Background: Systematic reviews of measurement properties of outcome measures are important tools for evidence-based instrument selection. Furthermore, they are important tools for Cochrane reviewers because they offer an overview of the quality of outcome measures used in clinical trials. Sensitive search strategies for finding studies on measurement properties have not yet been developed. Objectives: To develop a sensitive search strategy for finding studies on measurement properties of outcome measures in PubMed. Methods: A random sample of 10,000 records was drawn from Pubmed (from 1990 onwards) as a representation of the literature. This set was used as a reference set. From this set, we excluded publications types other than original research, such as editorials, reviews, comments, and we excluded animal research. The remaining set was handsearched (title and abstract) for studies on measurement properties. Three sources were used to select search terms: relevant MeSH headings and textwords from the relevant articles in the reference set; relevant terms from title and abstracts of the relevant articles in the reference set; relevant terms from the search strategies and full-text of 100 existing systematic reviews on measurement properties. Sensitivity and precision were determined of all individual terms. The filter was developed by combining terms, starting with the terms with the optimal combination of sensitivity and precision. The filter was evaluated by calculating sensitivity, specificity, precision, and number needed to read. The final search filter was validated in three existing searches from published systematic reviews of measurement properties. Results: We found 116 studies on measurement properties in the reference set. The most sensitive filter was able to identify 113 of these studies (sensitivity 97%, precision 4%). A more precise filter was also developed with a sensitivity of 93% and a precision of 9%. Validation is ongoing, and the results will be presented at the Colloquium. Conclusions: A highly sensitive search filter was developed for finding studies on measurement properties of outcome measures in PubMed.