One of the impacts of the rising demand for community health services, primarily used by seniors, is that hospitals are often faced with the challenge of having patients finish the acute phase of their treatment and yet are unable to discharge them due to the lack of a bed in a more appropriate community care setting. The frequency of this challenge has led to the designation of “alternative level of care” (ALC) being ascribed to patients who remain in the hospitals due to insufficient capacity downstream. The thesis focuses on a model that seeks to address patient flow through the community care network (CCN) and finding capacity allocation policies for the different facilities that resolves the ALC challenge using scenario analysis. A queuing network model with general routings and nodes’ blocking has been developed and a heuristic approximation method has been employed for solving the model. Blocking probabilities and the number of blocked patients are derived as performance metrics of the CCN. We test the accuracy of the queuing model through a simulation model and the behaviours of the system in different scenarios are investigated in the simulation model and our policy insights and conclusions are provided.

One of the impacts of the rising demand for community health services, primarily used by seniors, is that hospitals are often faced with the challenge of having patients finish the acute phase of their treatment and yet are unable to discharge them due to the lack of a bed in a more appropriate community care setting. The frequency of this challenge has led to the designation of “alternative level of care” (ALC) being ascribed to patients who remain in the hospitals due to insufficient capacity downstream. The thesis focuses on a model that seeks to address patient flow through the community care network (CCN) and finding capacity allocation policies for the different facilities that resolves the ALC challenge using scenario analysis. A queuing network model with general routings and nodes’ blocking has been developed and a heuristic approximation method has been employed for solving the model. Blocking probabilities and the number of blocked patients are derived as performance metrics of the CCN. We test the accuracy of the queuing model through a simulation model and the behaviours of the system in different scenarios are investigated in the simulation model and our policy insights and conclusions are provided.

Action formalisms based on description logics (DLs) have recently been introduced as decidable fragments of well-established action theories such as the Situation Calculus and the Fluent Calculus. However, existing DL action formalisms fail to include general TBoxes, which are the standard tool for formalising ontologies in modern description logics. We define a DL action formalism that admits general TBoxes, propose an approach to addressing the ramification problem that is introduced in this way, and perform a detailed investigation of the decidability and computational complexity of reasoning in our formalism.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

The diploma thesis Detection of Alcohol in Speech Signal first describes the effect of alcohol on the human body. The second part deals with ways to obtain parameters that describe the speech signal. The third part provides a brief overview of previous case studies and patents focused on the detection of alcohol in the speech signal. The fourth part presents the collected own database of voice recordings and developed software application for the analysis of intoxicated speech. The final part describes the measured changes in speech signal parameters that indicate alcohol intoxication.

