Charna Albert
October 2019—As payments to laboratories decline and labs look for costs to cut, drawing on Lean and CAP 15189 know-how is the path to stronger productivity, workflow, and quality, “and all of that is eventually going to help,” says Mike Black, MBA, MT(ASCP), DLM, laboratory assistant VP of Avera McKennan Hospital and University Health Center, Sioux Falls, SD, and Avera laboratory service line administrator.
Black joined Avera Health in 2012, three years after the Avera laboratories became the first hospital labs to earn CAP 15189 accreditation. They have since been assessed four times to the ISO 15189 standard and are the longest accredited CAP 15189 hospital laboratory.
“Lean initiatives produced a solid foundation for ISO 15189, and ISO has enhanced our Lean initiatives,” Black told CAP TODAY in an interview. Together they are helping the labs “cut costs, boost productivity, and support quality gains throughout our integrated health network.”
In a presentation at this year’s Executive War College, Jessica DesLauriers, Avera McKennan lab quality and education manager and quality functional leader for the Avera laboratory service line, tallied some of the most recent savings and process improvements stemming from the use of real-time data analytics.
Before DesLauriers’ team began using Visiun’s Performance Insight, a real-time data analytics tool, they had been trying to tackle the problem of misplaced specimens for more than a year. “And we were meeting maybe once a month because that’s how long it took to gather the information,” DesLauriers said. Her team wanted staff to begin reviewing the data daily, but to do that, “we needed it at their fingertips right then and there,” DesLauriers said. “Prior to real-time data analytics, my QA team was spending a good chunk of their morning trying to pull this data because receiving quality data from the LIS was too cumbersome.”
With the data tool, on the other hand, they knew they could build queries and have staff enter the correct information in order to automatically pull a daily misplaced specimen report.
“So we built that. We said we want this report by 6 AM every day, and now our staff can drill down in real time what happened to that specimen,” she said. “And it actually turned out that a lot of times we hadn’t misplaced it. It was the system in our LIS that we needed to tweak.” They were able to figure out that they were hunting down specimens they thought made it to the lab but did not.
From July 2018 to January 2019, DesLauriers and her team reduced by 76 percent the number of specimens mistakenly categorized as misplaced, saving 35 hours a month and more than $40,000 in hard costs. They also increased patient and employee satisfaction, she said, “because [our staff] no longer have to hunt for specimens, take angry phone calls, or make that phone call that says, ‘Hey, we can’t find this.’” As of August this year, the project had saved Avera Laboratories $75,000.
Even after a project is completed, DesLauriers continues to send regular analytics emails to department staff. With any process, she said, “sustaining is the hardest part.” And continuing to evaluate effectiveness is critical. “We use long-term reports to see if we made changes, how those changes are going, were they successful, and did our countermeasures hold strong,” she said.
Her team has found a more efficient way to ensure compliance with Gen.55499 and Gen.55500, two requirements in the CAP laboratory general checklist that call for each individual to have training and be evaluated for proper test performance.
“At first, our education team was going through the competencies, they were pulling Meditech reports, they were compiling all the data to be able to prove, if CAP walked in the door, that we did not have techs verifying results before they were proven competent,” DesLauriers said.
With the real-time data analytics tool, the lab “found a better way. We used our tool to be able to report by tech ID. So every time they were done with competency, in that area, our education department simply had to pull the result based on what area they were in and filter it using tech ID.” Automating competency reports, she said, has reduced by 52 hours per year the amount of time it takes the education department to fill out employee competencies.
In 2017, the Avera system decided that new employees would receive blood draws for TB testing rather than skin tests, she said, with all the TB testing across the system sent to the main laboratory. When the lab had to reject samples, new employees were held back from starting by about a week. “When you’re trying to cut costs and you need a new employee to start, the last thing you want is us to call you and say, ‘You have to redraw,’” she said.
“So we put a Kaizen together, and we built a report for TB testing. We are able to see why specimens were getting rejected”—mostly because tubes were overfilled. They dug further to see who possibly at the other labs was responsible, “to see if it was one person. By no means are we casting blame,” she said. “We just want to provide better tools. What can we do? Can we make more visual cues, better instructions, better training?”
[dropcap]A[/dropcap]nalytics has made it easier for the lab to sharpen test utilization and to zero in on hemolysis in the ED—and in general to build its reputation for quality.
“We had voiced for a while that we felt the C. diff test was being overutilized,” DesLauriers said, and in February this year, the medical decision support department reached out to the laboratory. Using data analytics, DesLauriers’ team began generating reports on test ordering practices for C. diff by PCR.
“The first report showed the total number of C. diff by PCR ordered that week, and the percentage of positives versus negatives,” DesLauriers said, citing one week in which 393 C. diff tests were ordered with only a 16.54 percent positive rate. “This painted a very visible picture that we had an opportunity to improve the utilization of this test.”
In addition, the lab gave the medical decision support department a report of the hospital’s C. diff testing that could be sorted by physician group and patient unit. “This helped medical decision support go to the units that were doing well to learn best practices, and to share those best practices with the groups that needed improvement,” DesLauriers said.
In response, the department began inviting the lab to ongoing meetings to share thoughts on how the C. diff initiative could be improved. This was “a big win for the hospital as well as the patient,” she said.
