Most of the literature on scheduling of multi-product batch process does not consider the uncertainties in demand and variability in processing times. We develop a simulation based variable production schedule model for a multi-product batch facility assuming zero wait transfer policy and single product campaign. The model incorporates the demand uncertainties and processing time variability. The impact of demand uncertainties is evaluated in terms of total annual cost, which comprises of the backorder and inventory costs per year. The effect of variability in processing time is measured by the annual production time. We also develop a constant production schedule model that has uncertain demand arrival, but the schedule is independent of demand variations. We compare the variable production schedule model with constant production schedule model in terms of the total annual cost incurred and subsequent results are presented. The conclusion drawn from this comparison is that the total annual cost can be significantly reduced when the demand uncertainties are accounted for in the production schedule.

Emergency surgeries are serviced by three main forms of capacity: dedicated operating room time reserved for emergency surgeries, alternative (on call) capacity, and lastly, canceling of elective surgeries. The objective of this research is to model capacity implications of meeting wait time targets for multiple priority levels in the context of emergency surgeries. Initial attempts to solve the capacity evaluation problem were made using a non-linear optimisation model, however, this model was intractable. A simulation model was then used to examine the trade-off between additional dedicated operating room capacity (and consequent idle capacity) versus increased re-scheduling of elective surgeries while keeping reserved time for emergency surgeries low. Considered performance measures include utilization of operating room time, elective re-scheduling, and wait times by priority class. Finally, the instantaneous utilization of different types of downstream beds is determined to aid in capacity planning. The greatest number of patients seen within their respective wait time targets is achieved by a combination of additional on call capacity and a variation of the rule allowing low priority patients to utilize on call capacity. This also maintains lower cancelations of elective surgeries than the current situation. Although simulation does not provide an optimum solution it enables a comparison of different scenarios. This simulation model can determine appropriate capacity levels for servicing emergency patients of different priorities with different wait time targets.

This thesis is composed of three studies pertaining to the quality of care for radical cystectomy in Ontario between 1992 and 2004. In the first paper, the associations between provider volume and both operative and overall mortality were assessed. In the second paper, potential factors that could explain the association between volume and outcome were explored. In the final paper, the impact of waiting for cystectomy on survival outcomes was evaluated. Methods: A total of 3296 patients undergoing cystectomy for bladder cancer in Ontario between 1992 and 2004 were identified using the Canadian Institute for Health Information Discharge Abstract Database and the Ontario Cancer Registry. The effects of hospital and surgeon volume on operative mortality and overall survival were assessed using random effects logistic regression and marginal Cox Proportional Hazards modeling, respectively. To elucidate the factors underlying the volume-outcome association, the ability of a number of structure and process of care variables to attenuate the impact of volume was assessed. The effect of waiting for care, from transurethral resection to cystectomy, on overall survival was also assessed using marginal Cox models. Results: Neither hospital nor surgeon volume was significantly associated with operative mortality; however, both were associated with overall mortality. Of the measured structure/process measures, hospital factors caused the greatest attenuation of the volume hazard ratios, albeit to a limited degree. The wait time between the decision for surgery and cystectomy was also significantly associated with overall survival. The impact of delayed care was greatest for patients with lower stage disease. The data suggested a maximum wait time of 40 days for cystectomy. Conclusions: In this thesis, gaps in the quality of care for radical cystectomy in Ontario were identified. Patients treated by low volume hospitals and surgeons or those with long wait times all experienced worse outcomes. Since the underlying measures responsible for provider volume remain elusive, additional work is required to understand what these factors are. Initiatives to decrease wait times, however, are under way in Ontario. Whether these interventions decrease wait times and benefit patients remains to be seen.

