Abstract
The Acute Care Surgery model has been implemented by many hospitals in the United States. As complex adaptive systems, healthcare systems are composed of many interacting elements that respond to intrinsic and extrinsic inputs. Systems level analysis may reveal the underlying organizational structure of tactical block allocations like the Acute Care Surgery model. The purpose of this study is to demonstrate one method to identify a key characteristic of complex adaptive systems in the perioperative services. Start and end times for all surgeries performed at the University of Vermont Medical Center OR1 were extracted for two years prior to the transition to an Acute Care Surgery service and two years following the transition. Histograms were plotted for the inter-event times calculated from the difference between surgical cases. A power law distribution was fit to the post-transition histogram. The Kolmogorov–Smirnov test for goodness-of-fit at 95% level of significance shows the histogram plotted from post-transition inter-event times follows a power law distribution (K-S = 0.088, p = 0.068), indicating a Complex Adaptive System. Our analysis demonstrates that the strategic decision to create an Acute Care Surgery service has direct implications on tactical and operational processes in the perioperative services. Elements of complex adaptive systems can be represented by a power law distributions and similar methods may be applied to identify other processes that operate as complex adaptive systems in perioperative care. To make sustained improvements in the perioperative services, focus on manufacturing-based interventions such as Lean Six Sigma should instead be shifted towards the complex interventions that modify system-specific behaviors described by complex adaptive system principles when power law relationships are present.
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Funding
Partial support provided by Vermont EPSCoR, with funds from the National Science Foundation (NSF) Grant OIA-1556770, is acknowledged.
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Timothy Wong helped design the study, prepare the manuscript, and provided critical edits. Erik J. Zhang: This author helped prepare the manuscript. Andrea J. Elhajj: The author helped design the study, analyze the data, and provided critical edits manuscript. Donna M. Rizzo: The author helped analyze the data and provided critical edits. Kevin Sexton helped prepare the manuscript and provided critical edits. Jaideep Pandit provided critical edits. Mitchell H. Tsai: The author helped design the study, prepare and manuscript and provide critical edits. He is the corresponding and archival author.
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Operating room management strategies require unique adaptations suited to complex adaptive systems, which may be identified by the presence of a power law relationship.
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The authors declare no personal conflicts of interest and have received no outside support for the creation of this document.
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Wong, T., Zhang, E.J., Elhajj, A.J. et al. The Power Law in Operating Room Management. J Med Syst 45, 92 (2021). https://doi.org/10.1007/s10916-021-01764-1
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DOI: https://doi.org/10.1007/s10916-021-01764-1