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.

Patient-centred tuberculosis treatment delivery under programmatic conditions in Tanzania: a cohort study.

BACKGROUND: Directly observed therapy (DOT) remains the cornerstone of the global tuberculosis (TB) control strategy. Tanzania, one of the 22 high-burden countries regarding TB, changed the first-line treatment regimen to contain rifampicin-containing fixed-dose combination for the full 6 months of treatment. As daily health facility-based DOT for this long period is not feasible for the patient, nor for the health system, Tanzania introduced patient centred treatment (PCT). PCT allows patients to choose for daily DOT at a health facility or at their home by a supporter of choice. The introduction of fixed dose combinations in the intensive and continuation phase made PCT feasible by eliminating the risk of selective drug taking by patients and reducing the number of tablets to be taken. The approach was tested in three districts with the objective to assess the effect of this strategy on TB treatment outcomes METHODS: Cohort analysis comparing patients treated under the PCT strategy (registered April-September 2006) with patients treated under health-facility-based DOT (registered April-September 2005). The primary outcome was the cure rate. Differences were assessed by calculating the risk ratios. Associations between characteristics of the supporters and treatment outcomes in the group of patients opting for home-based DOT were assessed through logistic regression. RESULTS: In the PCT cohort there were 1208 patients and 1417 were included in the historic cohort. There was no significant difference in cure rates between the cohorts (risk ratio [RR]: 1.06; 95% confidence interval [CI]: 0.96-1.16). In the PCT cohort, significantly more patients had successful treatment (cure or treatment completed; RR: 1.10; 95%CI: 1.01-1.15). There were no characteristics of supporters that were associated with treatment outcome. CONCLUSION: The PCT approach showed similar cure rates and better treatment success rates compared to daily health-facility DOT. The results indicate that there are no specific prerequisites for the supporter chosen by the patient. The programmatic setting of the study lends strong support for scaling-up of TB treatment observation outside the health facility.