Browsing by Author "Binka, Fred"
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Item Challenges in Establishing A Cohort-Event Monitoring Drug Safety Study in Ifakara And Rufiji HDSS(2011-08) Amuri, Mbaraka; Kigahe, Brown; Njozi, Mustafa; Masanja, Irene M.; Selemani, Majige; Dan, Kajungu; Khatib, Rashid A.; Adounvo, Sharon A.; Abdulla, Salim; Binka, Fred; Dodoo, AlexanderThe recommended artemisinin combination therapy (ACT) for treatment of uncomplicated malaria in Tanzania is artemether-lumefantrine (AL). Although Artemisinin and its derivatives are generally thought to be safe, there is currently little or no data on its safety among populations in Tanzania. In view of this INESS established a phase IV study to evaluate safety of AL through comprehensive pharmacovigilance in large populations with the aim of documenting rare adverse drug reactions and to characterize known effects in ‘real-life’. The methodology employed is cohort event monitoring which is observational, longitudinal and prospective. Patients with diagnosis of malaria for whom AL was prescribed were recruited into the cohort from four health facilities in each HDSS. Information on demographics, use of all medicines, mode of diagnosis of malaria, presenting signs and symptoms, co-diagnoses, events suspected as adverse drug reactions, reasons for stopping the drug and cause of death (if any) were collected using standardized questionnaire. They were followed up on 7 to 10 days after AL was dispensed. This report is on the number recruited so far and the challenges in getting the cohort going. 9028 patients were recruited. 9016 (99.8%) completed follow-up on day 7, of which 668 (7.4%) were done by telephone calls. 12 (0.13%) were lost during follow-up. The main challenges encountered are getting enough trained staff to recruit and follow up patients since CEM is quite labour intensive. 38 health providers and 10 field workers were recruited and offered the relevant training in collaboration with regulatory authorities. This helped to overcome the human resource challenge. Another challenge involved is the difficult to reach areas which are cut off especially during the rainy season. Follow up by telephone was adopted for these areas and this helped to reduce number of lost to follow-up. Setting up a cohort event monitoring program takes time and is demanding in terms of human resource. Training is very important in overcoming this. Involvement of all stakeholders and sponsors is a key to successItem Using classification tree modelling to investigate drug prescription practices at health facilities in rural Tanzania(2012-09) Dan, Kajungu; Selemani, Majige; Masanja, Irene M.; Amuri, Mbaraka; Njozi, Mustafa; Khatib, Rashid A.; Dodoo, Alexander; Binka, Fred; Macq, Jean; Alessandro, Umberto D.; Speybroeck, NikoBackground Drug prescription practices depend on several factors related to the patient, health worker and health facilities. A better understanding of the factors influencing prescription patterns is essential to develop strategies to mitigate the negative consequences associated with poor practices in both the public and private sectors. Methods A cross-sectional study was conducted in rural Tanzania among patients attending health facilities, and health workers. Patients, health workers and health facilities-related factors with the potential to influence drug prescription patterns were used to build a model of key predictors. Standard data mining methodology of classification tree analysis was used to define the importance of the different factors on prescription patterns. Results This analysis included 1,470 patients and 71 health workers practicing in 30 health facilities. Patients were mostly treated in dispensaries. Twenty two variables were used to construct two classification tree models: one for polypharmacy (prescription of ≥3 drugs) on a single clinic visit and one for co-prescription of artemether-lumefantrine (AL) with antibiotics. The most important predictor of polypharmacy was the diagnosis of several illnesses. Polypharmacy was also associated with little or no supervision of the health workers, administration of AL and private facilities. Co-prescription of AL with antibiotics was more frequent in children under five years of age and the other important predictors were transmission season, mode of diagnosis and the location of the health facility. Conclusion Standard data mining methodology is an easy-to-implement analytical approach that can be useful for decision-making. Polypharmacy is mainly due to the diagnosis of multiple illnesses.