PURPOSE: The aim of the study is to develop a method to estimate osteoarthritis (OA) incidence by using administrative health care databases. METHODS: Using actual counts of OA diagnoses in different periods, we generated an equation that estimated the number of new OA diagnoses based on the length of time used for excluding prevalent OA cases. Physicians billing files from 1983 to 2002 maintained at Alberta Health and Wellness were used to verify the proposed method. Age- and sex-specific and crude OA incidences in 2002 were calculated by using this method. RESULTS: Women aged 50 to 59 years had the greatest incidence. For men, the greatest incidence was in the 60- to 69-year age category. Crude incidences for women and men were 1103 and 934 per 100,000 person-years, respectively. The overall crude rate was 1040 per 100,000 person-years. CONCLUSIONS: Modified power function accurately summarizes the relationship between number of first OA diagnoses and length of the clearance period and thus provides an effective model to estimate OA incidence. Not restricted to OA, this model also can be implemented to estimate incidences of other chronic conditions.
PURPOSE: The aim of the study is to develop a method to estimate osteoarthritis (OA) incidence by using administrative health care databases. METHODS: Using actual counts of OA diagnoses in different periods, we generated an equation that estimated the number of new OA diagnoses based on the length of time used for excluding prevalent OA cases. Physicians billing files from 1983 to 2002 maintained at Alberta Health and Wellness were used to verify the proposed method. Age- and sex-specific and crude OA incidences in 2002 were calculated by using this method. RESULTS:Women aged 50 to 59 years had the greatest incidence. For men, the greatest incidence was in the 60- to 69-year age category. Crude incidences for women and men were 1103 and 934 per 100,000 person-years, respectively. The overall crude rate was 1040 per 100,000 person-years. CONCLUSIONS: Modified power function accurately summarizes the relationship between number of first OA diagnoses and length of the clearance period and thus provides an effective model to estimate OA incidence. Not restricted to OA, this model also can be implemented to estimate incidences of other chronic conditions.
Authors: Daniel Prieto-Alhambra; Andrew Judge; M Kassim Javaid; Cyrus Cooper; Adolfo Diez-Perez; Nigel K Arden Journal: Ann Rheum Dis Date: 2013-06-06 Impact factor: 19.103
Authors: Gabriel Chodick; Howard Amital; Yoav Shalem; Ehud Kokia; Anthony D Heymann; Avi Porath; Varda Shalev Journal: PLoS Med Date: 2010-09-07 Impact factor: 11.069
Authors: Dahai Yu; Matthew Missen; Kelvin P Jordan; John J Edwards; James Bailey; Ross Wilkie; Justine Fitzpatrick; Nuzhat Ali; Paul Niblett; George Peat Journal: Clin Epidemiol Date: 2022-02-17 Impact factor: 4.790
Authors: Dahai Yu; Kelvin P Jordan; John Bedson; Martin Englund; Fiona Blyth; Aleksandra Turkiewicz; Daniel Prieto-Alhambra; George Peat Journal: Rheumatology (Oxford) Date: 2017-11-01 Impact factor: 7.580