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Background. The consensus among Canadians with regards to end-of-life preferences is that with adequate support the majority prefer to live and die at home. Purpose. To compare quality indicator (QI) rates for home care clients receiving palliative and end-of-life care prior to and after the onset of the COVID-19 pandemic. Methods. A retrospective population-based cohort design was used. Sixteen QIs informed by existing literature and a preliminary set of QIs recently evaluated by a modified Delphi panel were compared. Data were obtained from the over 280-item interRAI PC instrument for Ontario home care clients for two separate cohorts: the pre-COVID (January 14th, 2019 to March 16th, 2020) and COVID cohort (March 17th, 2020 to May 18th, 2021). A propensity score analysis was used to match on 21 covariates, resulting in a sample size of 2479 unique interRAI PC assessments per cohort. Alternative propensity score methods were explored as part of a sensitivity analysis. Results. After matching the pre-COVID and COVID cohorts (using nearest neighbour matching), five of the 16 QIs had statistically-significant differences in the QI rates. The two alternative propensity score methods produced slightly different results with fewer statistically-significant differences between the cohorts. However, in examining the effect sizes, the results of all propensity score methods were found to be not clinically meaningful. High rates of the prevalence of shortness of breath with activity, no advance directives, and fatigue were observed in both cohorts and across all three propensity score methods. Discussion. This study is the first to examine differences in QI rates for home care clients receiving palliative and end-of-life care before and during COVID in Ontario. Key limitations in interpreting the results include a limited understanding of the typical variation in QI rates over time and reliance on the comparison of a single proportion (the QI) in judging potential differences in quality. Importantly, a strength of this study was that these QIs focused on outcomes of care and were mainly symptom-focused as aspects of high-quality care valued by home care clients and families and in contrast to previous studies focusing on structure and processes of care. These QIs also indicated how frequently quality concerns may be occurring for those receiving palliative and end-of-life home care. Conclusion. It appears that QI rates did not change over the course of the pandemic in this population. Future work should be directed to understanding the temporal variation in these QI rates, risk-adjusting the QI rates for further comparison among jurisdictions, provinces, and countries and in creating benchmarks to project acceptable rates of different QIs. / Thesis / Master of Science in Nursing (MSN)

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Risk indicators are metrics that are widely used in risk management to indicate how risky an activity is. Among different types of risk indicators, early warning systems are designed to help decision makers predict and be prepared for catastrophic events. Especially, in complex systems where outcomes are often difficult to predict, early warnings can help decision makers manage possible risks and take a proactive approach. Early prediction of catastrophic events and outcomes are at the heart of risk management, and help decision makers take appropriate actions in order to mitigate possible effects of such events. For example, physicians would like to prevent any adverse events for their patients and like to use all pieces of information that help accurate early diagnosis and interventions. In this research, first we study risk assessment for occupational injuries using accident severity grade as an early warning indicator. We develop a new severity scoring system which considers multiple injury severity factors, and can be used as a part of a novel three-dimensional risk assessment matrix which includes an incident's severity, frequency, and preventability. Then we study the predictability of health outcome based on early risk indicators. A systems model of patient health outcomes and hospital length of stay is presented based on initial health risk and physician assessment of risk. The model elaborates on the interdependent effects of hospital service and a physician's subjective risk assessment on length of stay and mortality. Finally, we extend our research to study the predictive power of early warning systems and prognostic risk indicators in predicting different outcomes in health such as mortality, disease diagnosis, adverse outcomes, care intensity, and survival. This study provides a theoretical framework on why risk indicators can or cannot predict healthcare outcomes, and how better predictors can be designed. Overall, these three essays shed light on complexities of risk assessments, especially in health domain, and in the contexts where individuals continuously observe and react to the risk indicators. Furthermore, our multi-method research approach provides new insights into improving the design and use of the risk measures. / Ph. D.

Environmental sustainability has become important considering limited natural resources and an ever increasing consumption. Sustainability assessment is a complex procedure which is used to quantify and measure sustainability of a system. It needs to be performed in an organized and coherent manner to avoid unintended negative consequences. A systems-level, overarching, integrated model coupled with underlying process models would provide structure to sustainability assessment of coupled systems, thereby making the procedure more effective. The first objective of the study is to illustrate such a systems-level, overarching, framework using a simple, idealized, hypothetical model of a watershed as an example. The essential elements of underlying process models are utilized in building a simple, System Dynamics (SD) model, which is integrated at the overarching level. Orientors and indicators are used to assess sustainability. Two additional scenarios are modeled in order to improve system sustainability: technological advancement by implementing a rainwater use policy in the existing watershed model; and human behavior modification by coupling a social model with the existing watershed model. This demonstrates the effectiveness of the System Dynamics modeling approach in integration of multiple, varied systems. The second and ultimate objective of this study is to propose a generic framework for the overarching, systems-level model, providing a definite structure but allowing others to define their own model elements and relationships. This would enable more effective sustainability assessment of coupled complex systems. / Master of Science