Precision medicine emerged as a promising approach to identify suitable interventions for individual patients with a particular health concern and at various time points. Technology can enable the acquisition of increasing volumes of clinical and "omics" data at the individual and population levels and support advanced clinical decision making. However, to keep pace with evolving societal realities and developments, it is important to systematically include sex- and gender-specific considerations in the research process, from the acquisition of knowledge to implementation. Building on the foundations of evidence-based medicine and existing precision medicine frameworks, we propose a novel evidence-based precision medicine framework in the form of the P32model, which considers individual sex-related (predictive [P1], preventive [P2], and personalized [P3] medicine) and gender-related (participatory [P4], psychosocial [P5], and percipient [P6] medicine) domains and their intersection with ethnicity, geography, and other demographic and social variables, in addition to population, community, and public dimensions (population-informed [P7], partnered with community [P8], and public-engaging [P9] medicine, respectively). Through its ability to contextualize and reflect on societal realities and developments, our model is expected to promote consideration of diversity, equity, and inclusion principles and, thus, enrich science, increase reproducibility of research, and ensure its social impact.