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Addressing the variation of post-surgical inpatient census with computer simulation

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Abstract

Objective

This study describes the development of a Discrete Event Simulation (DES) of a large pediatric perioperative department, and its use to compare the effectiveness of increasing the number of post-surgical inpatient beds vs. implementing a new discharge strategy on the proportion of patients admitted to the surgical unit to recover.

Materials and methods

A DES of the system was developed and simulated data were compared with 1 year of inpatient data to establish baseline validity. Ten years of simulated data generated by the baseline simulation (control) was compared to 10 years of simulated data generated by the simulation for the experimental scenarios. Outcome and validation measures include percentage of patients recovering in post-surgical beds vs. “off floor” in medical beds, and daily census of inpatient volumes.

Results

The proportion of patients admitted to the surgical inpatient unit rose from 79.0 % (95 % CI, 77.9–80.1 %) to 89.4 % (95 % CI, 88.7–90.0 %) in the discharge strategy scenario, and to 94.2 % (95 % CI, 93.5–95.0 %) in the additional bed scenario. The daily mean number of patients admitted to medical beds fell from 9.3 ± 5.9 (mean ± SD) to 4.9 ± 4.5 in the discharge scenario, and to 2.4 ± 3.2 in the additional bed scenario.

Discussion

Every hospital is tasked with placing the right patient in the right bed at the right time. Appropriately validated DES models can provide important insight into system dynamics. No significant variation was found between the baseline simulation and real-world data. This allows us to draw conclusions about the ramifications of changes to system capacity or discharge policy, thus meeting desired system performance measures.

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Acknowledgments

The authors appreciate the efforts of Lori Crowder, MHA BSN RN CNOR, Dylan Horn, MBA, Judith E. Kraft, MBA, Sonia Joiner-Jones, RN, and Michael L. Nance, MD in providing insight into the perioperative process and assisting with face validation for this investigation. In addition, the authors thank Melissa Bates, PhD, for manuscript review.

Conflict of interest

The authors received no external support for this study.

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Authors and Affiliations

  1. The Children’s Hospital of Philadelphia, Office of Patient Safety and Quality, AE25H, 3401 Civic Center Blvd, Philadelphia, PA, 19104, USA

    Theodore Eugene Day, Albert Chi, Matthew Harris Rutberg & Victoria M. Otarola

  2. The Children’s Hospital of Philadelphia, Pediatric Intensive Care Unit, Philadelphia, PA, USA

    Ashley J. Zahm

  3. General Anesthesia, Children’s Hospital of Philadelphia, Philadelphia, USA

    Jeffrey M. Feldman & Caroline A. Pasquariello

  4. University of Pennsylvania, Perelman School of Medicine, Philadelphia, USA

    Jeffrey M. Feldman & Caroline A. Pasquariello

Authors
  1. Theodore Eugene Day
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  2. Albert Chi
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  3. Matthew Harris Rutberg
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  4. Ashley J. Zahm
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  5. Victoria M. Otarola
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  6. Jeffrey M. Feldman
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  7. Caroline A. Pasquariello
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Corresponding author

Correspondence to Theodore Eugene Day.

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Day, T.E., Chi, A., Rutberg, M.H. et al. Addressing the variation of post-surgical inpatient census with computer simulation. Pediatr Surg Int 30, 449–456 (2014). https://doi.org/10.1007/s00383-014-3475-0

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  • DOI: https://doi.org/10.1007/s00383-014-3475-0

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