Master of Science (M.S.) in Health Informatics
College: College of Science and Health
Department: Nutrition and Public Health
Degree: Master of Science (M.S.)
Campus: Both Lisle Campus and Mesa Campus
Overview
Health Informatics is a growing specialization within the Public Health and Analytics fields. This degree is focused on training professionals to gain expertise in technology and systematic data-driven approaches to address community and population health issues. Data-driven approaches involving data collection, analysis, and informed interpretation can help improve public health processes and decision-making, whether one is identifying health trends, monitoring disease outbreaks, or informing public health programs or policies. Health informatics is an interdisciplinary field that draws on knowledge from analytics, computer science, information technology, healthcare, and public health principles to help address needs effectively within a range of work settings and in a variety of health-related careers.
Professionals with a background in public health can leverage their knowledge of health policy and population health to excel in health informatics roles, particularly in public health agencies and research institutions. Professionals with a background in analytics can add expertise in health systems to take on leadership roles in health informatics, whether in public health agencies, research institutions, or healthcare industry settings. Potential career paths include the following:
- Public Health Informatics Specialists: focus on using data and technology to address public health issues.
- Health Informatics Consultants: advise healthcare organizations on how to use data and technology to improve their operations and patient care as well as public health initiatives.
- Clinical Informatics Managers: lead clinical informatics teams.
- Data Analysts: analyze large datasets to identify population trends and patterns and to improve decision-making.
- EHR Implementation Specialists: help healthcare organizations implement and manage electronic health records systems crucial for data collection and sharing in public health.
Learning Goals for the M.S. in Health Informatics Program
- Demonstrate a thorough understanding of how to collect, store, and manage health data effectively, including database design and implementation.
- Analyze and visualize health data to identify trends and patterns.
- Forecast healthcare trends and improve operations.
- Apply informatics within various public health arenas, including disease surveillance, prevention, and intervention programs.
Program Structure
The M.S. in Health Informatics program requires the successful completion of 12 courses (including the Capstone), or 36 semester credit hours, earning at least a grade of “B” or better in each course. With careful planning, if students complete 2 classes each term (6 credit hours) over 6 consecutive terms (including the summer), the degree program can be completed within one year.
Program prerequisite: None
To apply for the M.S. in Health Informatics program, students should go to the university Application portal at https://ben.edu/apply/ and follow directions for Graduate admissions. Students will be requested to submit the following:
- Official transcripts from all previously attended colleges/universities.
Curriculum
Required Courses: 36 semester credit hours - 12 courses including Capstone (3 credit hours each); course sequence below is recommended. Students must earn at least a grade of "B" or better, in each course.
| Code | Title | Hours |
|---|---|---|
| BALT 5101 | Analytical Tools for Management Decisions | 3 |
| PBHL 5505 | Health Systems, Law and Policy | 3 |
| PBHL 5506 | Leadership and Management in Health Organizations | 3 |
| PBHL 5601 | Introduction to Health Informatics | 3 |
| BALT 5201 | Programming for Analytics | 3 |
| PBHL 5602 | Healthcare Information Systems | 3 |
| BALT 6102 | Business Analytics I: Predictive Analytics | 3 |
| BALT 6103 | Business Analytics II: Prescriptive Analytics | 3 |
| PBHL 5604 | Electronic Health Records | 3 |
| Select 2 of the following elective courses: | 6 | |
| Data Management for Business | ||
| Business Intelligence | ||
| Data-Driven Learning for Business | ||
| Analytics for Big Data | ||
| Data Visualization | ||
| PBHL 6900 | Health Informatics Capstone | 3 |
| Total Hours | 36 | |
BALT 5101 Analytical Tools for Management Decisions. The goal for this course is to prepare students to be more effective users of quantitative information, as well as to avoid the many potential pitfalls from the misuse of statistical methods. The emphasis is on understanding what a previously obtained data set implies and, if appropriate, to develop meaningful forecasts with a reasonable sense of confidence. Specific topics include data analysis and statistical description, sampling and statistical inference, time series, and regression analysis. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Fall, Spring, and Summer Terms)
MESA (Typically Offered: Fall, Spring, and Summer Terms)
MESA (Typically Offered: Fall, Spring, and Summer Terms)
BALT 5201 Programming for Analytics. The goal for this course is to introduce students, without prior programming experience, to essential programming concepts and techniques needed for analytics. The goal is to equip students with the necessary programming skills to be successful in other courses in the business analytics program. Examples are drawn from the problems often encountered in data analysis. Programming languages may include SAS, R, and Python. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
MESA (Typically Offered: Annually)
MESA (Typically Offered: Annually)
