Skip course categories
Skip available courses
Students in BIOT 5101 will present a research paper or their thesis research progress to faculty and peers. Each student enrolled in BIOT 5331 or BIOT 5332 must present a paper of his/her research each semester enrolled as scheduling permits. Seminars are formal PowerPoint presentations. Students in BIOT 6101 will present their thesis research progress to faculty and peers. Each student enrolled in BIOT 6331 or BIOT 6332 must present his/her research each semester enrolled as scheduling permits. The student should have a committee meeting following the seminar. Seminars are formal PowerPoint presentations in preparation for a thesis defense.
This course exposes students to current research published in major scientific journals. Students will learn how to read and interpret methodologies and results published by other scientists. Although this is the second of a two-course sequence, the first course (Critical Reading I) is not a prerequisite. This course is team taught with a different instructor facilitating the discussion each week on a topical paper of choice.
Credit hours: 1 Class meets: Tue 9:00 a.m. - 10:00 a.m. Room: 116.1 Semester: Fall
- Teacher: Buka Samten
Independent study of an emerging technique or technology in the field of biotechnology.
- Teacher: Torry Tucker
An introduction to standard molecular biology techniques such as isolation and purification of proteins and nucleic acids, cloning and expression of recombinant proteins with laboratory component. Co-requisite: BIOT 5211L
Lab component. An introduction to standard molecular biology techniques such as isolation and purification of proteins and nucleic acids, cloning and expression of recombinant proteins with laboratory component. Co-requisite: BIOT 5211
Designed for students desiring research projects directed by Biotechnology faculty, to provide an orientation into the research laboratory workplace, to master fundamental laboratory techniques, to develop skills in planning a laboratory project and to present their work in both an oral and written context.
Graduate-level course of biotechnological aspects of gene expression, transcription control mechanisms; molecular cloning, and its applications to biotechnology at the molecular level. The student will gain a thorough understanding of fundamental molecular biochemical principles used in biotechnology, including basic background information, theory and applications.
- Teacher: Pierre Neuenschwander
A comprehensive study of molecular biology applications and techniques as they relate to biotechnology. The topics covered in this course include mRNA isolation and Northern blotting, gene cloning, mutation of DNA, real-time quantitative PCR, bioinformatics, expression of recombinant proteins, large-scale production of proteins through fermentation and generation of transgenic animals.
A required residency/internship provides an opportunity for each student to work in a health administration settings in a position that carries responsibility. A minimum number of hours of effort is expected during the semester to satisfactorily complete the course (as per the instructor).
- Teacher: Patricia Royal
Class Meets: Wed., 6 - 9 p.m.
Format: Fully online with first week face-to-face or synchronous online; second week asynchronous online. May require two face-to-face class sessions. This class alternates with PBHL 5330.
- Teacher: Kimberly Elliott
Healthcare professionals benefit from having the knowledge and skills necessary to make informed decisions regarding health services. This course is intended to introduce the foundation of knowledge and skills students need to understand the conceptual and methodological issues of health research methods. Topics include but are not limited to: study conceptualization; research question and hypothesis formation; fundamentals of sampling, observation and measurement; research design and operationalization; secondary data analysis widely used in empirical health services research; interpreting research literature; and the capacity to translate knowledge into action.
Class Meets: Tues., 6 - 9 p.m.
Format: Fully online with first week asynchronous online; second week face-to-face or synchronous online. May require two face-to-face class sessions. Thursday delivery in Richardson 5:30 - 8:30 p.m. This class alternates with HPEM 6310.
- Teacher: Jessica Escareno
This course examines operational issues in healthcare management. Topics include systems analysis, continuous quality improvement and re-engineering, demand forecasting, facility location and design models, decision analysis techniques, linear programming, queuing and waiting models, inventory control models and statistical quality control. The goal is to instill an understanding of the language applications and limitations of quantitative models regarding decision-making and problem-solving in healthcare organizations.
