<p><strong>Background and Objectives</strong>: Tools designed for systems analysis (SA) can link the different levels of healthcare by modeling the interacting, interrelated and interdependent components. The objective of this thesis was to investigate the use of discrete event simulation (DES) to help inform decision making.</p> <p><strong>Methods</strong>:</p> <p>Project 1: A new method is developed in which physicians and their delegates are modeled using DES as interacting pseudo-agents when simulating a hospital emergency department (ED).</p> <p>Project 2: Using a SA approach, we examined the referral patterns, healthcare utilization, time intervals and patient flow to identify rate limiting steps that may lead to delayed surgical candidacy and epilepsy surgery at the Hospital for Sick Children (SickKids) in Toronto, Ontario.</p> <p>Project 3: A DES model was developed of the surgical evaluation and surgery process and its associated constraints at SickKids to inform decision making at both the institutional and provincial levels. Once validated, the model was used to evaluate the effect of alternative resource capacities on waiting times.</p> <p><strong>Results:</strong></p> <p>Project 1: Neglecting the interaction between physician and delegates in the ED could result in misleading conclusions with respect to physician utilization and waiting times.</p> <p>Project 2: We found that only 5.7% of the eligible population was referred annually for surgical evaluation and that children waited on average 1-2 years for surgery. Through mapping of patient flow and resource utilization we were able to identify multiple barriers to surgery.</p> <p>Project 3: The findings support the recommendations to the province by directing requested funds to identified resources that would decrease waiting times.</p> <p><strong>Conclusions: </strong>SA tools can be used to make decisions that are generalizable to all levels of healthcare. Adopting the use of these tools increases the uptake of evidence in decision making and provides useful and critical information to develop comprehensive policies for improved healthcare.</p> / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/13206 |
| Date | 10 1900 |
| Creators | Lim, Morgan E. |
| Contributors | Tarride, Jean-Eric, Goeree, Ron, Worster, Andrew, Clinical Epidemiology/Clinical Epidemiology & Biostatistics |
| Source Sets | McMaster University |
| Detected Language | English |
| Type | thesis |
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