BALT 5251 Programming for Information Systems. Through the study of this course, students can understand the basic principles, new technologies and development trends of computer, master the use of common operating systems and application software skills, improve the application of network, multimedia and other technologies, understand the basic knowledge of information security and program design, and cultivate innovative consciousness and ability through practice. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 5351 Computer Organization and Architecture. This course takes digital circuit and logic design (basic part), computer composition (main part), computer architecture (advanced part) as the main line, focusing on the complete composition of computer systems and feasible ways to improve performance. Through the study of this course, students can systematically understand the basic principles of computer composition and internal operating mechanism, master the basic concepts and basic working principles of computer systems, and understand the hardware structure, interaction, and function of each main component. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 5451 Business Data Analysis. The purpose of this course is to have students master the basic concepts, related technologies of Business Data Analysis and its application status, application prospects and research directions in different data processing, and different rules extraction. After studying this course, students should understand and explain the following: 1) Data retrieval and preprocessing for business decision-making; 2) Understand data analysis and mining methods including Association Rules Mining, Classification and Prediction, and Cluster Analysis; and 3) Use popular data mining software to implement data analysis tasks. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6102 Business Analytics I: Predictive Analytics. Business analytics refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. It makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management to drive decision making. Analytics may be used as input for human decisions or may drive fully automated decisions. Deliverables may include article reviews, case analyses, software-based exercises, projects, and presentations. Cross-listed as MSBA 6659. Prerequisite: BALT 5101. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6103 Business Analytics II: Prescriptive Analytics. This course introduces the topics of optimization techniques for management decisions. Optimization is the process of discovering the best business solution from many feasible solutions using mathematical and statistical methods. The increasing complexity of today’s business decision-making has resulted in the development of many optimization techniques. These techniques have provided a wealth of solutions to facilitate business planning and execution. Optimization combines data transformation, mathematical model building, and optimization software with analytical tools to present the recommended solutions to planners and decision makers. Deliverables may include article reviews, case analyses, software-based exercises, projects, and presentations. Cross-listed as MSBA 6641. Prerequisite: BALT 6102. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6201 Data Management for Business. Database technology has evolved from simply being a better way to organize and access data to being an information systems keystone, required to effectively support the enterprise. This course introduces database technology, emphasizing effective database design. The course emphasizes effective database design, querying, and optimization techniques to ensure data integrity and accessibility. Through hands-on exercises and projects, students will gain practical experience in structuring and managing business data to support analytics-driven decision-making. By the end of the course, students will be able to design and manage data systems that enable data-driven insights across industries such as finance, healthcare, and retail. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6251 Big Data Management and Applications. The era of big data has been fully opened, and understanding the concept of big data and having big data thinking are the new requirements for talents in the new era. The course includes overview of big data, big data and cloud computing, Internet of Things and artificial intelligence, big data technology, big data application, big data security, big data thinking, big data ethics, data sharing, data opening, big data trading, and big data governance. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6261 Data Management. Database technology has evolved from simply being a better way to "organize and read data" to becoming the core technology of information systems management. Through this course, students should be able to understand and explain 1) the process required to effectively design a database, 2) how to design and implement a database program system by using relevant data management products (ACCESS, ORACLE, DB2, etc.), and 3) the basic structure of relevant data models and SQL language; 4) the composition, roles, and functions of the database environment, and the importance of data security, integrity, and recovery. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6301 Data-Driven Learning for Business. In today’s data-driven world, businesses leverage advanced analytical techniques to extract insights, predict trends, and optimize decision-making. This core course provides a comprehensive introduction to machine learning concepts and their applications in business. Students will explore key supervised and unsupervised learning techniques, including regression, classification, clustering, and decision trees, as well as modern advancements in deep learning. The course emphasizes the practical implementation of machine learning models to solve real-world business problems in areas such as marketing, finance, healthcare, and customer analytics.
