Key result
Catheterization laboratory procedure times are best modeled by a 3-parameter lognormal distribution, which was statistically superior to both the 2-parameter lognormal (p=0.0054) and normal models (p=0.0001).
Observational (n=6,135)
No
p-value: p=0.0054
Cath Lab procedure durations are best modeled using a 3-parameter lognormal distribution, which can help improve scheduling efficiency and resource management.
BACKGROUND: In this study, we sought to analyze the stochastic behavior of Catherization Laboratories (Cath Labs) procedures in our institution. Statistical models may help to improve estimated case durations to support management in the cost-effective use of expensive surgical resources. METHODS: We retrospectively analyzed all the procedures performed in the Cath Labs in 2012. The duration of procedures is strictly positive (larger than zero) and has mostly a large minimum duration. Because of the strictly positive character of the Cath Lab procedures, a fit of a lognormal model may be desirable. Having a minimum duration requires an estimate of the threshold (shift) parameter of the lognormal model. Therefore, the 3-parameter lognormal model is interesting. To avoid heterogeneous groups of observations, we tested every group-cardiologist-procedure combination for the normal, 2- and 3-parameter lognormal distribution. RESULTS: The total number of elective and emergency procedures performed was 6,393 (8,186 h). The final analysis included 6,135 procedures (7,779 h). Electrophysiology (intervention) procedures fit the 3-parameter lognormal model 86.1% (80.1%). Using Friedman test statistics, we conclude that the 3-parameter lognormal model is superior to the 2-parameter lognormal model. Furthermore, the 2-parameter lognormal is superior to the normal model. CONCLUSIONS: Cath Lab procedures are well-modelled by lognormal models. This information helps to improve and to refine Cath Lab schedules and hence their efficient use.
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Stepaniak et al. (2013) conducted an observational in Catheterization laboratory procedures (n=6,135). 3-parameter lognormal model vs. 2-parameter lognormal and normal models was evaluated on Statistical fit of procedure times (p=0.0054). Catheterization laboratory procedure times are best modeled by a 3-parameter lognormal distribution, which was statistically superior to both the 2-parameter lognormal (p=0.0054) and normal models (p=0.0001).
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