Identifying non-value added waste that delay emergency CT brain workflow using lean management principles

Master Thesis


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Introduction: The Department of Radiology at Groote Schuur Hospital receives numerous emergency CT brain requests especially from the Emergency and Trauma departments. Improvement in emergency CT brain workflow should reduce waiting times for CT scans resulting in earlier diagnosis and treatment of these patients. Identification of the nonvalue-added waste (NVAW) (steps regarded as wasteful to the customer) in the CT brain workflow can be determined by use of a lean management tool namely a value stream map (VSM - a flow analysis of information required to provide service to the customer). AIM: The study aims to identify non-value-added waste in the CT brain workflow value stream map which may result in delay in emergency CT brain reporting. Method: This study investigated NVAW in emergency CT brain workflow for 5 working days between 08h00 to 22h00 from Monday to Friday. Nineteen patients booked for an emergency CT brain scan by the Emergency Department (ED) only between 08h00 and 22h00 over the specific 5 day working period were randomly selected using convenience sampling. The indications for emergency CT brain scans in the sample were similar to the wider group of patients undergoing emergency CT brain scans. A VSM identifying all the relevant steps in the emergency CT brain workflow was constructed. The investigator accompanied each of the nineteen patients from the ED to the CT scanner and back and manually recorded the time elapsed in minutes for each separate step on the data collection sheet. The outstanding information required was obtained from the Xiris system on the Phillips PACS (Picture Archiving and Communicating System). The average time interval for each of the steps as indicated on the VSM was calculated, and the rate limiting step(s) which resulted in a delay in emergency CT brain reporting was identified. Results: Overall, the longest step was the time interval from the time of completion of the scan to the generation of the report (turnaround time (TAT)) with an average time of 72.21 minutes (p value of < 0,01). Conversely, the time interval from placing the request by the clinician on the PACS to the time of annotation by the radiologist was the shortest with an average time of 5.84 minutes. Discussion: The lean management system was used to identify the rate limiting step(s) which resulted in delay in emergency CT brain reporting. Possible reasons identified for the delay caused by the rate limiting step include the backlog in reporting of the large number of already scanned cases which may be due to staff constraints as only one radiologist was on duty during most of the study period. Additional contributory factors include clinician telephonic query interruptions to radiology registrars during reporting sessions and delay in the emergency doctor authorising and facilitating transport of the patient from the emergency unit to the CT scanner. Conclusion: The value stream map tool in lean management can be utilised to identify non value added waste in emergency CT brain workflow.