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Full Text, Thesis (PhD Doctorate), Doctor of Philosophy (PhD), Institute for Integrated and Intelligent Systems, Science, Environment, Engineering and Technology, Scheduling problems emerge almost everywhere in real world situations. Efficient scheduling of resources in dynamic complex real world environments continues to pose a significant research challenge. Every real world problem has its own idiosyn- crasies, and environments in the real world are often more complicated. In real world dynamic environments, inevitable and unpredictable real-time events often force a change in scheduled plans. Despite this, most current approaches have been focused on solving simplified scheduling models assuming that all problem characteristics are known in advance. As the hospital’s largest revenue and cost centre, operating rooms are of pivotal importance to hospitals. Any improvement of surgery delivery systems is particularly important for hospitals. With healthcare starting to buckle under the pressures of growing demand and encumbered resources, improving operating room scheduling to deliver a significant improvement in utilisation of this overburdened resource is more important than ever. Motivated with this need, this dissertation describes our efforts to deliver significant improvements to operating room scheduling processes, particularly in Australian public hospitals.

Emergency department overcrowding is an increasing issue impacting patients, staff and quality of care, resulting in poor patient and system outcomes. In order to facilitate better management of emergency department resources, a patient admission predictive tool was developed and implemented. Evaluation of the tool’s accuracy and efficacy was complemented with a qualitative component that explicated the experiences of users and its impact upon their management strategies, and is the focus of this article. Semi-structured interviews were conducted with 15 pertinent users, including bed managers, after-hours managers, specialty department heads, nurse unit managers and hospital executives. Analysis realised dynamics of accuracy, facilitating communication and enabling group decision-making. Users generally welcomed the enhanced potential to predict and plan following the incorporation of the patient admission predictive tool into their daily and weekly decision-making processes. They offered astute feedback with regard to their responses when faced with issues of capacity and communication. Participants reported an growing confidence in making informed decisions in a cultural context that is continually moving from reactive to proactive. This information will inform further patient admission predictive tool development specifically and implementation processes generally.

OBJECTIVE: We explored the relationship between the National Emergency Access Target (NEAT) compliance rate, defined as the proportion of patients admitted or discharged from emergency departments (EDs) within 4 hours of presentation, and the risk-adjusted in-hospital mortality of patients admitted to hospital acutely from EDs. DESIGN, SETTING AND PARTICIPANTS: Retrospective observational study of all de-identified episodes of care involving patients who presented acutely to the EDs of 59 Australian hospitals between 1 July 2010 and 30 June 2014. MAIN OUTCOME MEASURE: The relationship between the risk-adjusted mortality of inpatients admitted acutely from EDs (the emergency hospital standardised mortality ratio [eHSMR]: the ratio of the numbers of observed to expected deaths) and NEAT compliance rates for all presenting patients (total NEAT) and admitted patients (admitted NEAT). RESULTS: ED and inpatient data were aggregated for 12.5 million ED episodes of care and 11.6 million inpatient episodes of care. A highly significant (P < 0.001) linear, inverse relationship between eHSMR and each of total and admitted NEAT compliance rates was found; eHSMR declined to a nadir of 73 as total and admitted NEAT compliance rates rose to about 83% and 65% respectively. Sensitivity analyses found no confounding by the inclusion of palliative care and/or short-stay patients. CONCLUSION: As NEAT compliance rates increased, in-hospital mortality of emergency admissions declined, although this direct inverse relationship is lost once total and admitted NEAT compliance rates exceed certain levels. This inverse association between NEAT compliance rates and in-hospital mortality should be considered when formulating targets for access to emergency care.

Study Objectives - To evaluate the implementation of a Patient Admission Prediction Tool (PAPT) in terms of patient flow outcomes and decision-making strategies. Methods - Setting: The PAPT was implemented in 2 Australian public teaching hospitals during October-December 2010 (hospital A) and October-December 2011 (hospital B). Design: A multisite prospective, comparative (before and after) design was used. Patient flow outcomes measured included access block and hospital occupancy. Daily and weekly data were collected from patient flow reports and routinely collected emergency department information by the site champion and researchers. Results - Daily decision-making strategies ranged from business as usual to use of overcensus beds. Weekly strategies included advanced approval to use of overcensus beds and prebooking nursing staff. These strategies resulted in improved weekend discharges to manage incoming demand for the following week. Following the introduction of the PAPT and workflow guidelines, patient access and hospital occupancy levels could be maintained despite increases in patient presentations (hospital A). Conclusions - The use of a PAPT, embedded in patient flow management processes and championed by a manager, can benefit bed and staff management. Further research that incorporates wider evaluation of the use of the tool at other sites is warranted.

Objectives: To i) identify predictors of admission, and ii) describe outcomes for patients who arrived via ambulance to three Australian public Emergency Departments (EDs), before and after the opening of 41 additional ED beds within the area. Methods: A retrospective, comparative, cohort study using deterministically linked health data collected between 3 September 2006 and 2 September 2008. Data included ambulance offload delay, time to see doctor, ED length of stay (ED LOS), admission requirement, access block, hospital length of stay and in-hospital mortality. Logistic regression analysis was undertaken to identify predictors of hospital admission. Results: One third of all 286,037 ED presentations were via ambulance (n= 79,196) and 40.3% required admission. After increasing emergency capacity, the only outcome measure to improve was in-hospital mortality. Ambulance offload delay, time to see doctor, ED length of stay (ED LOS), admission requirement, access block, hospital length of stay did not improve. Strong predictors of admission before and after increased capacity included: age over 65 years, Australian Triage Scale (ATS) category 1-3, diagnoses of circulatory or respiratory conditions and ED LOS > 4 hours. With additional capacity the odds ratios for these predictors increased for age >65 and ED LOS > 4 hours and decreased for triage category and ED diagnoses. Conclusions: Expanding ED capacity from 81 to 122 beds within a health service area impacted favourably on mortality outcomes but not on time-related service outcomes such as ambulance offload time, time to see doctor and ED LOS. To improve all service outcomes, when altering (increasing/decreasing) ED bed numbers, the whole healthcare system needs to be considered.