When a team needs to reset its course

UBT realizes they can't meet their goal alone and works with other teams to improve patient experience

THURSDAY, DECEMBER 15, 2011 :: By Jennifer Gladwell

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Management co-lead(s)

Benjamin Hofilena, Benjamin.A.Hofilena@kp.org, 503-885-7363

Union co-lead(s)

Mollie Lucero, Mollie.X.Lucero@kp.org, 503-885-7331

Members of the Tualatin Medical Office Lab

When unit-based teams begin a project, they typically answer a series of questions using the Rapid Improvement Model: What is the problem? What do we want to accomplish? How will we measure it? How will we know if we are successful?

But what happens when a team starts out with a goal and finds out it can’t fix the problem alone?

The Tualatin Medical Office Lab in the Northwest found itself in just that situation. The team’s problem was not unique—patients come into the lab needing a test, but there are no orders in the system. The UBT’s goal was to reduce the number of patients presenting at the lab without orders to 10 per month.

The team collected extensive data for two months. It tracked the time patients came in, when they left, what their orders were for and where they originated. Team members noted whether the orders had expired or were missing from the system. The UBT created a database with these details and charted it by month.

Once it collected this sea of information, team members realized they couldn’t prevent patients from coming in without orders. The issue really originated in the modules.

“We noticed that the intent of reducing the number of patients presenting with no orders is really out of our direct control,” explains supervisor Ben Hofilena.

Now what?

The team still wanted to resolve this service issue for patients. It was a tricky situation—the patient is waiting at the desk while the phlebotomist searches the computer for a lab order to do the test. Coming up with nothing, the phlebotomist identifies who the provider might have been after getting information from the patient, and tries to contact that provider’s nurse. Meanwhile, the patient is waiting on the other side of the desk. It’s a tense situation for the phlebotomist and a frustrating situation for the patient.

It also became apparent as the team sifted through the data that it also was an affordability issue. Team members calculated that phlebotomists were spending about 12 hours a week looking for missing orders. If you consider an average wage of $18 per hour per phlebotomist, and labs in 21 locations across the region, that’s an expense of more than $18,000 per month.

Eureka!

The team took its data to the source and presented it to staff in the modules in the facility. Within minutes, a suggestion was made to have a point person take the calls from the phlebotomists in the lab and either enter the orders or work with the doctor of the day to have orders added. A backup medical assistant was appointed to cover when the primary contact is not available.

As of June 2011, the number of missing orders was down to 23 a month, compared with 37 missing orders in the baseline data. While the team hasn’t reached its target of10 per month yet, it continues to review the data and work on the issue. Patients are being taken care of on the spot instead of being asked to return.

The result? “I think our wait times are still there; however, the patient is happier with a resolution of getting an order and they are not having to leave the lab and come back later,” explains Lucero.

And it looks like their work is impacting service scores. Two services measures, “courtesy of lab tech” and “wait for lab test,” are reported by Press Ganey, an outside organization that measures patient satisfaction. In May, the scores took a nosedive. That same month, the doctor of the day and the medical assistant both were out for two weeks. Coincidence? Maybe. Or it could be that their work does impact the service level patients think they receive.

Hofilena isn’t waiting for definitive data before spreading the practice. The four other labs he supervises in the Northwest are in the process of collecting similar data or implementing similar changes to prevent patients from having to return because of missed lab orders.