3 ways to ensure the right test for the right patient at the right time

July 20, 2017

3 ways to ensure the right test for the right patient at the right time

A lack of quality assurance in lab test ordering causes far-reaching effects in costs and outcomes. Labs need to ensure they’re performing the right test for the right patient at the right time. But as you may have experienced, this is not as easy as it sounds.

W

hile many organizations focus on test verification and validation, studies show that more than 70% of errors occur in the pre-analytic phase.1 As labs continue to evolve their quality standards, the pre-analytic phase of testing is ripe with opportunity for improvement.

Jason Majorowicz, Quality Management  Coordinator at the Mayo Clinic, shares some strategies to reduce errors and eliminate waste with a few simple quality initiatives.

 

Jason Majorowicz

Jason R. Majorowicz, MBA

Quality Management Coordinator
Department of Lab Medicine and Pathology (DLMP)
Mayo Clinic, Rochester, MN

 

 

 

Problem: As care teams are spread thin, it’s easy to rush through paperwork and miss key information on a requisition form or skip an ask at an order entry prompt on the electric requisition because the information is not immediately available. 

This is typically where a call team comes in. But what if there was a way to prevent this from happening in the first place? 

Solution: Redesign your organization’s requisition forms and electronic data entry fields. Draw attention to key fields by highlighting and prioritizing them. This improves accuracy and helps ensure that the lab gets all the information it needs the first time. 

 

 

 

Solving one problem
by creating another

Consider this all too common situation:

Problem: Incomplete order information received by primary and reference laboratories creates situations where significant effort is expended to gather the missing information.

Solution: Create a dedicated call team. Most laboratories that have outreach business have a dedicated call team, with larger labs having call teams of over 50 full-time employees. These labs receive tens of thousands of samples per day—hundreds of which could be held up by missing or inaccurate information. 

The upside: The call teams successfully help labs get the information they need.

The downside: It is not a lean solution. Managing hundreds of phone calls takes an incredible amount of time and money that can ultimately delay results. The time and extra processing steps to secure the information is an issue for both the reference lab and the lab submitting the sample for testing. While many labs sending samples to reference labs have a dedicated referrals bench to send samples out, incoming phone calls may be fielded by bench staff, taking them away from their testing duties.

The bottom line: Call teams are often only a bandage on a much larger issue, as they strive to obtain information vital for testing. It’s vital for labs to think bigger and find the root cause of the problem. By reactively addressing issues, labs are doomed to face them again and again. They need to proactively address the root of the problem to truly realize a quality outcome.

 

 

Redesigning forms. 
Redefining success. 

Large academic medical center patients travel from all over the country to seek treatment. This makes it difficult for physicians to have in-person follow-up visits to track lab values over time. To get physicians the follow-up data they need, many of these centers send out blood-draw sample kits with draw-and-return instructions. This practice helps ensure lab values can be monitored using the same analytic method. To ensure the sample is viable when received, the date and time of the draw must be documented on the form—but this field was often left blank. 

Working with their Patient Education Team, one academic medical center recently redesigned the hierarchy of the form to prioritize this needed information. The date and time fields were moved to the top and were also called out in color in the instructions.  

Following this redesign, the rate for obtaining accurate collection date and time significantly increased.

 

Problem: While genetic testing is on the rise, physician knowledge of these tests often does not keep pace. This results in overutilization and overspending. Running a single genetic test can cost upward of thousands of dollars. To get ahead of this, many organizations have begun establishing use standards. 

Solution: Many health care institutions have implemented test utilization management strategies where physicians need to consult with a genetic counselor before ordering genetic testing. The counselor is able to review the specific case and determine if the test is warranted or if there is an alternative solution or more appropriate test. In other instances, physicians may be required to obtain prior use authorizations before they can order a genetic test. 

 

 

Problem: Patient specimens are often collected by health care team members other than lab staff. When this occurs, non-lab personnel making the collection may not understand all of the demographic and collection information required for successful testing of the specimen. This opens the door further for oversights or errors, which may impact the lab’s ability to provide a relevant and accurate test result. 

Solution: Institute seminars or training workshops to open the lines of communication between teams collecting specimens at your institution. Use these sessions to establish quality standards, review existing processes and implement new ones. Any quality improvement initiatives within your organization can go a long way to help physicians, nurses and labs work better together and break down silos, which can significantly improve patient care.

 

Make your case

As you evaluate the quality of your lab, you may be inspired to launch a quality initiative. But how do you get approval—and funds—from leadership? Make a business case.

Start by looking for ways to quantify the issues

  • How often is the issue occurring?

  • How many hours are spent fixing the repeat issue and what level of staff is assigned to the task?

  • How much money is expended fixing the repeat issue?

  • How are patients affected by these issues? Increased inpatient stay days? Wrong test at the wrong time leading to a missed diagnosis? Potential for patient harm?

Dimensionalize your proposed solution

  • What can be done to proactively get ahead of the problem?

Quantify the expected results

  • How many hours will be spared?

  • How much money will be saved?

  • What higher-value tasks can your team do in place of fixing the issue?

 

 

The way it’s been vs.
the way it should be  

As the lab is continuously striving to redefine its value, laboratorians like yourself need to continuously raise your quality standards. This means removing barriers, inefficiencies and processes that increase risk. Rather than consistently reacting to issues, empower your laboratorians to proactively solve them. This can help your lab provide the right results more efficiently than ever.

By identifying and implementing quality initiatives, labs can deliver quality performance and help drive quality of care throughout their organization.

 

For additional insights and tools, watch the video below to see Jason's presentation on this topic, delivered at CLMA's Knowledge Lab 2017.

 

Review additional questions and answers from Jason's presentation below:

Q&A 

What are some other "low hanging fruit" you think we should go after to help improve quality?

Response: Every Laboratory has “low hanging fruit” they can harvest to improve quality; the type of fruit harvested will vary by organization. I would encourage people looking to reduce errors and rework to be objective and look at the data they have at hand. A robust event reporting system is a great place to start looking. If your organization is like most, the pre-analytic phase of the testing process is rife with opportunities. An event reporting system need not be fancy; I have seen labs do great things with simple paper based systems. The key is to select a project that is a relatively quick win that will have noticeable impact to the organization. A quick win will allow you to develop momentum while also showing lab staff the organization is actionable on the events staff are submitting. Don’t have an event management system you say? I would strongly encourage exploring CLSI’s document QMS11, Nonconforming Event Management. While implementing an event management system is not necessarily a “quick win” cultivating an effective event management system is akin to planting a fruit tree. You cannot harvest the low hanging fruit if you don’t have a fruit tree.

CLSI. Nonconforming Event Management. 2nd ed. CLSI guideline QMS11. Wayne, PA: Clinical and Laboratory Standards Institute; 2015.

What have you done to reduce those missing pieces of information from your clients? Do you track by client?

Response: Tracking incoming defects, i.e. missing information, is a crucial first step to driving down rework. A laboratory has clients both internally to the organization and externally if they are involved in outreach or referral business. It is important to work across traditional silos that occur in a healthcare organization to provide the best care for internal patients. In some cases the laboratory may think they are asking for all the relevant information to perform testing in a straight forward manner only to find a critical piece is lost in translation when viewed by a non-laboratorian. Working collectively with nurses and physicians to design forms or “ask at order entry” questions in the electronic order system is one way to ensure communication to the laboratory is accurate and complete. For external clients, providing feedback on missing information is also important. Tracking missing information on a client by client basis is important so you can work in a partnership to reduce rework. Most people, by nature, are competitive and if you provide client specific data along with benchmark data back to clients they will often strive to meet or exceed the benchmark.

 

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