Electronic health records (EHRs), data analytics, predictive modeling, artificial intelligence (AI), speech recognition, and natural language processing create massive volumes of information that can improve quality, safety, and health outcomes. Yet competencies to utilize big data and advanced analytics are constrained by the lack of knowledge and skills to support the use of these datasets by faculty and researchers in behavioral, health professions, public health, and nursing sciences. The University of Texas at Tyler (UT Tyler) has established an Institute for Health Innovation, Data Science, and Research (IHI-DSR) to address these challenges. The IHI-DSR adopts an interprofessional collaborative model across all health schools. The IHI-DSR was established to: (1) support research and curriculum development in data science, secondary data analysis, and advanced analytics, and (2) provide interprofessional education and development opportunities for faculty, students, and researchers. The purpose of this paper is to outline a roadmap for success for innovation and data science labs and discuss the importance of key components of the roadmap to educate health care professionals and prepare faculty and researchers.
McBride et al. (2026) studied this question.