Class Day: Monday, 6 - 9 p.m. Format: Fully Online (First Week Face to Face or Synchronous Online; Second Week Asynchronous Online) May require two Face to Face class sessions.
- Teacher: Michael Kennedy
This course focuses on functions and concepts required for managing human resources in organizations. It combines traditional human resource management (HRM) functions with concepts from organization behavior. Course content includes selection, training and development, compensation, performance appraisal, motivation, organization development, union activity and modes of conflict resolution.
This course presents the knowledge, infrastructure, functions and tools of health informatics. It explores technology, planning and management and applications in public health and healthcare. The emphasis is on conceptual frameworks as well as a deeper level of engagement on system applications. It focuses on the application of health technology. It is designed to familiarize students with core concepts and issues confronting managers in the health sector associated with planning, implementation and evaluation of information systems. The course provides an overview of the theory, processes and application of information systems and how they relate to health policy and management. It also provides a basic understanding of data standards and requirements, and the critical concepts and practice in mapping and interpreting health information.
This course will develop the foundations of quality and process improvement that lead to higher levels of efficacy, efficiency and effectiveness in health organizations and programs. This course will explore the basis of Quality Improvement (QI) consisting of systematic and continuous actions that lead to measurable improvement in health care services and the health status of targeted patient groups. The methodology of the course will begin with “how things are done now,” considering health care performance as defined by an organization's efficiency and outcome of care, and level of patient satisfaction. Quality is directly linked to an organization's service delivery approach or underlying systems of care throughout the continuum of care. The student will understand that to achieve a different level of performance (i.e., results) and improve quality and efficacy, an organization's current system needs to change. Lastly, this course will focus on a successful QI culture that incorporates the following four key principles: QI work as systems and processes; Focus on patients and community groups, especially rural areas; Focus on being part of the team, and Focus on use of the data and analyses of information.
Credit Hours: 3 Semester: Fall
This course focuses on learning key concepts and techniques related to healthcare reimbursement, employed provider contracting and operational budgeting. This knowledge will be applied to case-based lesson modules. Course content is divided into three sections: value and reimbursement, employed provider contracting and operational budgeting. Traditional and emerging payment models and compensation models for employed physicians will be discussed in depth from the provider perspective. Different techniques and their uses in operational budgeting will be covered.
This course offers an introduction to strategic planning and management in health services organizations. Processes and formats employed in strategic planning and marketing are presented and applied in case studies and a final project. Elements of market assessment, environmental analysis and strategy development are presented and applied to course practices.
Given the integration of data, community needs and regulation and policy, this course incorporates the elements of healthcare, public health, health information technology and the health insurance sub-industries to develop a framework and analytic methods to improve efficiency, effectiveness and efficacy of the health industry as a whole.
The course will establish an analytic framework, based on data from patients, populations, processes and profitability (4 P's of Health Analytics) utilizing industry, healthcare enterprise and community health data with appropriate tools, methods and approaches to answer community health needs and status, operational, financial and healthcare delivery outcomes questions to support leadership decisions. The course will also include an integrated platform of appropriate analytical and predictive/estimation methods, tools and techniques for enhanced decision making at the strategic and operational levels of the health enterprise for enhanced health status and improved health outcomes of communities served.
Credit Hours: 3 Class Meets: Tues, 5:30 - 8:30 p.m. Semester: Summer
COMH 6330 is intended to provide MPH students with a solid foundation and understanding of research methods and topics with enhanced capacity to produce and critically appraise public health research and literature. Students will learn the basic concepts and procedures to conduct evidence-based research addressing behavioral/social determinants of health. The course provides a concrete knowledge base to design conceptually sound and methodologically rigorous research proposals and/or evaluate behavioral/social interventions addressing public health problems. It covers a wide range of methodologies from observational studies to randomized controlled trials and non-randomized evaluations. The emphasis will be on developing a methodological literacy that allows students to understand the strengths of various methods and their common uses in public health research.