Through a combination of hands-on projects, case studies, and industry applications, students will learn how to: 1. Preprocess and clean data for machine learning models, 2. Select and evaluate appropriate algorithms for different business scenarios, 3. Interpret and communicate model results to drive business strategy, and 4. Address ethical considerations and biases in machine learning applications.
By the end of the course, students will be equipped with the skills to apply data-driven learning techniques effectively, making them valuable contributors to data-centric decision-making in modern organizations.
Deliverables may include article reviews, case analyses, software-based exercises, projects, and presentations. Prerequisite: MNGT 6701. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
MESA
MESA
BALT 6401 Analytics for Big Data. This course introduces the concept of big data, that is, data sets so large that traditional relational database management systems, statistics, and visualization tools are insufficient. Organizations today are inundated with data, gathered from both inside and outside the organization. Analytics for data-at-rest and data-in-motion will be explored. The problem of solving problems which involve complex and structured data will be explored using the Hadoop platform. Deliverables may include article reviews, case analyses, software-based exercises, projects, and presentations. Cross-listed as MSBA 6686. Prerequisite: BALT 6201. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6501 Data Visualization. This course introduces data visualization, that is, communicating information clearly and effectively through graphical means. Visualization tools go beyond the typical tables, histograms, pie charts and bar graphs by displaying data in more sophisticated ways such as dials and gauges, geographic maps, time-series charts, tree maps, heat maps and detailed bar, pie and fever charts. The goal is to expose patterns that might not have been noticed otherwise. Visualized data is often displayed in business Intelligence dashboards which provide users with high-level views of corporate information and key performance indicators. Deliverables may include article reviews, case analyses, software-based exercises, projects, and presentations. Cross-listed as MSBA 6685. Prerequisite: BALT 6201. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6651 Information Systems Security. This course aims at the basic principles and technologies of network information security, security threats, and preventive measures existing in modern information systems, security architecture and models, basic cryptographic knowledge and application, basic identity authentication technology, network firewall technology, virus and hacker attack defense technology, general system security enhancement technology, the security protection technology of E-mail and Web systems, as well as new technologies and trends in information security. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6701 Business Intelligence. This course explores how data and information systems can be utilized to drive effective operations, improved decision-making and create strategic advantages in organizations. Students will review the information lifecycle components of data collection, analysis, and interpretation as well as the development of measurement systems that align with strategic goals. It includes an introduction to common analysis techniques as well as technology tools that can be utilized for both analysis and presentation. Focus will be placed on collecting and transforming quality data in order to draw appropriate conclusions. Cross-listed as MIS 6677. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6751 Internet Technology and Applications. The objective of this course is to lay a foundation for students to use the Internet in their future study and work. Through the study of this course, students will understand the main content, system composition and characteristics of Internet technology, master the characteristics and application fields of network transmission media, understand the characteristics and engineering application conditions of TCP/IP protocol, and master the basic grammar rules of HTML language. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6801 Business Analytics Capstone. This course requires students to use and integrate the disciplines and techniques learned in business analytics program coursework to address a real-world problem, strategy formulation and implementation concepts are discussed using cases and readings. Deliverables may include article reviews, case analyses, software-based exercises, a course-length project, and presentations. This course should be taken within two courses of completion or with permission of the program director. Cross-listed as MSBA 6689. 3 semester credit hour/s. Department Consent Required.
