Alice and Bob are back. Previously, they each needed to buy cars. Now it’s health care. They each must find a medical group for their primary health care. We will see how their preferences matter.
Luckily, Alice and Bob live in a part of the country where a ‘data pooling collaborative’ exists. This is an organization devoted to measuring the performance of health care providers, health plans, and other players in the industry. Alice and Bob live in Washington State and their collaborative is the Washington Health Alliance.
When they were shopping for automobiles, Alice and Bob relied on consumer websites that evaluate various models. When it comes to medical groups, the Washington Health Alliance is their objective source of trusted, neutral performance data.
As with cars, Alice and Bob have different preferences. We give each of them a Preference Survey to see how their Preference Profiles differ – and which medical groups rate best.
The Washington Health Alliance collects data from health plans and employers to measure performance using methods approved by its multi-stakeholder board of directors. For medical groups, there are more than twenty performance measures available. We can organize the measures into four groups, or attributes, that Alice and Bob each will consider in selecting a medical group:
- Prevention (screening for diseases)
- Disease care (treatments for diagnosed conditions)
- Wise use of services (avoiding unnecessary treatments and expenses)
- Experience of care (how other patients perceived care delivered in a doctor office setting)
As they learned when shopping for cars, Alice and Bob found it quite difficult to judge with precision and confidence how the intensity of importance varies among these dissimilar attributes. Fortunately, we can help Alice and Bob discover their relative preferences by using the Preference Survey. Brief, simple, and non-mathematical, the survey detects both the priority and relative importance of preferences across multiple attributes.
Here are the results from Alice’s Preference Survey:
We can see that Alice place a large premium on having a good experience of care (52%). Expertise in prevention and disease care together account for nearly the rest of what matters to her (44%). Alice is least interested in practices that strive to keep costs low and avoid unnecessary services; wise use of services is about one-tenth as important to her as experience of care.
Now for Bob’s Preference Survey results:
For Bob, wise use of services is what matters most to him (55%). Moreover, he has a much weaker preference for experience of care than Alice does (23%). Prevention is roughly half as important to him as disease care. Bob’s results tell us, among other things, that wise use of services is about seven times more important to him than prevention.
There is nothing odd about such differing Preference Profiles. Alice is exemplary of what we might call a surveillance and treatment mindset, while Bob represents those who believe that less can be more when it comes to health care. We might even imagine that Alice’s health plan is rich with benefits and shields her from bearing the costs of care; in contrast, Bob’s plan might carry a large deductible and oblige him to share in paying for services. With personal preferences, there is no right or wrong; each person draws on his or her personal knowledge, experience, and unique circumstances.
Now let us turn to the Value Ratings for medical groups, recognizing that Alice and Bob have sharply differing Preference Profiles.
A Value Rating is a personalized composite measure; each Value Rating is a single number that lets you rank complex choices from most to least desirable. Although Alice and Bob are fictitious, the Value Ratings below derive from real performance data developed by the Washington Health Alliance; they regularly publish results on their dedicated website, www.wacommunitycheckup.org.
Below we display how actual medical groups in Washington State ranked for Alice and Bob, given their differing preferences. In this illustration, we have coded each medical group with a letter.
Although derived from identical underlying performance results, the summary rankings for Alice and Bob differ. This stems from their differing Preference Profiles.
Take a closer look at Medical groups Q and B. They are middle-of-the-pack options for Alice; however, for Bob, these two choices could hardly be more different. To Bob, medical group Q’s Value Rating is more than double that of medical group B. The reason: these two medical groups performed very differently in wise use of services, the attribute most important to Bob. Alice placed little importance on this attribute, so her rankings tone down the performance disparity between these two medical groups.
This illustration, using real performance data for actual medical groups, confirms the shortcomings of static, one-size-fits-all rankings, Top 10 lists, and other inflexible approaches. Without accounting for individual preferences, we can easily mislead when we intend to inform.