Dual Degree: BSHS in Clinical Research Administration / MSHS in Biomedical Informatics- Curriculum

Overview of health communication research, theory, and practice, examining the powerful communication influences on delivering care and health promotion. 

The student explores the different phases of drug and device development and introduces basic concepts such as benefit-risk assessment, the different stakeholders, protocol, informed consent, clinical oversight, institutional review board, Good Clinical Practice (GCP), investigational clinical supplies, data management activities, safety reporting, and monitoring.

The student examines the process steps and regulatory requirements governing the development and registration of investigational new products from different stakeholder perspectives as well as the steps and requirements in the conduct of a clinical trial for an investigational new drug or device while ensuring data integrity and human subjects protection.

The student analyzes the rationale and goals of Good Clinical Practice (GCP), and applies key principles within the context of case studies.

The student compares and contrasts the business priorities of sponsors, sites and third party vendors, such as contract research organizations (CROs); the student also examines the business considerations in preparing clinical trial budgets including outsourcing and potential trial delays.

The student analyzes and evaluates the basic principles and processes involved in the monitoring of clinical trials, as well as the required documentation such as monitoring visit reports; the student also examines the role of key participants with emphasis on the clinical research associate.

In this capstone course, students analyze business, ethical, cultural and practical aspects of clinical trial conduct; explore trends and technologies driving efficiencies in clinical trial performance and demonstrate how ethical and regulatory principles and trial management practices align to ensure quality and compliant clinical research conduct.

The cross-cutting nature of the social determinants of health and clinical and biomedical implications in practice and research settings. 

Biomedical and scientific framework for the understanding of human disease mechanisms and biologic processes. Overview of infectious, immunologic, cardiovascular, genetic, respiratory, gastrointestinal, neoplastic, reproductive, renal, hematologic, neurologic, and musculoskeletal diseases.

Basic issues, approaches, and requirements of ethically acceptable decision making with patients, including patient confidentiality, conflicts of interest, allocation of scarce resources, occupational risks in health care, and professional responsibility for overall quality of care.

Introduction to the health sciences literature Emphasis is on construction, evaluation and organization of written communication of health sciences information.

Foundational concepts in descriptive and inferential statistics, including probability, sampling distribution, estimation, correlation, t-Test, simple linear regression, and chi-square. Application of statistical concepts and methods within the health sciences.

Application of management and organizational principles to the delivery of services provided by health sciences disciplines Issues addressed include information systems, leadership, team building, fiscal management, human resources management, quality improvement, and management of conflict and change.

An introduction to epidemiological methods and their applications in the prevention and control of illness, community and clinical interventions, and health services. 

Includes a significant engagement in writing as a form of critical inquiry and scholarly expression to satisfy the WID requirement.

Introduction to the field of regulatory affairs to regulations, strategies, and laws that apply to safe and effective product development.

Medical informatics applications and innovations in health care and the health care system; implications for health care delivery and patient outcomes, including electronic medical records, health system databases, and medical data analysis.

Students examine leadership/leadership change theories in the healthcare industry setting, as well as management and communications strategies, and values in a systems framework. Theories and styles of leadership, including organizational management and values, strategic planning, communication strategies, managing change, and negotiating conflict in the context of the health care delivery system.

Students examine the major themes on healthcare policies, trends, and issues in the major health systems and research enterprise Students apply epidemiologic concepts in the context of translational research.

Analysis of medical informatics applications and innovations in health care and the health care system; implications for health care delivery and patient outcomes, including electronic medical records, health system databases, and medical data analysis. Restricted to graduate students. Recommended background: graduate enrollment in data science or related field.

Basic concepts and methods of biostatistics applied to translational research. Topics include distributions, populations and sample selection, variables, interaction and confounding, hypothesis formulation, correlation, t-tests, ANOVA, regression, and chi.

Students explore the basic concepts of epidemiology which includes various epidemiological study designs used to examine disease frequency, cause-effect relationships between risk factors and disease states, and effects of bias as examples. Students apply epidemiologic concepts in the context of translational research.

Survey of clinical medicine and basic concepts related to clinical process, medical vocabulary, anatomy, pathophysiology, and clinical disease management for selected organ systems and health care specialties; evaluation of medical records, clinical decision making, and health providers in the U.S. health care system. Laboratory fee. Restricted to graduate students. Recommended background: graduate students in the data science program or those with prior undergraduate coursework in general biology or anatomy and physiology or pathophysiology. Credit cannot be earned for this course and INFR 4102.

Health care quality theory, principles, and practice for medical informatics professionals. Restricted to students in the biomedical informatics program.

Applied contemporary concepts and practice in high performance computing for scientists; systems, resource management, parallel programming, and nationally shared resources Proctor fee Prerequisites: INFR 6101, INFR 6102, and HSCI 6263 (or equivalent statistics course.) Recommended background: graduate students in biomedical Informatics programs.

Supervised field work in biomedical informatics arranged in consultation with the program director. Students must have completed 9 credits of graduate INFR coursework and have program approval in order to enroll May be repeated for credit Prerequisites: graduate students in biomedical Informatics programs.

Capstone project for biomedical informatics arranged in consultation with the program director. Students must have completed 12 credits of graduate INFR coursework and have program approval in order to enroll May be repeated for credit Recommended background: graduate students in biomedical Informatics programs.

Clinical decision support systems (CDSS) used in biomedical informatics to assist health care providers with decision making tasks related to patient care and associated quality improvement efforts. Artificial intelligence in medicine Restricted to students in the biomedical informatics program Prerequisite: INFR 6121.

Writing grant proposals to fund clinical research, with an emphasis on translational research proposals Emphasis is on persuasive communication, conceptually based hypotheses and research methods and the grant application process, including communicating.

The bioinformatics tools for different analytical situations. Strengths and limitations of the most common bioinformatics strategies. Principally limited to analysis of genomic data, the course is planned to enable students to generalize the acquired knowledge and its underlying principles and techniques to other types of ‘big data’ applications for the purpose of interpretation of results.

The course examines advanced scripting skills in the context of biomedical informatics. This is a programming course utilizing current language for applied systems. Proctor fee Prerequisites: HSCI 6263, INFR 61n/a1 and INFR 61n/a2. Recommended background: graduate students in biomedical Informatics programs.