Campus: LISLE (Typically Offered: Annually)
BALT 6851 Strategic Information Technology Management. This course requires students to use all disciplines and techniques learned. Strategy formulation and implementation concepts focusing on information technology are discussed using cases and readings. This course should be taken within two courses of completion or with permission of the program director. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
BALT 6890 Supply Chain and Logistics Analytics Practicum I. This course provides a supervised, experiential learning opportunity in which students apply analytical methods to supply chain, logistics, and operations problems in professional or simulated settings. Students will analyze and evaluate business processes using data-driven approaches, including forecasting, performance analysis, and decision support. Students may complete the practicum through (1) employment-based experiential learning (Curricular Practical Training, CPT) or (2) a faculty-supervised applied project when employment is not secured. In both cases, students are required to meet defined learning objectives and complete structured academic deliverables. 3 semester credit hour/s. Department Consent Required.
Campus: LISLE (Typically Offered: Periodically)
MESA (Typically Offered: Periodically)
MESA (Typically Offered: Periodically)
BALT 6891 Supply Chain and Logistics Analytics Practicum II. This course builds on Practicum I by requiring more advanced and independent application of analytical methods to complex supply chain, logistics, and operations problems. Students will design, implement, and evaluate data-driven solutions involving forecasting, optimization, and performance improvement in professional or simulated environments.
Students may complete the practicum through (1) employment-based experiential learning (Curricular Practical Training, CPT) or (2) a faculty-supervised applied project when employment is not secured. In both cases, students are required to demonstrate increasing independence, analytical rigor, and integration of technical and managerial skills. Prerequisite: BALT 6890. 3 semester credit hour/s. Department Consent Required.
Campus: LISLE (Typically Offered: Periodically)
MESA (Typically Offered: Periodically)
MESA (Typically Offered: Periodically)
BALT 6901 Independent Study in Business Analytics. This course allows an opportunity for a student to concentrate on a specific topic related to an existing course or to explore a timely topic not covered in an existing course. A proposal is required, outlining the nature of the problem and scope of the investigation. A research paper or project is required, as appropriate to the problem under investigation. Cross-listed as MSBA 6600. 1-3 semester credit hour/s. Course Repeatable. Maximum number of units allowed: 3. Department Consent Required.
Campus: LISLE (Typically Offered: Annually)
BALT 6902 Internship in Business Analytics. An internship offers practical work experience within which the student has the opportunity to apply and test theoretical learning while developing executive skills. The internship experience may be an apprenticeship in which a less experienced student learns about the organization, the business unit, and a variety of analytics projects in which the supervisor is involved, or a project in which the student has major responsibility for a specific assignment and exposure to other areas of responsibility or interest. The Business Analytics internship may be repeated in different settings. Cross-listed as MSBA 6691. 1-3 semester credit hour/s. Course Repeatable. Maximum number of units allowed: 3. Department Consent Required.
Campus: LISLE (Typically Offered: Annually)
BALT 6903 Special Topics in Business Analytics. Timely business analytics topics are presented in the form of 1, 2, or 3-semester credit hour courses. Keeping pace with advances in analytics requires constant learning. These courses provide an opportunity to examine and assess issues in analytics. There are no designated pre-requisites, but graduate students are encouraged to have completed at least 12 semester credit hours. Topics are announced in advance. Cross-listed as MSBA 6691. 1-3 semester credit hour/s. Course Repeatable. Maximum number of units allowed: 3. Department Consent Required.
Campus: LISLE (Typically Offered: Annually)
PBHL 5501 Introduction to Public Health. (Formerly MPH 602, MPH 6002) Explores the history, basic structures, and operations of public health and health care delivery systems based on Essential Public Health Services. 3 semester credit hour/s.
