• by Neil Weisman , May 21, 2013

Despite the fact that our world is becoming more and more digital, direct mail can still be an effective tool for healthcare marketing campaigns. It can be highly informative, easy to track, and often an optimal way to reach older populations that don’t use computers, smartphones and tablets as much as younger generations. 

Still, a direct mail campaign is only as good as its list, and finding an effective list is a key challenge for any campaign. When it comes to healthcare, many people do not opt-in to receive information about their diseases. Those who do are often inundated with mail, creating a low response rate. Since much of a person’s healthcare information is protected and out of the public domain, how can we expand our lists to reach to those who aren’t hand raisers for various conditions while maintaining HIPAA compliance?

Expand Your List

According to the U.S. surgeon general, 70% of diseases and medical conditions are lifestyle-based, or have lifestyle components. Thus, by looking at an individual’s lifestyle, it is possible to assess whether a person is at risk for a given condition. So, how do you “look at someone’s lifestyle?” Like it or not, there are over 2,000 publicly available data points appended to anyone with a credit history. And by analyzing trends in consumer spending data, you can make extremely accurate predictions as to the likelihood that someone has a disease. This process is called Lifestyle-Based Analytics, or LBA.

Unlike other predictive healthcare models that use claims data that is often outdated, LBA uses consumer spending data to arrive at its predictions. For example, if someone buys a pair of running shoes every six months, and also uses their credit card to sign up for a marathon, you can assume that they are a runner and live an active healthy lifestyle. In contrast, someone with high television consumption or large amount of fast-food purchases is more likely to have cardiovascular disease or diabetes. 

Using LBA to Reach Obese Individuals

In a recent cardiovascular outcomes clinical trial, we used LBA as one of 15 different tactics to identify and enroll qualified study participants. 

Using key study inclusion and exclusion study criteria, we created an algorithm using LBA that linked to consumer behaviors related to obesity, such as fast-food purchases, television consumption, health and fitness purchases, and alcohol or tobacco use. The algorithm was then applied to major consumer databases such as InfoUSA and Experian and each name in the database was indexed. The higher the index, the more likely they were to resemble the target patient population.

We used zip codes for all study sites on the trial to further geo-target and limited the radius to 15 miles in order to accommodate the visit schedule. 

Overall, LBA delivered more inquires and referrals than any other tactic in our integrated campaign and increased our response rate more than 400%. Compared to digital initiatives, TV ads, print ads and other tactics, direct mail delivered the highest share of randomized patients (40%) at the most cost efficient ROI.

LBA Is Here to Stay

While this example of LBA was used for a patient recruitment campaign, there are other important potential applications beyond clinical trials. 

• It can be used to proactively help someone before they’re officially diagnosed with a disease or medical condition, as opposed to reactively indicating a health issue after the fact
  
  
• Unique metrics such as “willingness to change” can be identified. If someone is known to have purchased weight loss training products or signed up for a dieting program, you can assume that they are open to changing their lifestyle, and more willing than usual to try something like a clinical study

While consumer spending data has long been used for marketing purposes across other industries, it is exciting to see how this data can now be used in the health care arena to give people important information that may help them lead better, healthier lives.