- Teacher: Yordanos Tiruneh
- Teacher: Christiana Osuagwu
This course provides instruction and hands-on experience in the analysis and interpretation of data from epidemiologic studies. Topics to be covered include epidemiology research questions that can be addressed by case-control and cohort studies, the rationale underlying the major techniques used to analyze data from case-control and cohort studies, the conditions under which these methods are appropriate, and their relative advantages and disadvantages. Attention will be given to how interactions, confounders and nonlinear relationships among variables can be addressed along with interpretation of statistical software output from epidemiologic studies employing these designs and analytical methods.
Epidemiology is the study of the distribution and determinants of health in populations and the application of this study to improve health outcomes. It is the basic science of public health. Epidemiology I is an introductory level. By the end of this course, the student will be able to define the content, uses and significance of epidemiology as a means of public health investigation; describe epidemiological approaches to defining and measuring health problems in defined populations; describe the strengths and limitations of epidemiological study designs; explain the contributions of epidemiological approaches to disease prevention, health promotion and health policy; and describe the role of epidemiological approaches in evaluating the effectiveness and efficiency of health care and preventive health services.
This course presents basic statistical concepts and methods commonly used to make evidence-based decisions in business settings, with a focus on healthcare applications. This course will cover commonly used statistical tools needed by healthcare executives. During the course, techniques to collect, summarize, analyze, and interpret business-related data will be reviewed. Topics in this course may include defining and formulating problems, formulating and testing hypotheses, sampling and sampling distributions, creating descriptive statistics, statistical inference and using the results to make decisions.
Credit Hours: 3 Class Meets: Tues., 6-9 p.m. Rotation: ODD Semester: Spring 2020
Credit hours: 3 Class meets: TBD Semester: TBD
- Teacher: Kevin Moore
This is an introduction to environmental and occupational health with an emphasis on various levels of prevention and the scientific application of regulatory principles. Evaluation methods and general aspects of control measures relative to human health will also be explored. At the end of the course the student will have been acquainted with the history and basic principles of occupational and environmental health programs and how they relate; be able to review relevant legal, ethical, and regulatory issues pertinent to occupational and environmental health; and be familiar with the basic tools utilized in the evaluation of occupational and environmental health issues such as epidemiology and statistics, industrial hygiene, occupational health nursing, and toxicology.
- Teacher: Yordanos Tiruneh
- Teacher: Michael Kennedy
- Professor: Cynthia Ball
- Professor: Michele Bosworth
- Professor: Noah Burwell
- Professor: Sonja Bush
- Professor: Matt Cope
- Professor: Jerry Ledlow
- Professor: Jeffrey Levin
- Professor: Paul McGaha
- Professor: Pierre Neuenschwander
- Professor: Mickey Slimp
- Professor: Mickey Slimp
- Professor: Martha Weatherly
- Professor: Kent Willis
Grantsmanship: Getting the Competitive Edge. A slideshow adapted from a PowerPoint presentation given by Dr. Steven Idell to the BMR Faculty on Jan 28, 2003.
Use the enrollment key "Grantsmanship" to self-enroll.
All data and forms to assist faculty in advising.
The course offers an in-depth practical and conceptual approach to fundamental statistics.The course consists of learning a variety of procedures commonly used for testing hypotheses, learning to examine and analyze the data accordingly, and learning to communicate the research results to others. By the end of the course the student will be able to create a database, properly code and screen data and present results (SPSS or another statistical software package); determine and describe the strength of association and direction of relationships between two or more variables by identifying and computing appropriate statistical tests, such as chi-square statistics, correlation coefficients, and linear regression models and by writing up results; examine and present significant mean differences between and within groups by identifying and computing appropriate statistical tests, such as t-tests and analysis of variance models (ANOVA) and by writing up results.
Credit hours: 3 Class meets: Tue 6 p.m. - 9 p.m. Semester: Spring 2019
- Professor: Cynthia Smith