In the first step I made the argument that most of the dissemination of data around patient scores to all level of stake holders is vague and worthless. Knowing that your doctors are in the 57% percentile tells you nothing about what you’re doing right, what you could do different and better and what you should be doing next.
The only way to know what to focus on is to know more about less. Is the challenge in your ER younger females at night, or medicare patients on the weekend? How do different people perceive the quality of the food and the cleanliness of the room? When you know what you’re doing right, that is where and with whom the scores are high, and where you fall short, and should focus attention, you can act intelligently.
And acting with intelligence is the next step. When you’ve done due diligence with the data – and I can tell you with certainty that almost nobody has – can you “take it to the streets” and begin the execution of an improvement strategy.
This step is best understood with an example. A couple of years ago I worked with an ER on the east coast. Their overall scores were terrible – bottom quartile, very little good news. The director of the department of 40 years was racking her brain at what to do next to improve – they did everything stupid on earth – rounding, scripting, phony smiles and every other gimmick – and they were worse off than when they started.
When I began to dig into the data I uncovered some interesting things in the first few minutes. When the demographics were taken apart, there was a single time of day, and single demographic that led to patient disengagement. In fact when I pulled out the time of day, and profile of the patient in question the scores jumped into the 87th percentile and became one of the best ER’s in the state.
Now, before I go on I want you to consider something. If there was a single VERY dissatisfied demographic, that means that almost every other demographic was not only pleased but delighted with the care they received, would that affect how you approached patient satisfaction? Put another way, only one small part of the patient mix was “broken”, yet this hospital spent hours, days, and weeks thinking up strategies to improve the scores of all patients – does that make sense? It’s absurd – why fix what is not broken – most patients – the vast majority, most of the time were raving fans – but the data and how it was displayed and interpreted only showed a failing ER. Sound familiar?
So, pray tell, what is that single time of day and single demographic that served to drag down the scores of the whole department? Females, between 19 and 35, between 11 pm and 5 am.
With that we will ease into step 2. Take it to the streets. When I presented my findings to the director, she did what almost all of us would do. She started making guesses as to why that patient and that time was an issue. But I ended the conjecture and said “Let’s ask the team.” And we did.
That night we pulled together a group of late night nurses and techs – between 19 and 35 and told them what we found. The response was stunning – and here is a summary:
- Women that age coming to the ER at that time have to be really sick – otherwise they would wait until morning.
- Many will have children they will need to bring along.
- The parking lot is dark and scary – and depending on how busy the ER is it can be a long walk.
After a few more questions we discovered the following:
- The department did not have diapers available for patients to use for their children.
- Also no formula, bottles, mats for a nap or a babysitter for when mom had to go for a scan.
- Nearly every third shift nurse was a male.
Let me take you for a moment back to the worthless report you get every millennium from your quality person. Does any of this stick out as obvious? In fewer than ten hours working with the data and the team we figured out the disengagement of the lowest scoring customer. Dude?
Working with the team a number of things occurred:
- A sign was placed above the entrance offering valet parking after 9 pm.
- The department was stocked with diapers, formula, a breast pump, coloring books and crayons, and sleeping mats.
- The entire ER team was made aware of the scores and given ideas for sensitivity to this important, but vulnerable patient.
Although a good start, it is not finished. The leader, that is the director did a daily lookup in their patient scores to query how this patient at these times scored the ER and posted the results in plain sight. Every night shift began with a short 5-10 minute huddle on how the team would accomodate younger women with children and make them feel more comfortable and at home.
You guessed it. The peeling away of the data, the daily discussion and the accountability to the results turned the ER scores around. Being sensitive to a hurting and scared patient became second nature for this team. The problem wasn’t everyone, or everything the staff did – it was one type of patients that the data did not reveal, without knowing to look.
Then step three began – “Lather, Rinse, Repeat.”
We’ll talk more.