FOUNDATIONS OF DATA-DRIVEN HEALTHCARE

Prerequisites & course information

Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Utilize informatics-based tools in translational research including locate relevant informatics tools; select appropriate informatics tools; and use those tools in research for managing and analyzing biomedical and health information. Audience: Graduate 2. Describe the essential functions of the major clinical systems ( e.g., the EHR-- (electronic health record and its feeder systems, such as radiology and lab) that are relevant to healthcare analytics and quality improvement and the challenges to using these data for research. Audience: Graduate 3. Explain the role of health information technology standards in the interoperability of research, clinical, and administrative information systems and on secondary use of data for Clinical Translational Research or CTS. Audience: Graduate 4. Describe the essential information generation, management, analysis, transformation, summarization, and visualization methods that apply to healthcare analytics and quality improvement, such as clinical data; imaging data; consumer and patient reported data; and population-level and environmental exposure data. Audience: Graduate 5. Identify and describe available methods for handling large-scale data for machine learning and medical language processing. Audience: Graduate 6. Illustrate the nature of the contributions in consulting and/or collaborating with biomedical and health informaticians throughout the life cycle of clinical and translational research projects: use the terminology and principles of biomedical informatics; discriminate among the different subdomains of biomedical informatics; and enumerate the roles of biomedical informatics specialists. Audience: Graduate 7. Identify how structure and organization of information in a domain can affect quality research foci through fundamental data categories and elements, terminologies and taxonomies, and ontologies. Audience: Graduate 8. Identify, retrieve, and manage biomedical and health science knowledge through literature searches using advanced search techniques (MeSH, PubMed, Google Scholar, etc.). Audience: Graduate 9. Discuss the fundamental principles and practices that address the ethical, legal, social, privacy, and security implications of bio- medical and health informatics. Audience: Graduate Learning Outcomes: 1. Utilize informatics-based tools in translational research including locate relevant informatics tools; select appropriate informatics tools; and use those tools in research for managing and analyzing biomedical and health information. Audience: Graduate 2. Describe the essential functions of the major clinical systems ( e.g., the EHR-- (electronic health record and its feeder systems, such as radiology and lab) that are relevant to healthcare analytics and quality improvement and the challenges to using these data for research. Audience: Graduate 3. Explain the role of health information technology standards in the interoperability of research, clinical, and administrative information systems and on secondary use of data for Clinical Translational Research or CTS. Audience: Graduate 4. Describe the essential information generation, management, analysis, transformation, summarization, and visualization methods that apply to healthcare analytics and quality improvement, such as clinical data; imaging data; consumer and patient reported data; and population-level and environmental exposure data. Audience: Graduate 5. Identify and describe available methods for handling large-scale data for machine learning and medical language processing. Audience: Graduate 6. Illustrate the nature of the contributions in consulting and/or collaborating with biomedical and health informaticians throughout the life cycle of clinical and translational research projects: use the terminology and principles of biomedical informatics; discriminate among the different subdomains of biomedical informatics; and enumerate the roles of biomedical informatics specialists. Audience: Graduate 7. Identify how structure and organization of information in a domain can affect quality research foci through fundamental data categories and elements, terminologies and taxonomies, and ontologies. Audience: Graduate 8. Identify, retrieve, and manage biomedical and health science knowledge through literature searches using advanced search techniques (MeSH, PubMed, Google Scholar, etc.). Audience: Graduate 9. Discuss the fundamental principles and practices that address the ethical, legal, social, privacy, and security implications of bio- medical and health informatics. Audience: Graduate