open access

Vol 21, No 4 (2014)
Original articles
Published online: 2014-08-29
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Improving the efficiency of the cardiac catheterization laboratories through understanding the stochastic behavior of the scheduled procedures

Pieter S. Stepaniak, Mohamed A. Soliman Hamad, Lukas R.C. Dekker, Jacques J. Koolen
DOI: 10.5603/CJ.a2013.0112
·
Cardiol J 2014;21(4):343-349.

open access

Vol 21, No 4 (2014)
Original articles
Published online: 2014-08-29

Abstract

 

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.

Abstract

 

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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Keywords

catheterization laboratory, scheduling, lognormal, efficiency

About this article
Title

Improving the efficiency of the cardiac catheterization laboratories through understanding the stochastic behavior of the scheduled procedures

Journal

Cardiology Journal

Issue

Vol 21, No 4 (2014)

Pages

343-349

Published online

2014-08-29

DOI

10.5603/CJ.a2013.0112

Bibliographic record

Cardiol J 2014;21(4):343-349.

Keywords

catheterization laboratory
scheduling
lognormal
efficiency

Authors

Pieter S. Stepaniak
Mohamed A. Soliman Hamad
Lukas R.C. Dekker
Jacques J. Koolen

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