Preventable Adverse Drug Reactions – Meta-Analysis the individual studies was applied, as no consensus on quality scoring of observational epidemiological studies exists [21]. Statistical analysis Meta-analysis was performed using DerSimonian and Laird random effect model with the estimate of heterogeneity being taken from the inverse variance fixed effect model [22]. The summary measures for the percentage of patients with PADRs and for the preventability of ADRs were calculated separately for ADRs occurring in outpatients and for ADRs present among inpatients during hospitalisation. Studies on the elderly were analysed separately. For the percentage of patients with PADRs, we first converted the individual percentage estimates to logit to meet the normal distribution assumption, conducted the analysis on the logit and converted the final results into non-logit for interpretation. Preventability estimates were calculated without converting them into logit in the analysis, because overall estimates using direct and logit methods differed less than one percentage when they were compared. Confidence intervals (95%) for each summary measure were calculated. STATA software version 10 was used for data analysis. To investigate the robustness of the overall estimates, we conducted sensitivity analyses. Each analysis was conducted separately for studies with less than six months’ study period and with six months’ or longer study period, because studies with longer study periods may more likely include revisits of the same patients. Moreover, outlier studies whose estimates differed 20% or more from the overall estimate were omitted from each analysis. We also assessed the possibility of publication bias by evaluating funnel plots. No asymmetry was evident. Heterogeneity was explored using Cochrane’s Q test of heterogeneity and I2 statistics. Figure 2. Flow diagram of the selection of eligible studies on preventable adverse drug reactions (ADR). doi:10.1371/journal.pone.0033236.g002 PLoS ONE | www.plosone.org 3 March 2012 | Volume 7 | Issue 3 | e33236