OBJECTIVES

: The aim of the study is to analyse the prescribing pattern and to identify the various DRPs associated with the therapy in a CKD patient.

METHODS

: A prospective observational study was conducted in 160 patients diagnosed with any stages of CKD. The prescription pattern was studied from the medication chart and the DRPs were identified, reported and categorised as per Pharmaceutical Care Network Europe (PCNE) classification V 5.01. Descriptive statistics was used to summarize the data. Association between categorial variables were analysed using chi-square test. The predictors of drug related problems were identified using binary logistic regression analysis. Any p value less than 0.05 is considered as statistically significant.

RESULTS

: The mean age of the study population was 50.08 ± 15.32 years with male predominance (71%). The average number of drugs per prescription was found to be 9.16± 3.01. The most prescribed drug category was anti-hypertensives and the most commonly prescribed drugs were diuretics. A total of 337 DRPs were identified, out of which the most common DRP was drug interactions (60%), followed by frequency errors (11.6%) and indication without drug use (11.3%). Logistic regression analysis identified co-morbidities more than three (odds ratio 2.09), anti-hypertensives more than two (odds ratio 1.9), Alcoholism (odds ratio 1.5) and polypharmacy (odds ratio 1.2) as the predictors of DRP’s even though they were not statistically significant at p=0.01

CONCLUSIONS

: DRPs increase the risk of deterioration of the disease state and increase the length of hospital stay. Identification and resolving of the DRPs will lead to better patient care and aid them in achieving proper treatment. Early identification and modification of the above-mentioned predictors could possibly prevent/reduce drug related problems.