Introduction: Alternate Level of Care (ALC) patients are those who are kept hospitalized although they are medically well enough to be discharged. Those patients wait in acute care because they cannot access an appropriate alternative level of care outside the hospital. ALC leads to the improper consumption of valuable resources that are needed for patients waiting in other departments such as emergency rooms. This reflects poor quality outcomes of the healthcare system and represents a significant economic burden. Moreover, particularly when it concerns older adults, longer stay in hospital results in worsening their health outcomes, declining their functional status and increasing their needs for long-term care. Therefore, ALC is costly from both patient and health care system perspective. Objectives: The main objective of this study was to assess the impact of the Home First strategy on the incidence of ALC. Moreover, the study addressed both the specialized clinical needs (such as dialysis, chemotherapy and mechanical ventilation) and socioeconomic status of ALC patients in order to unveil their association with the ALC length of stay. Methods: This study involved a secondary analysis of data from the Institute for Clinical Evaluation (ICES). The analyzed dataset included a cohort of 6,059,033 hospitalization records of Ontario citizens, aged 65 years and older, who were admitted to an acute care facility between April 2004 and March 2017. The study involved descriptive analytics grouping the dataset into ALC and non-ALC subsets and examined the percentage of ALC hospitalizations, ALC days and reported odds ratios across several patients' characteristics. Results: From 2004 until 2016, ALC patients waited to access an appropriate destination for 10.7 million days. Those numbers represented 19.7% of all hospitalization days across Ontario. ALC was more likely among seniors aged 75-84 (OR 1.36, 95% CI 1.35-1.36), aged 85-94 (OR 2.16, 95% CI 2.15-2.17), aged 95+ (OR 2.46, 95% CI 2.40-2.50), females (OR 1.37, 95% CI 1.35-1.36), those who were hospitalized 90 days prior to their current admission (OR 1.22, 95% CI 1.21-1.22), and those who were admitted to hospital through Emergency Department (OR 2.64, 95% CI 2.62-2.67). Moreover, ALC was 10 times more likely in the subgroup of patients who were discharged to long-term care (LTC) (OR 9.71, 95% CI 9.66-9.77). For the socioeconomic characteristics, this study showed that patients were more likely to have ALC days when they lived in urban areas, had a lower income, and were highly unstable and dependent. Furthermore, patients with special clinical needs spent from 10% to 25% of their total hospitalization length of stay waiting to be discharged to an appropriated alternative level of care. Finally, the study revealed that although the implementation of a Home First strategy resulted in a 26% reduction of ALC hospitalizations and a 13% decrease in ALC days, the percent of patients discharged to LTC did not change. For the subgroup having the highest percentage of ALC hospitalizations (53.4%) and ALC days (40.3%), this reflects a partial failure of the Home First strategy in achieving its main objective of facilitating the discharge of patients to their homes. Conclusions: Policy makers and health care practitioners may benefit from the findings of this study by considering the needs of the ALC patients while planning, allocating resources, and developing polices for discharge, LTC and community care. However, more work is required to quantify the impact of the ALC determinants suggested in this study and assess the efficiency of the current policies and procedures. Introduction: Alternate Level of Care (ALC) patients are those who are kept hospitalized although they are medically well enough to be discharged. Those patients wait in acute care because they cannot access an appropriate alternative level of care outside the hospital. ALC leads to the improper consumption of valuable resources that are needed for patients waiting in other departments such as emergency rooms. This reflects poor quality outcomes of the healthcare system and represents a significant economic burden. Moreover, particularly when it concerns older adults, longer stay in hospital results in worsening their health outcomes, declining their functional status and increasing their needs for long-term care. Therefore, ALC is costly from both patient and health care system perspective. Objectives: The main objective of this study was to assess the impact of the Home First strategy on the incidence of ALC. Moreover, the study addressed both the specialized clinical needs (such as dialysis, chemotherapy and mechanical ventilation) and socioeconomic status of ALC patients in order to unveil their association with the ALC length of stay. Methods: This study involved a secondary analysis of data from the Institute for Clinical Evaluation (ICES). The analyzed dataset included a cohort of 6,059,033 hospitalization records of Ontario citizens, aged 65 years and older, who were admitted to an acute care facility between April 2004 and March 2017. The study involved descriptive analytics grouping the dataset into ALC and non-ALC subsets and examined the percentage of ALC hospitalizations, ALC days and reported odds ratios across several patients' characteristics. Results: From 2004 until 2016, ALC patients waited to access an appropriate destination for 10.7 million days. Those numbers represented 19.7% of all hospitalization days across Ontario. ALC was more likely among seniors aged 75-84 (OR 1.36, 95% CI 1.35-1.36), aged 85-94 (OR 2.16, 95% CI 2.15-2.17), aged 95+ (OR 2.46, 95% CI 2.40-2.50), females (OR 1.37, 95% CI 1.35-1.36), those who were hospitalized 90 days prior to their current admission (OR 1.22, 95% CI 1.21-1.22), and those who were admitted to hospital through Emergency Department (OR 2.64, 95% CI 2.62-2.67). Moreover, ALC was 10 times more likely in the subgroup of patients who were discharged to long-term care (LTC) (OR 9.71, 95% CI 9.66-9.77). For the socioeconomic characteristics, this study showed that patients were more likely to have ALC days when they lived in urban areas, had a lower income, and were highly unstable and dependent. Furthermore, patients with special clinical needs spent from 10% to 25% of their total hospitalization length of stay waiting to be discharged to an appropriated alternative level of care. Finally, the study revealed that although the implementation of a Home First strategy resulted in a 26% reduction of ALC hospitalizations and a 13% decrease in ALC days, the percent of patients discharged to LTC did not change. For the subgroup having the highest percentage of ALC hospitalizations (53.4%) and ALC days (40.3%), this reflects a partial failure of the Home First strategy in achieving its main objective of facilitating the discharge of patients to their homes. Conclusions: Policy makers and health care practitioners may benefit from the findings of this study by considering the needs of the ALC patients while planning, allocating resources, and developing polices for discharge, LTC and community care. However, more work is required to quantify the impact of the ALC determinants suggested in this study and assess the efficiency of the current policies and procedures. / Thesis / Master of Science (MSc)

Non-standard inferences are particularly useful in the bottom-up construction of ontologies in description logics. One of the more common non-standard reasoning tasks is the most specific concept (msc) for an ABox-individual. In this paper we present similar non-standard reasoning task: most specific concepts for models (model-mscs). We show that, although they look similar to ABox-mscs their computational behaviour can be different. We present constructions for model-mscs in FL₀ and FLE with cyclic TBoxes and for ALC∪∗ with acyclic TBoxes. Since subsumption in FLE with cyclic TBoxes has not been examined previously, we present a characterization of subsumption and give a construction for the least common subsumer in this setting.

An approximation of an ALC-concept by an ALE-concept can be computed in double exponential time [4]. Consequently, one needs powerful optimization techniques for approximating an entire unfoldable TBox. Addressing this issue we identify a special form of ALC-concepts, which can be divided into parts s.t. each part can be approximated independently. This independent approximation in turn facilitates caching during the computation of approximation.

Reasoning for Description logics with concrete domains and w.r.t. general TBoxes easily becomes undecidable. For particular, restricted concrete domains decidablity can be regained. We introduce a novel way to integrate a concrete domain D into the well-known description logic ALC, we call the resulting logic ALCP(D). We then identify sufficient conditions on D that guarantee decidability of the satisfiability problem, even in the presence of general TBoxes. In particular, we show decidability of ALCP(D) for several domains over the integers, for which decidability was open. More generally, this result holds for all negation-closed concrete domains with the EHD-property, which stands for the existence of a homomorphism is definable. Such technique has recently been used to show decidability of CTL with local constraints over the integers.

In the last few years there has been a large effort for analysing the computational properties of reasoning in fuzzy Description Logics. This has led to a number of papers studying the complexity of these logics, depending on their chosen semantics. Surprisingly, despite being arguably the simplest form of fuzzy semantics, not much is known about the complexity of reasoning in fuzzy DLs w.r.t. witnessed models over the Gödel t-norm. We show that in the logic G-IALC, reasoning cannot be restricted to finitely valued models in general. Despite this negative result, we also show that all the standard reasoning problems can be solved in this logic in exponential time, matching the complexity of reasoning in classical ALC.