International Journal of Pharma and Bio Sciences
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editorijpbs@rediffmail.com (or) editorofijpbs@yahoo.com (or) prasmol@rediffmail.com
10.22376/ijpbs.2019.10.1.p1-12
Volume 7 Issue 2
2016 (April - June)
ASSESSMENT OF ECONOMIC IMPACT AND DEVELOPMENT OF A PREDICTOR MODEL FOR TOTAL COST DUE TO ADVERSE DRUG REACTIONS IN CANCER PATIENTS ON CHEMOTHERAPY
The aim of our study was to assess the economic impact of adverse drug reactions (ADRs) on patients due to cancer chemotherapy and develop a predictor model to predict the total cost due to ADRs. Total cost was calculated by taking into account both the direct and indirect cost incurred by the patient due to ADRs. Predictor model was developed to predict the total cost due to ADRs using multivariate regression analysis. A total of 387 patients participated in the study. Mean age of patients was 50.85 ± 11.82 years (95% CI, 49.66-52.03). Out of 387 patients, 51 were admitted to the hospital due to ADR/ADRs. The mean increase in length of stay of patients in hospital due to ADRs was found to be 12.5 days. The total cost due to ADRs in cancer patients on chemotherapy in our study was found to be INR 39,72,737 (≈ 62,568 US$) which included direct and indirect cost of INR 33,25,434 (≈ 52,373 US$) and INR 6,47,303 (≈10,195 US$) respectively. A significant difference was found in the total cost due to ADRs based on the onset of the reaction, severity of ADRs, length of stay of patients in hospital due to ADRs and quality of life scores. In the predictor model, the Coefficient of determination R-square (r lessThan sup greaterThan 2 lessThan /sup greaterThan ) was found to be 0.3684.The F lessThan sub greaterThan (5, 381) lessThan /sub greaterThan = 44.45, p lessThan 0.001 indicating the overall significance of the regression model. In conclusion, the total cost due to ADRs in cancer patients receiving chemotherapy is huge.
SMITA KHANDELWAL,KL BAIRY,MS VIDYASAGAR,ASHA KAMATH,JAMES GONSALVES AND BHARTI CHOGTU
Adverse drug reaction, Tertiary care hospital, Direct and Indirect cost, Multivariate regression, Predictor model
234-242