OBJECTIVE: The main objective was to estimate the mean direct costs of warfarin treatment for atrial fibrillation (AF) patients. Secondly, the costs of initiating warfarin treatment during a 60-day period and the impact of International Normalized Ratio (INR) and co-morbidities on costs were estimated. DESIGN AND DATA: The study was performed as a retrospective cohort study over a 12-month period in a Finnish communal health care setting. All AF patients aged 65 years or older (n = 250) with warfarin treatment were identified from the database of the health service district of an urban area. Patient specific information related to comorbidities, INR-control, complications and health care resource use were collected. Cost information was obtained from the Finnish national health care unit cost list. METHODS: The effect of treatment balance and other background variables on treatment costs were evaluated using ordinary least squares regression (OLS), log-transformed OLS and generalized linear model (GLM). The mean costs were calculated on the basis of the different models and bias corrected and accelerated (BCa) bootstrap confidence intervals (CIs) were calculated for the mean costs. RESULTS: The best fitting cost model was log-transformed OLS. The costs of warfarin treatment on the basis of the log-transformed model were 589.82 Euros (BCa 95% CI: 586.68-591.99) per patient compared to 616.00 Euros (BCa 95% CI: 579.98-652.96) obtained with the OLS-model. For the treatment initiation period, the mean costs were 263 Euros (BCa 95% CI: 218.90-314.71). Depending on the way that INR-control was defined, the mean costs were 95.27 Euros or 166.92 Euros higher for patients who were not in the defined INR-balance. CONCLUSIONS: The INR-control has a significant impact on the warfarin treatment costs. The choice of model influences the estimated mean costs. In addition, different models identify statistically significant effects between different background variables and costs.
OBJECTIVE: The main objective was to estimate the mean direct costs of warfarin treatment for atrial fibrillation (AF) patients. Secondly, the costs of initiating warfarin treatment during a 60-day period and the impact of International Normalized Ratio (INR) and co-morbidities on costs were estimated. DESIGN AND DATA: The study was performed as a retrospective cohort study over a 12-month period in a Finnish communal health care setting. All AFpatients aged 65 years or older (n = 250) with warfarin treatment were identified from the database of the health service district of an urban area. Patient specific information related to comorbidities, INR-control, complications and health care resource use were collected. Cost information was obtained from the Finnish national health care unit cost list. METHODS: The effect of treatment balance and other background variables on treatment costs were evaluated using ordinary least squares regression (OLS), log-transformed OLS and generalized linear model (GLM). The mean costs were calculated on the basis of the different models and bias corrected and accelerated (BCa) bootstrap confidence intervals (CIs) were calculated for the mean costs. RESULTS: The best fitting cost model was log-transformed OLS. The costs of warfarin treatment on the basis of the log-transformed model were 589.82 Euros (BCa 95% CI: 586.68-591.99) per patient compared to 616.00 Euros (BCa 95% CI: 579.98-652.96) obtained with the OLS-model. For the treatment initiation period, the mean costs were 263 Euros (BCa 95% CI: 218.90-314.71). Depending on the way that INR-control was defined, the mean costs were 95.27 Euros or 166.92 Euros higher for patients who were not in the defined INR-balance. CONCLUSIONS: The INR-control has a significant impact on the warfarin treatment costs. The choice of model influences the estimated mean costs. In addition, different models identify statistically significant effects between different background variables and costs.
Authors: Jonas Wallvik; Anders Själander; Lars Johansson; Orjan Bjuhr; Jan-Håkan Jansson Journal: Scand J Prim Health Care Date: 2007-06 Impact factor: 2.581
Authors: Andrea L Jorgensen; Sameh Al-Zubiedi; Jieying Eunice Zhang; Andrew Keniry; Anita Hanson; Dyfrig A Hughes; Diane van Eker; Lisa Stevens; Karen Hawkins; Cheng H Toh; Farhad Kamali; Ann K Daly; David Fitzmaurice; Alison Coffey; Paula R Williamson; Brian Kevin Park; Panos Deloukas; Munir Pirmohamed Journal: Pharmacogenet Genomics Date: 2009-10 Impact factor: 2.089