Modeling Time to Return of Volunteer Blood Donor’s: In National Blood Bank, Addis Ababa, Ethiopia

Abstract

Background: Blood is the most precious and unique gift that one human being can give to another. It is lifesaving fluid that cannot be created artificially, but is only collected from donors which are the precious resources. Objectives: The study aimed to model time to return of volunteer blood donors’ in National blood bank, Addis Ababa, Ethiopian. Methods: A retrospective cohort study had been conducted at National Blood Bank, Addis Ababa, Ethiopia. In this study, a total of 6,019 voluntary blood donors were included and baseline data had been obtained from existing databases of all volunteer blood donors who donated blood from September 06, 2012 to September 11, 2013 and whether he/she returned or not were followed until September 2015. In this study Exponential, Weibull, log-logistic and lognormal as baseline hazard functions with the gamma and the inverse Gaussian frailty distributions were used. Results: A total of 6,019 voluntary blood donors donated blood during a period of 06 Sept 2012 to 11 Sept 2013. The median returning time of the donors was 26 months. About 46.7% of the donors were returned to donate blood again during the study period. The clustering effect is significant on modeling time to return of volunteer blood donors. According to the output of the Lognormal Gamma frailty model, gender of the donors’, age of the donors’, weight, occupation, donation experience, and experiencing donors’ reaction were the significant risk factors at 5% level of significance. Conclusion and Recommendation: Lognormal-Gamma frailty model is the model that best described time to return of the donors’ dataset. Being male donor, donation experience (repeat donor) and increasing weight (in Kg) significantly shorten/minimize the time-to-return of blood donors, while being in the age group (45-65), being a student and experiencing donors’ reaction prolongs the time to- return of volunteer blood donors. For those groups whose return time were prolonged, policy makers and human resource managers are expected to make interventions, and design appropriate policy, programs and donor motivational strategies to improve their return time.