Journal article
Long-term capacity planning for obstetric surgical suites using quantile linear regression
Anaesthesia and intensive care, Vol.51(3), pp.178-184
05/2023
DOI: 10.1177/0310057X221127713
PMID: 36688369
Abstract
Obstetric surgical suites differ from most inpatient surgical suites, serving one specialty, and often small. We evaluated long-term capacity planning for these operating rooms. The retrospective cohort study included all caesarean births in three operating rooms over 28 years, 1994 through 2021, plus all other obstetric procedures over the latter 19 years. We calculated the obstetric anaesthesia activity index, 0.5 × neuraxial labour analgesia placement + 1.0 × caesarean births. Annual caesarean births from one year to the next had a Pearson linear correlation coefficient of 0.993. Therefore, linear regression can be used for long-term capacity planning. However, the difference between 0.9 and 0.1 quantiles in weekly caseloads was greater than tenfold larger than the annual rate of growth in births per week. Therefore, clinicians likely would be unable to distinguish, by experience, between growth versus being busy due to variability, suggesting value of the modelling. Over 19 years, the fraction of the obstetric workload from caesarean births was unchanging, Pearson correlation coefficient of 0.04. Therefore, use of the obstetric anaesthesia activity index to judge changes in workload was appropriate. The annual total for the index increased linearly, Pearson correlation coefficient of 0.98, supporting validity of the finding that long-term capacity can be planned with linear regression. The difference between 0.9 and 0.1 quantiles in weekly totals of the index exceeded annual rate of growth, supporting validity of the finding that variability week to week is very large relative to growth. These results help decision-makers ensure that operating rooms and staff meet referring hospitals’ needs.
Details
- Title: Subtitle
- Long-term capacity planning for obstetric surgical suites using quantile linear regression
- Creators
- Franklin Dexter - University of IowaRichard H Epstein - University of MiamiKokila N Thenuwara - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Anaesthesia and intensive care, Vol.51(3), pp.178-184
- DOI
- 10.1177/0310057X221127713
- PMID
- 36688369
- ISSN
- 0310-057X
- eISSN
- 1448-0271
- Language
- English
- Electronic publication date
- 01/23/2023
- Date published
- 05/2023
- Academic Unit
- Health Management and Policy; Anesthesia
- Record Identifier
- 9984362260102771
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