Efficiently retrieving relevant evidence from databases is crucial for knowledge syntheses, particularly for underrepresented or hard-to-define populations. This panel explores the development, validation, and use of search filters for locating research on specific demographic groups, such as age groups, minority populations, or workers in particular settings. Through three presentations and an interactive conversation with the panelists, we will discuss how and when to use validated and unvalidated search filters to improve retrieval efficiency for evidence relating to the health of population groups. We will discuss the principles of filter design, focusing on terminology, inclusion/exclusion criteria, and balancing sensitivity and precision. Through examples of validated filters for minority populations, we will explore how to design filters to reduce irrelevant results while maintaining inclusivity for evolving terminology. We will review methods to ensure relevance and accuracy, including insider input, pilot testing, relative recall from published reviews, and flexibility in updating for different purposes or projects. Practical applications in academic, clinical, and policy contexts will be addressed, alongside challenges like evolving language, limited metadata specific to the population, and translating filters for use in different search interfaces. We will also discuss how information specialists share filters through publication and repositories. Inspired by resources such those provided by ISSG and the University of Alberta Library, we suggest options for finding, adapting, and citing search filters. By covering both theoretical foundations and practical applications, this panel aims to improve the retrieval of population-specific health evidence, offering tools to better serve diverse populations in healthcare and social research.