Predictors of Antibiotics Co-prescription with Antimalarials for Patients Presenting with Fever in Rural Tanzania.

Successful implementation of malaria treatment policy depends on the prescription practices for patients with malaria. This paper describes prescription patterns and assesses factors associated with co-prescription of antibiotics and artemether-lumefantrine (AL) for patients presenting with fever in rural Tanzania. From June 2009 to September 2011, a cohort event monitoring program was conducted among all patients treated at 8 selected health facilities in Ifakara and Rufiji Health and Demographic Surveillance System (HDSS).It included all patients presenting with fever and prescribed with AL. Logistic regression was used to model the predictors on the outcome variable which is co-prescription of AL and antibiotics on a single clinical visit. A cohort of 11,648 was recruited and followed up with 92% presenting with fever. Presumptive treatment was used in 56% of patients treated with AL. On average 2.4 (1 -- 7) drugs was prescribed per encounter, indicating co-prescription of AL with other drugs. Children under five had higher odds of AL and antibiotics co-prescription (OR = 0.63, 95% CI: 0.46 -- 0.85) than those aged more than five years. Patients testing negative had higher odds (OR = 2.22, 95%CI: 1.65 -- 2.97) of AL and antibiotics co-prescription. Patients receiving treatment from dispensaries had higher odds (OR = 1.45, 95% CI: 0.84 -- 2.30) of AL and antibiotics co-prescription than those from served in health centres even though the deference was not statistically significant. Regardless the fact that Malaria is declining but due to lack of laboratories and mRDT in most health facilities in the rural areas, clinicians are still treating malaria presumptively. This leads them to prescribe more drugs to treat all possibilities

Using classification tree modelling to investigate drug prescription practices at health facilities in rural Tanzania.

BACKGROUND: 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

Experiences and Lessons From Implementing Cohort Event Monitoring Programmes for Antimalarials in Four African Countries: Results of a Questionnaire-Based Survey

INTRODUCTION: Cohort event monitoring (CEM) is an intensive method of post-marketing surveillance for medicines safety. The method is based on prescription event monitoring, which began in the 1970s, and has since been adapted by WHO for monitoring the safety of medicines used in Public Health Programmes. CEM aims to capture all adverse events that occur in a defined group of patients after starting treatment with a specific medicine during the course of routine clinical practice. OBJECTIVE: The aims of this study were to describe the experiences of National Pharmacovigilance Centres (NCs) that have used CEM to monitor artemisinin-based combination therapy (ACT) for uncomplicated malaria in the African setting, to raise awareness of some of the challenges encountered during implementation and to highlight aspects of the method that require further consideration. METHOD: A questionnaire-based survey was conducted to capture the experiences of NCs that have implemented CEM for active post-marketing surveillance of antimalarial medicines in sub-Saharan Africa. Six NCs were identified as having implemented CEM programmes and were invited to participate in the survey; five NCs indicated willingness to participate and were sent the questionnaire to complete. RESULTS: Four NCs responded to the survey—Ghana, Kenya, Nigeria and Zimbabwe—providing information on the implementation of a total of six CEM programmes. Their experiences indicate that CEM has helped to build pharmacovigilance capacity within the participating NCs and at the monitoring sites, and that healthcare providers (HCPs) are generally willing to participate in implementing the CEM method. All of the programmes took longer than expected to complete: contributing factors included a prolonged enrolment period and unexpectedly slow data entry. All of the programmes exceeded their budget by 11.1–63.2 %. Data management was identified as a challenge for all participating NCs. CONCLUSIONS: The reported experiences of four NCs that have undertaken CEM studies on ACTs indicate that CEM has helped to build pharmacovigilance capacity within NCs and monitoring sites and that HCPs are willing to participate in CEM programmes; however, the method was found to be labour intensive and data management was identified as a challenge. Reducing the workload associated with CEM, particularly in relation to data management, and integrating the method into the routine work of HCPs and NCs should be considered for future implementation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40264-015-0331-7) contains supplementary material, which is available to authorized users

Correction to: Pharmacokinetic profile of amodiaquine and its active metabolite desethylamodiaquine in Ghanaian patients with uncomplicated falciparum malaria

An amendment to this paper has been published and can be accessed via the original article

Characterisation of CYP2C8, CYP2C9 and CYP2C19 polymorphisms in a Ghanaian population

<p>Abstract</p> <p>Background</p> <p>Genetic influences on drug efficacy and tolerability are now widely known. Pharmacogenetics has thus become an expanding field with great potential for improving drug efficacy and reducing toxicity. Many pharmacologically-relevant polymorphisms do show variability among different populations. Knowledge of allelic frequency distribution within specified populations can be useful in explaining therapeutic failures, identifying potential risk groups for adverse drug reactions (ADRs) and optimising doses for therapeutic efficacy. We sought to determine the prevalence of clinically relevant Cytochrome P450 (<it>CYP) 2C8</it>, <it>CYP2C9</it>, and <it>CYP2C19 </it>variants in Ghanaians. We compared the data with other ethnic groups and further investigated intra country differences within the Ghanaian population to determine its value to pharmacogenetics studies.</p> <p>Methods</p> <p>RFLP assays were used to genotype <it>CYP2C8 </it>(<it>*2</it>, <it>*3</it>, <it>*4</it>) variant alleles in 204 unrelated Ghanaians. <it>CYP2C9*2 </it>and <it>CYP2C19 </it>(<it>*2 </it>and <it>*3</it>) variants were determined by single-tube tetra-primer assays while <it>CYP2C9 </it>(<it>*3, *4, *5 </it>and <it>*11</it>) variants were assessed by direct sequencing.</p> <p>Results</p> <p>Allelic frequencies were obtained for <it>CYP2C8*2 </it>(17%), <it>CYP2C8*3 </it>(0%), <it>CYP2C8*4 </it>(0%), <it>CYP2C9*2 </it>(0%), <it>CYP2C9*3 </it>(0%), <it>CYP2C9*4 </it>(0%), <it>CYP2C9</it>*5 (0%), <it>CYP2C9*11 </it>(2%), <it>CYP2C19*2 </it>(6%) and <it>CYP2C19*3 </it>(0%).</p> <p>Conclusion</p> <p>Allele frequency distributions for <it>CYP2C8</it>, <it>CYP2C9 </it>and <it>CYP2C19 </it>among the Ghanaian population are comparable to other African ethnic groups but significantly differ from Caucasian and Asian populations. Variant allele frequencies for <it>CYP2C9 </it>and <it>CYP2C19 </it>are reported for the first time among indigenous Ghanaian population.</p