Translation and validation of a geographic search filter to identify studies about Germany in Embase (Ovid) and MEDLINE(R) ALL (Ovid)

We developed a geographic search filter for retrieving studies about Germany from PubMed. In this study, we aimed to translate and validate it for use in Embase and MEDLINE(R) ALL via Ovid. Adjustments included aligning PubMed field tags with Ovid’s syntax, adding a keyword heading field for both databases, and incorporating a correspondence address field for Embase. To validate the filters, we used systematic reviews (SRs) that included studies about Germany without imposing geographic restrictions on their search strategies. Subsequently, we conducted (i) case studies (CSs), applying the filters to the search strategies of the 17 eligible SRs; and (ii) aggregation studies, combining the SRs’ search strategies with the ‘OR’ operator and applying the filters. In the CSs, the filters demonstrated a median sensitivity of 100% in both databases, with interquartile ranges (IQRs) of 100%–100% in Embase and 93.75%–100% in MEDLINE(R) ALL. Median precision improved from 0.11% (IQR: 0.05%–0.30%) to 1.65% (IQR: 0.78%–3.06%) and from 0.19% (IQR: 0.11%–0.60%) to 5.13% (IQR: 1.77%–6.85%), while the number needed to read (NNR) decreased from 893.40 (IQR: 354.81–2,219.58) to 60.44 (IQR: 33.94–128.97) and from 513.29 (IQR: 167.35–930.99) to 19.50 (IQR: 14.66–59.35) for Embase and MEDLINE(R) ALL, respectively. In the aggregation studies, the overall sensitivities were 98.19% and 97.14%, with NNRs of 83.29 and 33.34 in Embase and MEDLINE(R) ALL, respectively. The new Embase and MEDLINE(R) ALL filters for Ovid reliably retrieve studies about Germany, enhancing search precision. The approach described in our study can support search filter developers in translating filters for various topics and contexts.