BACKGROUND: Comorbidity scores based on medical or prescription claims data are frequently used to control for confounding in pharmacoepidemiological studies. Performance of such scores in predicting the risk of death in community-dwelling elderly adults may be compromised by the absence of mental health and socioeconomic characteristics not captured in claims data. OBJECTIVE: The aim of the study was to assess the impact of adding mental health status and sociodemographic characteristics to the Geriatric Comorbidity Score (GCS), a score derived from prescription claims data in the Quebec community-dwelling elderly population. METHODS: We used the cohort study from the longitudinal Quebec Seniors' Health Survey (n = 1,494) conducted between 2005 and 2006. For each participant, we obtained mental health and socioeconomic characteristics through validated questionnaires, which we linked with the medical and prescription claims databases of the Quebec Health Insurance Agency [Régie de l'assurance maladie du Québec (RAMQ)]. The main study outcome was death within 1 year, ascertained using the Quebec death registry. The GCS was calculated from prescription claims data, with the c statistic as a measure of performance. Using backward stepwise selection, external variables (marital status, region, family income, social support, daily hassles, perceived physical and mental health status, presence of mental health disorders) were added to the logistic regression model and the marginal effect assessed by comparing the c statistic with and without each covariate. RESULTS: Over 1 year, 77 deaths (5.15 %) were reported. The c statistic for the GCS was calculated as 0.67 (95 % confidence interval 0.64, 0.70). Addition of sex and age to the score yielded a 2.4 % increase. The variable with the greatest impact on the c statistic was marital status (6.1 % increase). Though important contributors, social support and perceived mental health status did not significantly improve performance of the score. CONCLUSIONS: While sex, age and marital status significantly improved performance of a predictive score in the community-dwelling elderly population, the absence of data on mental and physical health status did not appear to compromise the validity of claims-based scores. Combining comorbidity scores with other methods to control for confounding thus remains a useful tool in pharmacoepidemiological research.
BACKGROUND: Comorbidity scores based on medical or prescription claims data are frequently used to control for confounding in pharmacoepidemiological studies. Performance of such scores in predicting the risk of death in community-dwelling elderly adults may be compromised by the absence of mental health and socioeconomic characteristics not captured in claims data. OBJECTIVE: The aim of the study was to assess the impact of adding mental health status and sociodemographic characteristics to the Geriatric Comorbidity Score (GCS), a score derived from prescription claims data in the Quebec community-dwelling elderly population. METHODS: We used the cohort study from the longitudinal Quebec Seniors' Health Survey (n = 1,494) conducted between 2005 and 2006. For each participant, we obtained mental health and socioeconomic characteristics through validated questionnaires, which we linked with the medical and prescription claims databases of the Quebec Health Insurance Agency [Régie de l'assurance maladie du Québec (RAMQ)]. The main study outcome was death within 1 year, ascertained using the Quebec death registry. The GCS was calculated from prescription claims data, with the c statistic as a measure of performance. Using backward stepwise selection, external variables (marital status, region, family income, social support, daily hassles, perceived physical and mental health status, presence of mental health disorders) were added to the logistic regression model and the marginal effect assessed by comparing the c statistic with and without each covariate. RESULTS: Over 1 year, 77 deaths (5.15 %) were reported. The c statistic for the GCS was calculated as 0.67 (95 % confidence interval 0.64, 0.70). Addition of sex and age to the score yielded a 2.4 % increase. The variable with the greatest impact on the c statistic was marital status (6.1 % increase). Though important contributors, social support and perceived mental health status did not significantly improve performance of the score. CONCLUSIONS: While sex, age and marital status significantly improved performance of a predictive score in the community-dwelling elderly population, the absence of data on mental and physical health status did not appear to compromise the validity of claims-based scores. Combining comorbidity scores with other methods to control for confounding thus remains a useful tool in pharmacoepidemiological research.
Authors: D C Steffens; I Skoog; M C Norton; A D Hart; J T Tschanz; B L Plassman; B W Wyse; K A Welsh-Bohmer; J C Breitner Journal: Arch Gen Psychiatry Date: 2000-06
Authors: Michel Préville; Richard Boyer; Sébastien Grenier; Micheline Dubé; Philippe Voyer; Rosita Punti; Marie-Claire Baril; David L Streiner; John Cairney; Joëlle Brassard Journal: Can J Psychiatry Date: 2008-12 Impact factor: 4.356
Authors: Alfredo J Selim; Graeme Fincke; Xinhua S Ren; Austin Lee; William H Rogers; Donald R Miller; Katherine M Skinner; Mark Linzer; Lewis E Kazis Journal: J Ambul Care Manage Date: 2004 Jul-Sep