This thesis is composed of three studies pertaining to the quality of care for radical cystectomy in Ontario between 1992 and 2004. In the first paper, the associations between provider volume and both operative and overall mortality were assessed. In the second paper, potential factors that could explain the association between volume and outcome were explored. In the final paper, the impact of waiting for cystectomy on survival outcomes was evaluated. Methods: A total of 3296 patients undergoing cystectomy for bladder cancer in Ontario between 1992 and 2004 were identified using the Canadian Institute for Health Information Discharge Abstract Database and the Ontario Cancer Registry. The effects of hospital and surgeon volume on operative mortality and overall survival were assessed using random effects logistic regression and marginal Cox Proportional Hazards modeling, respectively. To elucidate the factors underlying the volume-outcome association, the ability of a number of structure and process of care variables to attenuate the impact of volume was assessed. The effect of waiting for care, from transurethral resection to cystectomy, on overall survival was also assessed using marginal Cox models. Results: Neither hospital nor surgeon volume was significantly associated with operative mortality; however, both were associated with overall mortality. Of the measured structure/process measures, hospital factors caused the greatest attenuation of the volume hazard ratios, albeit to a limited degree. The wait time between the decision for surgery and cystectomy was also significantly associated with overall survival. The impact of delayed care was greatest for patients with lower stage disease. The data suggested a maximum wait time of 40 days for cystectomy. Conclusions: In this thesis, gaps in the quality of care for radical cystectomy in Ontario were identified. Patients treated by low volume hospitals and surgeons or those with long wait times all experienced worse outcomes. Since the underlying measures responsible for provider volume remain elusive, additional work is required to understand what these factors are. Initiatives to decrease wait times, however, are under way in Ontario. Whether these interventions decrease wait times and benefit patients remains to be seen.

In this thesis, I explored the relationship between patient experience of wait time for consultation and scheduled surgery, type of illness (orthopaedic or cardiac), and descriptions of time using qualitative methodology. Thirty two patients awaiting orthopaedic or cardiac surgery were recruited by surgeons in Saskatoon, Saskatchewan during the period of September 2009 to November 2010. Those patients awaiting orthopaedic surgery were interviewed when the decision to treat was made and again at the midpoint of their waiting period. Cardiac surgery patients were interviewed after their angiography and consent to surgery, and again the day prior to surgery. Patients were asked about their perceptions of time while waiting, maximum acceptable wait time for consultation and surgery, and the effects of waiting. Interpretative phenomenology (1) was the method and data were analysed using interpretative phenomenological analysis.Participant suffering, the meaningfulness given to the experience, and the agency participants felt they had over the waiting period determined the lived duration of time experience. Participants considered pain, mobility restriction, disease progression and lethality of condition to be the primary determinants of wait time maximums. Waiting effects included restriction, uncertainty, resignation, coping with waiting, and opportunity. Few subtle differences between groups emerged indicating other variables may be more relevant to the quality of waiting experience. Participant suggestions for improving experience consisted of managing patient conditions and navigating the system. The findings suggest uncertainty in illness impacts the quality of wait time experience. The study denotes the experience of waiting for scheduled surgery is complex and not necessarily a linear relationship between greater symptom severity and less tolerance for wait time.

The basis for this thesis involved a four month Accelerate Canada internship at the Grand River Hospital Emergency Department in Kitchener, Ontario. The Emergency Department (ED) Process Committee sought insight into strategies that could potentially reduce patient length of stay in the ED, thereby reducing wait times for emergency patients. This thesis uses discrete event simulation to model the overall system and to analyze the effect of various operational strategies within the fast track area of the emergency department. It discusses the design and development process for the simulation model, proposes various operational strategies to reduce patient wait times, and analyzes the different scenarios for an optimal fast track strategy. The main contribution of this thesis is the use of simulation to determine an optimal fast track strategy that reduces patient length of stay, thereby reducing patient wait times. Wait times were most significantly reduced when there was an increased physician presence/availability towards the fast track system. This had the greatest impact on the total time spent in the ED and also on queue length. The second most significant reduction to the performance measures occurred when an additional emergency nurse practitioner was supplemented to the fast track system. Accordingly, the nurse practitioner’s percent utilization increased. There was only one two-way interaction effect that was statistically significant in reducing the primary performance measure of wait times; however, the effect did not change the queue length, a secondary performance measure, by a significant amount. Finally, the implementation of a See-and-treat model variant for fast track had a negligible effect on both the average length of stay and queue length.

