Date of Award

Winter 1-1-2019

Document Type

Dissertation

Degree Name

MPharm Pharmacy Practice

Department

Department of Pharmacy Practice

First Advisor

Dr. Ravindra Prabhu

Abstract

Background: HRQOL, socioeconomic status (SES) factors andpenetration ofinsurance play a main role in affecting the patients’ QOL and the diseased population is linked with increased prevalence of end stage kidneydisease in view of disease progression in chronic kidney disease (CKD). However, not much studies were performed in India with respect to QOL, SES factors and insurance in ESKD patients.Objective: To investigate the association of SES and health insurance type in ESKD patients with maintenance HD and non-dialysis patients, and also to investigate the QOL in them.Methodology:A prospective study was performed on ESKD patients with dialysis and without dialysis in nephrology unit in a tertiary care hospital. Continuous data was analyzed using mean ± SD and categorical variables were analyzed using frequency. The HRQOL was assessed by using KDQOL-36 questionnaire. The domains scores, SES factors and insurance type were collected in a suitably designed data collection form and data was analyzed using SPSS 20. The association between SED, Insurance status and outcomes expressed in the form of domain score obtained by using KDQOL-36 questionnaire were assessed.Results:During the study period, an overall 160 ESKD patients were recruited in the study. In which 80 participants were recruited in dialysis group and the other 80 in non-dialysis group. The mean age was 51.03 ± 15.16 in dialysis and 57.45 ± 15.71 in non-dialysis patients. When KDQOL-36 domains score when compared among the two groups, the mean total score of HRQOL were found to be in the range between 50-60% , but it was found the dialysis patients (52.73 ± 12.75) group had low score when compared with non-dialysis patients (57.34 ± 15.85) implies poor HRQOL in dialysis patents when compared to with the other. The association between SES, Insurance status when compared with four different domains of KDQOL-36 questionnaire showed more significant association with residency in urban (p < 0.026), marital status of in unmarried (p < 0.008) and employment status of Student (p < 0.046). There was a positive association observed in the group with insurance and with 3 of the 4 domain score compared. Conclusion:SES factors and insurance played an important role in managing and obtaining better healthcare. Urban residency and insurance had positive association with domain score. Employment status and education level were not showing the significance association with the domain score in the study population

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