Using Lean Six Sigma and Discrete-Event Simulation to Reduce Patient Waiting Time Before Sample Collection: A Clinical Lab Case Study

Prolonged waiting time has been identified as a common shortcoming in different clinical labs and has been associated with delayed diagnosis, untimely treatment, cost overruns, a major risk of more severe health complications, and higher mortality rates. The problem is even more sharpened if the target population is composed of pregnant women who may experience dizziness, headache, vomiting, or fainting in case of extended delays before sample collection. Therefore, this paper proposes a combination between Lean Six Sigma (LSS) and Discrete-Event Simulation (DES) to minimize the waiting time before blood collection in clinical laboratories. We first described the process and its interactions with other departments using a SIPOC diagram. Second, we evaluated the measurement system reliability and performed a non-normal capability analysis to verify the current process performance. Afterward, we analyzed the main causes of the waiting time problem by employing the fishbone diagram, Value Stream Mapping (VSM), Correlogram, and DES. Following this, various improvement strategies were pretested using a DES model. Once these interventions were applied in the wild, a before-and-after analysis was undertaken to evidence how much the waiting time before sampling had lowered. Finally, X-R process control charts were elaborated to monitor this variable and underpin continuous improvement. A real case study in a private clinical laboratory is presented to validate this approach. As a result, the mean waiting time before sample collection passed from 61 to 21.5 min per patient while the parts per million (ppm) decreased from 873920 to 145714.