Publications by authors named "D Voaklander"
Background: The National Hockey League (NHL) saw an unprecedented disruption to the competitive calendar due to the COVID-19 pandemic in March of 2020. Returning to play following an abrupt cessation of activity is a known risk factor for athletes.
Purpose: To analyze the occurrence and severity of events (injury and illness) in the NHL and to understand any differences in occurrence and severity between pre-pandemic seasons and seasons that immediately followed.
Introduction: Because farming is a physically demanding occupation, farmers may be susceptible to developing osteoarthritis (OA). The aim of this study was to determine the risk of developing OA in Canadian farm, non-farm rural and urban residents.
Methods: A retrospective cohort study of five Alberta health administrative databases examined the risk of developing OA among three groups: farm (n=143 431), non-farm rural (n=143 431) and urban (n=143 431) residents over the fiscal years 2000-2001 through 2020-2021.
Background: Little is known about human papillomavirus (HPV) vaccination among immigrant children in Canada. We conducted a study in Alberta, Canada to assess HPV vaccine coverage among school-aged immigrant children compared with non-immigrant children.
Methods: This cohort study analysed population-based linked administrative health data to measure HPV vaccine coverage for 346 749 school-aged children, including 31 656 immigrants.
Article Synopsis
- The study focused on developing a machine-learning model to help health systems in Alberta, Canada, identify older adults (aged 65 and older) at risk for falls and related hospital admissions, using 2018-2019 administrative health data.
- The CatBoost model showed promising results with a c-statistic of 0.70, indicating moderate accuracy, and predicted fall-related events among a large group of participants (224,445).
- The findings suggest that targeting interventions for the highest risk groups could lead to significant cost savings in the healthcare system, with potential savings of up to $C16 million by focusing on the top 25-50% of predicted risk.
Objective: To develop a machine-learning (ML) model using administrative data to estimate risk of adverse outcomes within 30-days of a benzodiazepine (BZRA) dispensation in older adults for use by health departments/regulators.
Design, Setting And Participants: This study was conducted in Alberta, Canada during 2018-2019 in Albertans 65 years of age and older. Those with any history of malignancy or palliative care were excluded.