Waiting for service was often happen in Service setting. The literatures about the consequence of the waiting were strong in certain respects, typically negative and erode the customers¡¦ overall service evaluation, and underdeveloped in other respects. In this article, I consider the influence of the waiting on the customers perceived values. I propose the effect of waiting experiences on the customers perceived values depends on both how far the time lags of distances between purchasing and consuming and the word-of ¡Vmouth information supply. For the purpose, I choose the oversea leisure travel products that appear to have a significant time lag of consuming. The sample data from 290 college and graduated students were analyzed using descriptive statistics, T-tests, One-Way ANOVA and Two-Way MANOVA. The results of the three studies are presented as follows: 1. When customers perceived higher the value of the service products, they were more patient about waiting duration and more purchasing intentions. 2. The time lags of distances between purchasing and consuming were longer, the customers perceived values would increase first and then drop late. 3. Word of mouth information supply will enhance the customers perceived value.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) surgery is the most common reason for elective pediatric orthopaedic surgery. Minimization of adverse events is an important goal. Institute of Medicine (IOM) outlined 6 facets of healthcare quality improvement within the acronym STEEEP. Two of these facets, Safety and Timeliness for AIS surgery in Canada, are examined in this thesis. METHODS: A three - part study, using clinical records at the largest Canadian pediatric hospital and CIHI national administrative data, determined i) the relationship between surgical wait times and rates of adverse events, along with determination of an empirically derived access target, ii) accuracy of ICD-10 coding of surgical AIS cases along with an optimal search strategy to identify surgical AIS cases, and iii) the volume – outcome relationships for scoliosis surgery using hierarchical and conventional single level multi-variate regression analysis. RESULTS: Access target of 3 months minimized the adverse events related to waiting. Optimal search strategy for AIS surgical cases using ICD-10 coding required combination of codes as each code in isolation was inaccurate due to limitations in coding definitions. There was no significant volume – outcome relationship using appropriate modeling strategies. CONCLUSIONS: Ensuring timeliness of surgical treatment of less than 3 months is important in surgical cases of AIS given the potential for curve progression in higher risk individuals who are skeletally immature with large magnitude curves at time of surgical consent. At the administrative database level, knowledge of coding accuracy and optimal search strategies are needed to capture a complete cohort for analysis. In AIS, several ICD-10 codes need to be combined. AIS surgery cases captured through this optimal search strategy, revealed no significant volume-outcome relationships with appropriate modeling. Based on these results, minimum volume thresholds and regionalization of care for AIS surgery does not appear to be justified. However, a larger sample size was needed to determine whether there was a clinically significant difference in wound infection and blood transfusion rates. Furthermore, clinical variables, not part of an administrative database such as curve pattern were not included.

No description available.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) surgery is the most common reason for elective pediatric orthopaedic surgery. Minimization of adverse events is an important goal. Institute of Medicine (IOM) outlined 6 facets of healthcare quality improvement within the acronym STEEEP. Two of these facets, Safety and Timeliness for AIS surgery in Canada, are examined in this thesis. METHODS: A three - part study, using clinical records at the largest Canadian pediatric hospital and CIHI national administrative data, determined i) the relationship between surgical wait times and rates of adverse events, along with determination of an empirically derived access target, ii) accuracy of ICD-10 coding of surgical AIS cases along with an optimal search strategy to identify surgical AIS cases, and iii) the volume – outcome relationships for scoliosis surgery using hierarchical and conventional single level multi-variate regression analysis. RESULTS: Access target of 3 months minimized the adverse events related to waiting. Optimal search strategy for AIS surgical cases using ICD-10 coding required combination of codes as each code in isolation was inaccurate due to limitations in coding definitions. There was no significant volume – outcome relationship using appropriate modeling strategies. CONCLUSIONS: Ensuring timeliness of surgical treatment of less than 3 months is important in surgical cases of AIS given the potential for curve progression in higher risk individuals who are skeletally immature with large magnitude curves at time of surgical consent. At the administrative database level, knowledge of coding accuracy and optimal search strategies are needed to capture a complete cohort for analysis. In AIS, several ICD-10 codes need to be combined. AIS surgery cases captured through this optimal search strategy, revealed no significant volume-outcome relationships with appropriate modeling. Based on these results, minimum volume thresholds and regionalization of care for AIS surgery does not appear to be justified. However, a larger sample size was needed to determine whether there was a clinically significant difference in wound infection and blood transfusion rates. Furthermore, clinical variables, not part of an administrative database such as curve pattern were not included.