A Pilot Study to Validate Disease Ascertainment Algorithms for the Canadian Longitudinal Study on Aging

The Canadian Longitudinal Study on Aging (CLSA) will examine the health and lifestyle of 50,000 Canadians aged 45 to 85 years. The goal will be to better understand the aging process. As part of the CLSA, the presence of a variety of health conditions will be ascertained in participants. These health conditions will include stroke/cerebrovascular event, hypertension, myocardial infarction, angina pectoris, diabetes mellitus type 2, hypothyroidism, rheumatoid arthritis, osteoarthritis of the knee, hip, or hand, osteoporosis, dementia, depression, Parkinson's disease, chronic obstructive pulmonary disorder (COPD), and asthma. In studies like the CLSA, doctors cannot conduct a full clinical examination of every participant. Therefore, researchers have developed 'algorithms' (checklists) to determine an individual's disease status for research purposes. These algorithms must be able to identify persons who truly have the disease, as well as properly identify persons who are healthy. Algorithms for seven conditions, i.e., diabetes, osteoarthritis of the knee, hip, or hand, Parkinson's disease, COPD, and asthma have all been developed, but they have not been tested to see how well they accurately identify sick or healthy people. To use these algorithms in the CLSA, they must first be shown to have the ability to make such identifications. In this project, the seven algorithms will be tested in a group of persons whose health status is already known. This will be done to determine how well each algorithm can accurately rule in or rule out disease. Algorithms that work well will be included in the CLSA.