To address hemolysis, the lab generates a hemolysis report for the emergency department, providing it with the tools needed to determine “which nurses could use more assistance learning best practices to prevent hemolysis.” In the process, the lab built a relationship in which “the ED trusts us enough to come into the department and give their nurses tips and tricks on how to improve,” DesLauriers said. “Hospital departments are constantly asking us to come to the table now, and they’re always impressed with how quickly and reliably we can pull data.”
Pre-real-time analytics, laboratory staff manually pulled turnaround time data from Meditech at the end of every shift. “They would have to make sense of the report, and we would require that they circle anything that was outside of our goal,” DesLauriers explained. With the real-time data analytics tool, TAT reports are generated automatically and sent to staff by email twice a day.
Staff can “very easily make sense of” the Visiun report format, Black says, noting reports can be modified to fit whatever metric or measure a laboratory is trying to meet. His team designed the TAT report to also generate an outlier report, aggregating “everything that did not meet our turnaround time goal.”
DesLauriers said the outlier report is used to drill down to root cause. “We added barcodes to the report because that helps us get more specific about what happened with that specimen. It’s about designing it so you have meaningful data.”
Reports also include a comment section that has been helpful in determining the root cause of above average TAT. “If the shift has already left . . . I’ll pull out the outlier report, and our staff has become so good at being proactive and using the comment section, I don’t have to take the risk of trying to find them a couple days later and hoping they remember what happened,” DesLauriers said. “Maybe they had a hard time getting ahold of the nurse so they couldn’t verify out that report right away, or maybe there was something going on with that instrument. Majority of the time I can figure that out with the comment section, which also helps in our daily management of drilling down to the root cause.”
For TAT goals, “we used to go by average,” Black says. “We wanted to raise the bar. We wanted to meet the targeted turnaround time 90 percent of the time,” he says, citing as an example hemoglobin, which has a TAT (received to verified) target of 13 minutes. Using daily management and Lean techniques, and with the aid of the real-time data analytics reports, “90 percent of the time our patients are [now] receiving an 11-minute turnaround time” for hemoglobin. “Our average TAT is 6.6 minutes. There is a big difference between an average TAT and meeting your target 90 percent of the time.”
Meeting TAT objectives would not be scrutinized on a regular CAP inspection, Black says, and that’s one important difference between CAP accreditation and CAP 15189 inspection. “The 15189 process picks up cultural differences and process improvement measures, like turnaround times, and emphasizes continual improvement and raising the bar”—average versus 90 percent, for example.
In early 2017, Avera Laboratories was transitioning to a new line of chemistry instruments, dealing with construction, and changing processes to accommodate a new automation line. “We had a steady increase in turnaround times, and we needed to do something about it,” Black says.
First, they implemented a daily management report, with staff spending a maximum of 15 minutes every shift looking for “low-hanging fruit, what were our outliers and what can we shave off.” While they began to see improvement, they hoped, again, to reach the targeted TAT in 90 percent of all cases.
In January of that year, the lab conducted a Kaizen. “If I’m going to pull multiple people off the bench,” DesLauriers said, “I better make sure I am prepared and we use that day to our best ability and produce results. I didn’t have time to pull together a bunch of information, and I surely didn’t have the time or resources to spend mining data for the event.” Instead, the lab used its real-time data analytics TAT report, discovering that 60 percent of the time it was within 10 minutes of reaching its 90 percent TAT completion goal.
“When the laboratory installed its chemistry automation lines, there were significant changes and frustrations that went along with it,” Black says. Initially, the plan was to put all specimens on the automation line because “we did not want to have differences in our standardized processes. It goes against Lean principles.” But putting hematology on the line was bringing significant increases in TAT.
“That was probably not the right decision,” Black says. “And our oncology physicians were not very happy about it. We had to go back to the drawing board. We evaluated, we went to Gemba, we listed out the processes, we eliminated waste, and we were able to bring that turnaround time back down.”
[dropcap]L[/dropcap]aboratory staff receive a weekly report showing testing volume and distribution, a tool DesLauriers and her team use to make workflow decisions. “There’s a lot of different factors that can affect staff, how busy that shift feels . . . . This provides objective data of what we’re seeing in each department and helps us make staff recommendations about start times, responsibilities, and can be powerful when you also combine it with time spent,” she said. Using these data, “we realized our evening shifts were coming in way too early, we had too many people standing around,” and “we didn’t have buy-in to have them there.”
They have also used these data to collaborate with the outreach department: “We can evaluate that if [a new] client comes in, what kind of impact is that going to have on our workflow?” she said.
In another process improvement, the laboratory began using Voalte, a vendor with a HIPAA-compliant electronic messenger system. The laboratory sends critical value messages with the laboratory values electronically, “instead of waiting for a nurse or physician to get to the phone,” Black says, adding that the Voalte platform uses data communication to drive workflow improvement.
As with any project, of course, it takes a team to solve a problem. The Avera team has support from administration, including the laboratory medical director Raed Sulaiman, MD, and the entire lab. “By using analytics and being a CAP ISO 15189 laboratory,” Black says, “we have built a culture of continual improvement.”
Charna Albert is CAP TODAY associate contributing editor.