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The nature and sources of variability in pediatric surgical case duration
Fernanda Bravo1, Retsef Levi1, Lynne R Ferrari2
1Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
Insights
Pediatric case time variability is significant but not explained by surgeon or patient factors. Future efforts should focus on identifying predictors of unexpectedly long cases to improve operating room scheduling.
Area of Science:
- Pediatric Surgery
- Healthcare Operations Research
- Anesthesiology
Background:
- Operating room scheduling is challenged by case time variability, impacting resource allocation.
- Existing research on case time variability primarily focuses on adults, with limited data in pediatrics.
Purpose of the Study:
- To investigate patient and procedural factors influencing case time variability in pediatric surgery.
- To identify predictors for improving operating room efficiency in academic pediatric hospitals.
Main Methods:
- Analysis of over 40,000 pediatric surgeries across three years.
- Utilized bootstrapping for descriptive and variability statistics of 249 procedures.
- Employed conditional inference regression trees to identify predictive patient and procedural factors.
Main Results:
- Pediatric case time variability, measured by standard deviation, was 30% of the median case time.
- Relative variability was highest for shorter procedures.
- Predictive factors, including surgeon identity, explained little of the variability in most cases.
Conclusions:
- Pediatric case time variability is poorly explained by commonly available electronic health record data.
- Surgeon-specific scheduling is not supported by current data; similar cases can be pooled.
- Future research should identify predictors of prolonged cases to optimize pediatric operating room scheduling.
Background:
Case time variability confounds surgical scheduling and decreases access to limited operating room resources. Variability arises from many sources and can differ among institutions serving different populations. A rich literature has developed around case time variability in adults, but little in pediatrics.
Objective:
We studied the effect of commonly used patient and procedure factors in driving case time variability in a large, free-standing, academic pediatric hospital.
Methods:
We analyzed over 40 000 scheduled surgeries performed over 3 years. Using bootstrapping, we computed descriptive statistics for 249 procedures and reported variability statistics. We then used conditional inference regression trees to identify procedure and patient factors associated with pediatric case time and evaluated their predictive power by comparing prediction errors against current practice. Patient and procedure factors included patient's age and weight, medical status, surgeon identity, and ICU request indicator.
Results:
Overall variability in pediatric case time, as reflected by standard deviation, was 30% (25.8, 34.7) of the median case time. Relative variability (coefficient of variation), was largest among short cases. For a few procedure types, the regression tree can improve prediction accuracy if extreme behavior cases are preemptively identified. However, for most procedure types, no useful predictive factors were identified and, most notably, surgeon identity was unimportant.
Conclusions:
Pediatric case time variability, unlike adult cases, is poorly explained by surgeon effect or other characteristics that are commonly abstracted from electronic records. This largely relates to the 'long-tailed' distribution of pediatric cases and unpredictably long cases. Surgeon-specific scheduling is therefore unnecessary and similar cases may be pooled across surgeons. Future scheduling efforts in pediatrics should focus on prospective identification of patient and procedural specifics that are associated with and predictive of long cases. Until such predictors are identified, daily management of pediatric operating rooms will require compensatory overtime, capacity buffers, schedule flexibility, and cost.
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