Guest Article: What Jenny McCarthy can teach us about behavior change and data

Home > Guest Article: What Jenny McCarthy can teach us about behavior change and data

As all you probably already know, I’m a follower of healthcare startups and am a sucker for new ideas and smart people. I was recently introduced to Joshua Rosenthal, Ph.D. and when I found out he’s a Fulbright recipient whose work focuses on behavior change I knew I had to get him to share his thoughts about how IT can help. He recently worked with a small team creating clinical facts systems and data architectures for a disease management company with about 20 million members and a multi-dimensional database for a large health plan, tying together disparate data sources (service center calls, web sessions, claims, lab, Dartmouth Atlas, census, consumer/commercial marketing data, etc.) at the member level to give a single customer view and segment populations according to attitudinal, motivational and behavioral attributes. In their current start up, Sprigley ( ), they are creating an application that allows a “smart conversation” to entertain people as they become more engaged in their own health and wellness, to find personalized resources and to create a valuable data asset for their lifelong care. Dr. Rosenthal knows this stuff cold — here’s his guest article.

Eat eggs, don’t eat eggs. Drink as much wine as you possibly can… don’t touch a drop. Take hormone replacement therapy… avoid it like the plague. Get your childhood vaccinations…avoid them, they’re associated with autism. Oh by the way, be sure to choose the physician with the best outcomes. Don’t forget to comparison shop your health insurance benefits – etc. – etc. – etc.

One of the problems with paternalistic approaches to behavior change is that the “parents” often disagree. People loose confidence in conflicting messages and that is especially damaging when the messaging asks someone to do more and more (here’s a lump sum, go find a high deducible plan). Even if you try and segment by attitudinal, motivational and behavioral attributes, at the end of the day telling people to do something or avoid something doesn’t really work.

Even when people believe that something is beneficial, there is a personal gap (fill in favorite academic term here) that prevents action. I know I should eat better, exercise more, join a DM or health coaching program. Behavior change’s devil, like so many others, is in the details. What type of exercise, what type of nutritional changes, how do I incorporate them into my daily life, and arguably most importantly, will they work for me?

Solution. Ask people what motivates them. You know what motivates you best. You know what works for you best. What you’re likely to do, what you’re not. Then aggregate that data. Create a community with a data backbone – give people their own lifelong data asset and the tools to interpret it – aggregate observational data.

Lights flip on. Cameras roll. Oprah is doing her thing. Celebrities and children with autism. Doctors offering theories based on literature from differing schools. Paternalistic overtones galore. Finally one frazzled parent stands up and say, in effect, “Hey, you guys are not taking us parents seriously and we’re the ones with millions of hours of observational data.” Show blows up – spins off other shows – lights up You Tube. Pent up demand to contribute. Jenny wanted to see what other parents with similar children did in her situation, what are the top five things they need to know? Show her and her child compared to their peers when facing decisions and show the outcomes of those decisions and you have her.

Not just her, anyone faced with behavior change. Have back pain? Think about surgery or chiropractic treatment – 45% of people “like you” chose A and 15% reported success – 55% chose B and 75% had success. Why don’t you shop your data out and see what responses you get? Hey, Joe coach potato – the vast majority of people like you who tried this exercise program had really good success, even when they were initially hesitant. That’s gold. Decades old in financial services but revolutionary in health care.

Um, yeah, sounds great. As long as we’re at it why not sundaes that are good for you and never-ending weekends? How, exactly, to we get to this fairy tale? Google, Amazon, Yahoo, Microsoft and their likes creating lifelong data assets for consumers that the consumers control.

Um, but haven’t plans tried that with Personal Health Records and they’ve never worked? Yep, but people hate their plans and don’t trust them – why volunteer incriminating information. And they will change jobs and employers every couple of years so they don’t bother.

Okay, but where does the data come from? Physicians groups, one-click requests from individuals to their plans, and self-reported data (speaking from experience, we can create models from self-reported data that rival and even exceed the predicative power from claims-based models) and the web companies will incentive individuals to self-report.

But it can’t be that easy! It’s not. You need a data standard and some serious plumbing that’s accessible via an API. But you already know the web companies are doing that. To find people “like me” you need some multidimensional databases that can give a single customer view – and that is tough. You also need an integrated fact system to interpret the data and profile individuals clinically, attitudinally, motivationally and behaviorally and that’s years of research. You also need a user-friendly application sitting on top of the web companies API and giving a great consumer experience.

Jenny, here are the top five things people like you and like your child think you need to know. Here is what they’ve chosen, here’s how that’s worked for them. Here’s where to sign up.

Jenny, keep an eye out for the web companies in the next few months.


Shahid N. Shah

Shahid Shah is an internationally recognized enterprise software guru that specializes in digital health with an emphasis on e-health, EHR/EMR, big data, iOT, data interoperability, med device connectivity, and bioinformatics.