Science strives to provide high-quality evidence for all members of society, but there continues to be a considerable gender and diversity data gap, i.e., a systematic lack of data for traditionally underrepresented groups. Gender and other diversity domains are related to morbidity, mortality, and social and economic participation, yet measures as well as evidence regarding how these domains intersect are missing. We propose a brief, efficient Diversity Minimal Item Set (DiMIS) for routine data collection in empirical studies to contribute to closing the diversity and gender data gap. We focus on the example of health but consider the DiMIS applicable across scientific disciplines.