Patient Experience, Social Media, and Analytics

On Sunday, I spoke at the Cleveland Clinic Patient Experience: Empathy and Innovation Summit on a panel about social media analytics. It was an honor to be asked to speak at such a prestigious event.

My co-panelists were Jeff Rohrs from ExactTarget, Debra Beaulieu from Fierce Practice Management, and Lance Hill from Within3. They were a fantastic panel, and it was an inspiring event. It’s not every day you get to speak in front of a room full of smart, forward-thinking healthcare professionals invested in improving and innovating within the patient experience.

The topic, though, was a bit challenging. It’s not too great a challenge to connect the dots between customer experience and patient experience, and between social media and analytics. But to tie all of those concepts together was a bit more ambitious. Here are some quick thoughts recapping some of what I had to say.

People who work in healthcare are used to thinking in terms of outcomes measurement. This is handy, since marketing has had a major movement in the past few years towards ROI and accountability, and the thinking here is easy to align. Measurement in terms of patient experience could be thought of in terms of minimizing negative outcomes, such as a reduction in errors, or in terms of maximizing positive outcomes, such as increasing referrals. And there are some subtle differences between marketing efforts focused on revenue growth and those focused on cost reduction.

When you think about marketing, it’s easy to relate to the classic marketing funnel:

awareness > consideration > preference > purchase > loyalty

This is the milestone progression as seen from the company or institution point of view. This is easy enough to measure and optimize, and this is certainly an important set of measures. But it is also critically important to think about an experience funnel from the patient point of view and determine how to measure that way. Put in these terms, some measures will be qualitative, and measures of qualitative experience are usually proxies or approximates, but they’re better than not measuring at all.

In terms of how social media analytics relate to the business marketing funnel, there are some commonly accepted analogs. A “purchase,” or some conversion or success event correlates to a goal action. This is typically an event that results directly in revenue or the opportunity for revenue, or in a risk reduction process, the opportunity to conserve costs.

Consideration or preference correlates with engagement and influence measures. Bear in mind that most people indicate that they are online to participate in activities that fit within learning, socializing, and having fun. Efforts to drive engagement should be conscious of these participant goals.

And awareness, at the top of the funnel, is associated with online reach, such as allowing the patient to self-educate through web media, social media, etc.

Next we can think about how to draw lines between the company funnel perspective and the patient funnel perspective.

On the patient side, we may propose a framework where the funnel progresses from learning (about a disease, condition, etc.) to empowerment (being able to make educated choices, select appropriate treatments, facilities, etc.) through active involvement (the ability to be heard, select an effect treatment, etc.) and reaches, hopefully, success (of being on the right side of treatment with a reduction in symptoms and overall satisfaction in the experience). Of course it’s not always a rosy picture in healthcare, but this is what we’re considering the intended path from the patient perspective.

Clearly, this funnel consists of fundamentally difficult things to measure. And when measuring difficult things, we rely on closest approximations, quantitative analogs to qualitative waypoints, and results-based or outcomes-based measurement.

But that leads us to the concept of differing kinds of metrics groups. The stars of the metrics universe are Key Performance Indicators, or KPIs, which are part of even the most basic analytics program. But some KPIs are measures of events that take a long time, and there may be events that happen along the way that predict positive outcomes in those KPIs, and so we may use earlier indicators, called Key Leading Indicators. But I propose that there may be another category of measures, too: Key Experience Indicators, which may be more esoteric but which can be used, along with KLIs, as directional feedback on the projected success of a program over the long term.

There was more, but hopefully you get the picture. I’d love to know your thoughts in the comments.

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