Electronic Thesis and Dissertation Repository

Thesis Format

Monograph

Degree

Master of Science

Program

Epidemiology and Biostatistics

Supervisor

Dr. Piotr Wilk

2nd Supervisor

Dr. Kelly Anderson

Co-Supervisor

Abstract

Ambulatory care sensitive conditions (ACSC) hospitalizations are potentially preventable events and considered as indicator of the efficiency of the primary healthcare system. Therefore, a high level of geographic variation in ACSC hospitalizations warrants more research. The objective of current research was to assess the variation in odds of ACSC-related hospitalizations across Canadian communities and health regions. To do so, the Discharge Abstract Database (DAD) from the Canadian Institute of Health Information (CIHI), was linked to the long-form census by Statistics Canada. Data from three fiscal years (FY), (2006 to 2009), were pooled. Statistical analysis included hierarchical three-level mix modeling. Results of my study showed that between 2006 and 2009, out of 4305400 Canadian population aged below 75 years age, 29130 individuals were hospitalized because of ACSC diseases. This study indicates that up to 14.62 % of variation in the odds of ACSC-related hospitalization was attributable to general contextual factors at the Census Subdivision (CSD)-level, 1.13% was accounted by health regions and the remaining 84% was related to individual-level variations. In summary, results suggest high geographic variation in the odds of ACSC hospitalization across CSDs and health regions. Beyond urbanicity characteristics, the place of residence (CSDs) appeared as a more influential attribute for the odds of ACSC compared to the place within which primary or acute healthcare services were received (health regions).

Summary for Lay Audience

Limiting preventable hospital admissions is a goal for the healthcare system, in Canada and around the world. The underlying motivations for reducing preventable hospitalizations can be addressed from three perspectives: a) cost (i.e., to avoid the financial waste of healthcare spending on hospital events that could be avoided); b) patient safety (i.e., there are increased risks of poor health outcomes for hospitalized patients regardless of their primary reason of hospital admission); and c) process disruptions (i.e., the disruption it causes to elective healthcare processes such as inpatient waiting lists). According to global evidence, including evidences from Canada, a disproportionate number of preventable hospital admissions occur among individuals with chronic conditions referred to as ambulatory care sensitive conditions (ACSC). The definition of ACSC from the Canadian Institute of Health Information (CIHI) includes the following conditions: grand mal status and other epileptic convulsions, chronic obstructive pulmonary disease (COPD), asthma, heart failure and pulmonary edema, hypertension, angina, and diabetes. According to the CIHI’s definition, ACSC hospitalizations are a relevant indicator of healthcare performance for non-elderly population (under 75 years of age). The overall goal of this study was to assess the geographic variation in the odds of ACSC hospitalizations and the factors associated with this variation. To achieve this goal, the census cohort comprised of the 2006 long-form census respondents was employed and this cohort was followed prospectively over a three-year follow-up interval (May 16, 2006 to March 31, 2009) for detecting their ACSC hospitalization events. Using this cohort, I found out that: the individual’s odds of hospital admission for ACSC was not the same across Canada. I found significant geographic variation in odds of ACSC hospitalization across Community (CSD) and health regions. Also results of my study showed that age, sex, visible minority status, marital status, income, educational attainment, immigration status, community-level socioeconomic status (SES) characteristics (i.e., median household income), and urbanicity of ACSC patients were strongly associated with the odds of ACSC hospitalization and its geographic variation. However, I found that these risk factors could not completely explain the geographic disparities and there should be other important, risk factors that need to be explored in future studies.

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