Date of Award
8-2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Industrial Engineering
Committee Chair/Advisor
Dr. David M. Neyens
Committee Member
Dr. Mary Elizabeth Kurz
Committee Member
Dr. Kapil Chalil Madathil
Committee Member
Dr. Katherine Law
Abstract
Improving patient safety in anesthesia has proven to be an arduous and challenging task. Despite the many strategies and interventions to improve patient safety that have been employed, patient harm in anesthesia remains a problem. The struggle to reduce patient harm in anesthesia is both attributable to and representative of the complexity of the anesthesia system. In navigating this complex system, anesthesia providers have different approaches to how they accomplish their work, which results in variability in anesthesia practice. This variability provides an immense challenge to designing and implementing efforts to improve patient safety, as rigid interventions are often met with intransigence due to their inability to mesh with variable practice. Just as anesthesia providers must be flexible to adapt to the complexities each case presents, human factors engineers are faced with the challenge of developing interventions that boast the same level of flexibility to fit within these work systems. In order to do so, we must first further our knowledge of the existing variability in anesthesia so it can be appropriately considered in future designs. It is only through proper consideration of the existing variability in anesthesia that we will be able to determine avenues for improving patient safety that are flexible to the entire scope of medication administration, and therefore are not susceptible to the same pitfalls that have inhibited the success of prior efforts. Thus, the overall objective of this dissertation was to provide a scope of the variability that exists in the practice of anesthesia such that it can be utilized by engineers to create interventions which are flexible to the entire scope of medication administration.
Three studies were completed in this dissertation. The first study investigated the scope of variability and inconsistency in patient safety-related terminology in anesthesia through a structured literature review. The main finding of this study is that the term “medication error” had widely variant definitions which represent fundamentally different concepts. This inconsistency in terminology can lead to problems with synthesizing, interpreting, and overall sensemaking in relation to anesthesia medication safety. The second study investigated the scope of variability in the use and dosing of anesthesia medications through several statistical analyses of a large anesthesia dataset. The main finding of this study is that there was significant variability in the use and dosing of medications between five different hospitals within the same health system. By examining variability between hospitals in the same health system, we can identify potential avenues for interventions that improve patient safety and foresee potential difficulties with implementing these interventions. The third study investigated the feasibility of designing a standardized medication set that accounts for variability in anesthesia medication use through the development and use of a greedy algorithm. The main finding of this study is that, depending on the available size for a standardized medication set, a single standard set may be able to effectively cover a vast majority of cases at all institutions. Improving patient safety through standardization is possible despite the large amount of variability identified, though the design and implementation of such systems must be done with careful consideration of the existing variability. This dissertation informs anesthesia patient safety ideology and provides guidance towards how we can make lasting, widespread improvements to anesthesia patient safety.
Recommended Citation
Biro, Joshua Michael, "Variability in Anesthesia and Its Implications for Improving Patient Safety" (2023). All Dissertations. 3391.
https://tigerprints.clemson.edu/all_dissertations/3391
Author ORCID Identifier
0000-0001-7362-4138
Included in
Ergonomics Commons, Industrial Engineering Commons, Other Medicine and Health Sciences Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons, Patient Safety Commons, Systems Engineering Commons, Systems Science Commons