College of Graduate Studies
Clinical Biostatistics | Introduction to Basic Analytics | Comparative Effectiveness Research | Clinical Epidemiology | Ethical Issues in Clinical Research | Leadership | Critical Review | Introduction to Clinical Trials | Regression Methods for Clinical Research | Grants Overview | Data Management for Clinical Research | Core Clinical Research Training | Industry/Regulatory | Community Engagement Research | Student Research
This course is intended to develop an informed consumer of biostatistics rather that an independent analyst, and is primarily application based with less emphasis on theoretical underpinnings. Although the technicalities of how to solve statistical problems remains an important skill set, the focus is directed more toward the goal of why certain statistical tests are appropriate, and when they are most effectively employed. The student spends fewer hours learning statistical programming in order to complete mathematical homework problems, and more time on problem solving applications that demonstrate the students’ understanding of the use of the specific biostatistical tool.
As the student progresses through the course, the problems will become more complicated requiring the repeated demonstration of competency of earlier material. The problem sets employ vignettes to challenge the student to think about the reasons behind the selection of specific tests over alternatives. In addition to the problem solving component, there are application based segments that challenge the student to develop comprehensive analytic plans to address an array of clinical and translational applications.
This course is not a standalone course in statistics, but is meant to be used in conjunction with the Biostatistics and Regression courses. This course will provide means for students to perform advanced statistical computing, and acquire a further understanding for data analysis and data application. Students will be introduced to the SAS programming language, a skill that is truly invaluable in the clinical research industry and other research fields.
CER is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition or to improve the delivery of care. The purpose of CER is to assist consumers, clinicians, purchasers, and policy makers to make informed decisions that will improve health care at both the individual and population levels.
This course is focused on design and measurement issues for three of the four types of study designs:
1. Systematic Review
2. Database Review
3. Prospective Observational Study
This course will also cover the approaches used for interpretation and translation of CER data through decision models to compare the cost effectiveness of treatments. Decision analysis models are predictive mathematical models that are used to structure CER and cost data to help inform evidence-based decision choices.
The following topics are include in the course:
1. A review of research designs and statistical methods for outcomes research
2. Measurement of efficacy, effectiveness, opportunity cost, and quality of life
3. Benchmarks for economic value, cost effectiveness, cost utility, and budget impact
4. Mathematical approaches for estimating expected outcomes: decision trees, Markov and simulation/estimation with regression
The course is designed for clinical researchers who have an identified area of interest in medical condition or a treatment approach. Most course assignments require the student to have a clinical focus area to which they can apply the course topics and designs. The design and construction of a decision model in an area of interest to the individual student is required.
This course is intended to focus on issues unique to the application of epidemiological principles in the clinical and translational research arena. This course will be taught with an approach that acknowledges that the epidemiological needs of the interdependent clinical researcher are fundamentally different from graduate students in biostatistics or epidemiology. There will be emphasis on execution of epidemiological techniques as they apply to clinical and translational research. Epidemiology provides the framework within which scientific discovery originates, is replicated and validated. These essential applications are the foundation for scholarly advances in clinical research. This new course will focus heavily on applications of epidemiological principles in clinical and translational research. There will be extensive exposure to the use of quasi-experimental and observational clinical trials.
An emphasis will be placed on the ethical issues associated with research and practice in all aspects of biostatistics, bioinformatics and epidemiology. The process of assessing ethical issues in research and study will be described. The ethical considerations in study design; study implementation, data management, data analysis, data interpretation and results presentation and publication will be described. As future educators, the students will be presented with the honor council process, assessment process for unethical classroom and study behavior, and the process for behavior modification and remediation. The ethical considerations involved with collaborative research will be presented.
This course was developed expressly for the MSCR program to emphasize the skills and personalities of successful leaders in academic medicine with emphasis on promoting the clinical research environment.
Leadership is examined from the perspective of Executive Leadership in Academic Medicine as it applies to the interdependent research team leader. While the past goal of the MSCR program was to singularly train the independent clinical researcher, the contemporary program expands on that to include formal training in leadership – with the expectation that our graduates will become leaders in their respective national specialty societies, leaders in academic medicine research, leaders in academic medicine administration, and effective mentors to students, residents, fellows, and junior faculty.
During this course, an emphasis will be placed on the competencies and processes necessary to review the scientific literature. In particular, the students will review the published and unpublished literature associated with clinical research results. The focus of the class will be the review of the types of scientific and clinical research manuscripts papers and reports produced from different study approaches. The course will identify resources for the critical review of the scientific literature. The considerations and criteria for critical review of the literature will be addressed in the course. Students will prepare written critiques of selected literature and manuscripts.
This is a comprehensive course in the design and conduct of clinical trials. The course will cover:
1. The various types of clinical trials
2. Study design (including sample size estimation)
3. Randomization methods and implementation
4. Project and data management
6. Issues in data analysis (e.g., intent-to-treat; missing data analysis).
Both clinical and basic science investigators can benefit from this course, provided they have the required background in statistics obtained from the Biostatistics and Basic Analytics courses.
