Formalization and Quantification of the workflow in the Catheterization Laboratory

Abstract

Cardiovascular disease is the number one cause of death in the USA and number two in the Netherlands(1, 2). In addition, it is expected that in 2030 40.5% of the population in America will be inflicted with a form of cardiovascular disease(2). The growing volumes and thereby health care costs will put a strain on hospitals and health care providers, as more individuals need to be treated with the same resources. Workflow and efficiency optimization are topics that are gaining momentum over the last years in the field of medicine (3-6). Health care providers see this as a viable solution to treat more patients and reduce the costs, i.e. increasing efficiency. This research group intend to automatically evaluate the workflow efficiency in the cath lab with use of two sensors: the X-ray imaging system and video cameras. In order to facilitate automatic workflow monitoring and optimization, prior research should be conducted, as “the initial step for improving the process is to acquire knowledge of how things are done”(7). To continue in this line of reasoning, in this research the current peri-operative workflow of the CAG procedure is formalized and quantified.METHODWe used the SPM (surgical process model) methodology to formalize the peri-operative workflow of the CAG. The role activity diagram (RAD) was chosen as the model representation. The model approach was top-down. The metrics were determined and designed based on a previous conducted literature study, the formalization of the workflow and the design criteria. The metrics were divided in two groups: 1) the high-level metrics and 2) the procedure and CAG specific metrics. To evaluate metrics two datasets were used: 1) the manually acquired dataset through observations and 2) the dataset retrieved from the X-ray imaging system. To validate the methodology, the outcomes of the metrics were compared with the experience of the cath lab team. The generalizability was tested by utilizing the phases and metrics in different endovascular procedures and in a different hospital.RESULTSIn total 19 metrics were created of which 11 evaluated the high-level workflow, three the procedure specific process and five the CAG specific steps. Prior the first procedure in the morning, the LA waiting time showed an average of 37 minutes and on average seven minutes are used for lab preparation. In the afternoon similar results are found: the LAs waiting time is longer than the actual lab preparation. The average percentage on-time start cases was 43%. A significant mean difference of 3.3 minutes (p=0.041) regarding the turn-over time was found between the two LA and three LA group. Delivery time showed a mean difference of 3.7 minutes (p=0.004), comparing inpatients (M = 8.1± 5.43 minutes) to outpatients (M = 4.4 ± 4.4 minutes). There was significant positive correlation between delivery times and turn-over times, r=0.66 (p<0.001). Longer delivery times resulted in longer turn-over times. The procedure time presented the highest mean and variance, M=38.0 ± 21.1 minutes. The patient preparation time and post-care duration presented low variances, respectively M=11.8 ± 3.8 minutes and M=4.6 ± 3.3 minutes. The variability in the procedural time could be attributed to the operative phase, M=22.4 ± 18.8 minutes. Within the operative phase, the duration of P1 and P2 accounted for 70% of the variability in the operative length. The X-ray imaging system was able to correctly measure consolidation of metrics describing P2, P3 and P4. The non-procedure specific metrics have the potential to be generalized to any type of procedure. Only P1 and P5 showed potential to be utilized in other endovascular procedures. The analysis in Haga hospital suggests that phases and the metrics could be generalized and therefore used in more cath labs throughout the Netherlands.DISCUSSIONThis research has paved the way for in-depth efficiency assessment and workflow optimization in the cath lab. The cost of delay in an OR is $25 /minute(8). In the event that turnover time can be shortened by five minutes, 20 minutes of scarce lab time would be saved each day. Assuming the cost of delay in the cath lab is similar to the cost of delay in the OR, 500 $/day can be saved by optimizing the turn-over times. Moreover, the LAs wait in the morning for 20 minutes and in the afternoon for 15 minutes. In case the waiting time could be reduced with 50%, 18 minutes of wasted time would be utilized and 450 $/day would be saved. Enhancing starting time and the turn-overtime can result in saving 38 minutes that account for 950 $/day, which is approximately the scheduled time of one CAG procedure. As a result of optimization, an extra patient could be treated every day and money could be saved.