Joe’s haircut is darn ugly. What are effective ways to persuade Joe, or other people and organizations, such as healthcare providers, to make improvements? One way is to issue orders, but that only works if you’re the boss. Another way is to reliably predict a bad outcome unless improvements are made, as in the case of budgets, health, safety, etc. Yet another way is to teach how to improve on a specific key measure, which can work if people or organizations are self-driven.
It’s often pointed out (e.g., in this Harvard Business Review article) that people are motivated by peer comparisons, which are effective because it’s human nature to notice others and be influenced by them, and because the comparisons are easy to grasp: Your Peer does better at X, and X is important, so try to measure up! But a comparison to a single Peer is subject to the defensive reaction that the Peer has very different circumstances, so the two aren’t comparable!
I wish to put forth a way to make peer comparisons that are arguably persuasive, but rare. People seldom think of them and they are hard to come up with without the help of automated comparisons of available data. These peer comparisons are characterized by a second measure, Y.
Consider telling Joe this comparison: You have the ugliest haircut of everybody as good-looking as you! Notice that you are implicitly using two measures: (1) haircut ugliness, and (2) good looks. The peer group is everybody who is at least as handsome as Joe. Within this elite group, unfortunately Joe does the worst. On the one hand, Joe feels good about his comparison group, and on the other hand, he has the worst outcome, assuming he cares at all. And the peer group is large, unless Joe is stunning!
Now, for you logician readers, let’s acknowledge that “Joe has the ugliest haircut of everybody who is as good looking as him.” is absolutely equivalent to “Joe is the best looking of everybody with such an ugly haircut.” But psychologist readers will agree that the first version does better at motivating performance improvement, since a likely human reaction to the second version is “Well, at least I’ve got something going for me!”
It turns out that automated experiments with healthcare or business data turn up a large number of such peer comparisons. Here are three actual, but anonymized, insights taken from various healthcare sectors at BenchMine.com:
1. A California hospital has the lowest communication-about-medicines rating (2 stars) of the 358 hospitals with as high an overall patient rating (5 stars). Those 2 stars compare to an average of 4.3 stars across the 358 hospitals.
2. In the Southwest, a Texas home health agency has the fewest patients who got better at getting in and out of bed (19.1%) among the 1,651 home health agencies with at least 49.1% of patients who got better at walking or moving around. That 19.1% compares to an average of 65.3% across those 1,651 home health agencies.
3. A Pennsylvania nursing home has the most short-stay residents who had an outpatient emergency department visit (34.1%) among the 317 nursing homes with at most 10.1% of short-stay residents who were rehospitalized after a nursing home admission. That 34.1% compares to an average of 9.8% across those 317 nursing homes.
The basic “shaming” message is this: Why are you so bad at X if you’re so good at the related measure Y? Everybody else with such a good Y is doing better than you! Of course, the world is filled with such potential insights, although coming up with verifiable ones may best be done with rigor by software, as long as data can be collected and analyzed.
Instead of merely ordering Joe to get a new barber, presenting him with a book on hairstyling, or predicting that his love life is doomed unless he improves, let’s try pointing out how poorly he stands out as compared to his wonderful peer group! The same goes for Doris the hospital’s chief quality officer, Nancy the home health agency’s chief nurse, and Mary the nursing home’s director.