This course covers regression analysis, a method for investigating functional relationships among variables. You will learn to evaluate the fit using statistics such as t, F, and R2, but you will also learn informal analysis based on uncovering patterns in the data. The emphasis is on exploratory data analysis rather than on statistical theory or formula derivation. We will rely heavily on graphical representations of the data and make use of plots of regression residuals. Concepts and techniques of regression analysis will be taught based on carefully developed examples. This course is intended for anyone involved in analyzing data, but who does not specialize in statistics. We will use computer software (mainly SAS) to examine data output, but you will only be required to read and understand the output. You are not responsible for computer programming.
By the conclusion of the course, students will be able to:
1. Know which regression technique is appropriate in given situations
2. Read computer printout to interpret results
3. Examine model fit using graphs and plots as well as statistical tests
4. Be knowledgeable in seeking help for more complex problems
This course will function as an interactive description of the research grant mechanisms, application process, review process and implementation. The different types of grants will be presented and the details of the application and peer review. The source of funding will be described. Students will learn on overview of the types of grants, potential funding sources, how to get started and resources available.
This course is intended to introduce clinical researchers to research oriented data management and related basic topics in Informatics. Students taking this course will learn about basic concepts in clinical research, data management, best practices, relational database design, modern research data capture tools, clinical data warehousing, security risks and mitigations, privacy issues in electronic data, data standards, data mining and other related topics. Students will get hands-on experience with using modern database tools to solve specific scientific problems by attending the course labs.
By the conclusion of the course, students will be able to:
1. Recognize good practices for clinical data management
2. Understand the concept of relational databases
3. Recognize the differences between and needs for research databases and data warehouses
4. Create a database appropriate for a given scientific project using modern desktop and online tools
5. Recognize associated privacy and security risks in electronic data management and the tools to mitigate them
6. Understand regulatory needs related to electronic clinical research data
7. Determine appropriate use of data management
The purpose of the Core Clinical Research Training is to prepare participants to coordinate cost-effective health care research which protects the rights and safety of human subjects, achieves recruitment and retention outcomes and contributes to the science of health care. Participants completing the training will be prepared to coordinate research studies in compliance with the Good Clinical Practice Guidelines and federal regulations concerning human subject research.
Upon completion of the training, participants will have the information to be able to:
1. Manage the day-to-day activities required of a study coordinator of human research protocols in order to ensure compliance with federal regulations, IRB policies and Good Clinical Practice Guidelines
2. Recruit, enroll, and retain satisfied, informed research subject
3. Organize efficient documentation systems and ensure reliable results on schedule within budget
4. Identify those agencies that regulate the conduct of human research and the resources available to answer questions
5. Ensure appropriate and timely required communication with sponsors, CROs, principal investigators, the IRB and subjects
6. Collaborate effectively with principal investigators, the IRB personnel and other health care professional
7. Prepare for and participate in internal and external study audits
8. Identify the essential elements of an informed consent document that complies with the MUSC IRB Informed Consent Guidelines and the federal regulations governing the informed consent process
The objective of this course is to provide an introduction to working with industry and to provide a nuts-and-bolts program on performing a clinical trial. The students will have been expected to have had education regarding clinical trials, such as study design, and this course will provide detailed descriptions of all of the steps in actually performing a clinical trial. Students will learn about the path from drug discovery to drug approval, including drug development, regulatory affairs, and clinical trials management. Although the focus will be on drug development, there will be discussion about biologics and devices as well. Students will acquire analytical and communication skills suitable for managerial and staff positions in clinical research, clinical trials, contract research organizations, and federal agencies for regulatory affairs (e.g., FDA).
Community engagement is an important element to the successful translation of research from bench to bedside and community. “Community-engaged research (CEnR) is an approach to conducting research that requires partnership development, cooperation and negotiation, and commitment to addressing health issues of the community of interest. At the heart of all CEnR is the understanding that community members will be involved in some meaningful way in the research process.
This course provides a foundation for incorporating the principles of community engagement in the development of community-academic research partnerships and implementing best practices of CEnR. Topics include community interaction, partnership development, ethics and responsible conduct in community-engaged research, strategies to engage communities across all phases of the research process, and community-based dissemination.
By the conclusion of the course, students will:
1. Understand the principles, components, and theoretical basis of community-engaged research
2. Identify ways to demonstrate cultural humility when interacting with socially and culturally diverse communities
3. Understand the influence of social determinants on health and well-being
4. Identify strategies to engage community members in the development and implementation of research studies
5. Identify multiple communication and dissemination strategies across diverse audiences for community-engaged research
6. Identify and analyze ethical issues in community-engaged research
7. Describe the benefits and challenges of community-academic partnerships in research
Students are provided with the opportunity to conduct individual research with the assistance of a board of 4 advisors and a mentor chosen by the students and approved by the program director along with the board. Here, students will apply the methods of literature reviews, statistical analyses, study formulation and design, and ethics. Final research protocols will be submitted upon the completion of the 38 credit hour program.