How a potassium-based quality-of-service metric reduces phlebotomy errors

Preanalytical errors in laboratory testing are a frequent cause of inaccurate clinical lab results and can occur at any time—from test ordering, to sample collection, to specimen transport and handling. Data about preanalytical errors are often collected, and monitoring helps identify areas in which such errors are more likely to occur. Preanalytical errors often occur during sample-collection steps and can involve tourniquet time, tube type, order of draw, and filling, mixing, and transporting specimens to prevent hemolysis. If performed incorrectly, these process steps can cause changes in concentrations of critical serum and plasma analytes, including potassium. Because true hyperkalemia is a life-threatening panic value, it is important to address phlebotomy steps that may lead to spurious potassium results. The authors described herein the institutionwide implementation of a continuous quality management program focused on a potassium phlebotomy metric that supports continuous feedback, intervention, and retraining. This quality-of-service phlebotomy metric involves systematically evaluating plasma potassium concentrations per phlebotomist to detect preanalytical biases caused by variations in sample collection and handling that do not lead to frank hemolysis. The authors monitored potassium and retrained 26 full-time phlebotomists as part of their quality-of-service intervention pilot program. They periodically downloaded potassium values, measured between January 2013 and December 2020, from the electronic health record system. The name of the person performing the phlebotomy and the collection location, time, and date were recorded. The potassium threshold selected for hyperkalemia was more than 5.2 mmol/L and for hypokalemia was up to 3.5 mmol/L. The authors assessed how variations in potassium concentrations affected resource utilization. Laboratory-associated costs were calculated based on turnaround time, processing/procedure-related times and expenses, and the average hourly salaries of lab personnel, including phlebotomists. The authors developed an algorithm for monitoring data and providing feedback on a per phlebotomist basis. Their project was divided into three phases: Phase one involved investigating phlebotomy techniques and procedures; phase two involved implementing monthly surveillance on a per phlebotomist basis and monitoring potassium values for their effects on resource utilization; and phase three involved institutionwide use of the aforementioned quality-of-service metric. The results showed that intervention and retraining reinforced compliance with phlebotomy techniques and reduced the percentage of venipunctures with potassium results above the threshold. This resulted in an average savings of 13 to 100 percent for each high-volume phlebotomist and reduced the number of repeat blood draws needed to confirm hyperkalemia. Supervisors initially met with each phlebotomist monthly to review the data but, eventually, met only with those who had more than two percent of draws with potassium values above the 5.2 mmol/L threshold, to help reinforce compliance with techniques. The authors concluded that the ability to provide feedback and retraining on a per phlebotomist basis reduced erroneous hyperkalemia events and critical value alerts and led to significant cost savings. The simplicity and impact of this quality-of-service metric may help reduce preanalytical errors from phlebotomy techniques at other institutions as well.