when it is most sought after.
  • Conversations around back and knee injuries often spike over Thanksgiving. As the dads and uncles take the backyard football games against the teenager, injuries are bound to happen. What can you do to anticipate this and offer tips, services or flexible appointment options in the days leading up to, and just after, Thanksgiving?
  • Bariatric conversations grow in volume and intensity during the holiday season and beginning of the new year.

Too obvious for you? How about these examples:

  • First, analyze the historical volume of conversations and searches around consumers talking about or searching on flu like symptoms. Then map that trend line to documented flu cases. It is very likely that the online information is a leading indicator of flu cases.  By monitoring online activity you can then anticipate the next flu outbreak.
  • If a local TV or radio celebrity takes up a cause, say breast cancer awareness, you can track the rise in local interest in mammograms and offer extended hours at your women health centers.
  • Suppose you find that weekend warriors in your area are active online during the first nice days of the year and lamenting how their old knee injuries prevent them from running.  You can make plans to heavily promote your runners’ clinics on social media and PPC advertising platforms during that first nice weekend in spring.

The days of guesswork around understanding patients are behind us. Using real data from real patients and understanding it in real times allows us all to provide better care more efficiently for our communities.

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Check out our study of the competition health systems face in paid search.

Health Systems & Paid Search

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