Campus: LISLE
PBHL 5502 Introduction to Biostatistics. (Formerly MPH 511, MPH 5511) Applies statistical reasoning and methods in addressing, analyzing, and solving problems in public health, healthcare, and biomedical, clinical, and population-based research. Prerequisite: Algebra or equivalent. 3 semester credit hour/s.
Campus: LISLE
LISLE
LISLE
PBHL 5504 Introduction to Epidemiology. (Formerly MPH 604, MPH 6004) This course introduces students to the basic principles of epidemiology, the study of the distribution, determinants, and control of health in populations. The course will emphasize fundamental epidemiologic methods, including descriptive and analytic methods, in a variety of public health settings. 3 semester credit hour/s.
Campus: LISLE
PBHL 5505 Health Systems, Law and Policy. (Formerly MPH 610, MPH 6010) Addresses the development and advocacy processes for public health policies; provides tools for policy analysis; and application to important public health issues. 3 semester credit hour/s.
Campus: LISLE
MESA
MESA
PBHL 5506 Leadership and Management in Health Organizations. (Formerly MPH 662, MPH 6062) Explores basic management principles and practical tools for health management professionals in a variety of public health and health care organizations. 3 semester credit hour/s.
Campus: LISLE
MESA
MESA
PBHL 5507 Health Behavior Theory. (Formerly MPH 601, MPH 6001, PBHL 6200) This course exposes students to a variety of traditional and emerging theoretical models and frameworks which can be applied toward explaining and modifying health behaviors. Students will have the opportunity to apply relevant theoretical principles towards changing a health behavior in a specific population. 3 semester credit hour/s.
Campus: LISLE
PBHL 5508 Research Methods in Public Health. (Formerly MPH 606, MPH 6006, PBHL 6500) This course introduces students to public health research methods, including study design, data collection and analysis, and interpretation of findings. 3 semester credit hour/s.
Designation: Writing Intensive
Campus: LISLE
LISLE (Typically Offered: Periodically)
LISLE (Typically Offered: Periodically)
PBHL 5509 Community Health Analysis. (Formerly MPH 6098, PBHL 6898) Demonstrates the collection of data on setting priorities for improving the health of a defined population. It involves field work and utilization of research skills. The synthesis and integration of knowledge from previous coursework is helpful, so students are advised to take this course later in their program curriculum. 3 semester credit hour/s. Department Consent Required.
Campus: LISLE
PBHL 5601 Introduction to Health Informatics. Introduces scope of health informatics in public health settings and programs and its importance in modern healthcare. Provides a foundational understanding of how information technology is used to improve healthcare delivery, particularly in public health contexts. Survey topics include healthcare information systems used in healthcare (EHRs, HIE, and clinical decision support systems); basic data analytics and data visualization techniques to identify trends and patterns in healthcare data; the impact of technology on patient safety, quality of care, and public health interventions; ethical issues related to health informatics; and emerging technologies and trends such as AI and telehealth. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
PBHL 5602 Healthcare Information Systems. Provides strong foundation in the principles and applications of clinical and administrative systems within health informatics, enabling contribution to the design, implementation, and evaluation of health information systems to improve healthcare delivery and public health outcomes. Topics include information systems used in clinical settings that support workflows, patient care and data collection (EHRs, LIS, and RIS); administrative systems and processes related to management of healthcare organizations including revenue cycle management and patient billing systems; role of clinical decision support systems (CDSS) in patient safety and quality of care. Methods include hands-on activities, such as case studies, simulations, or real-world projects to apply their learning. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
PBHL 5604 Electronic Health Records. Provides a comprehensive overview of Electronic Health Records (EHRs) within the context of public health, focusing on their design, implementation, and impact on population health management. Students will learn about EHR architecture, data management, interoperability, the use of EHR data for surveillance, research, and quality improvement as well as different data analysis techniques and methods for interpreting EHR data. Topics include implementation and maintenance of EHR systems such as customization options and ongoing support needs, data exchange with different standards and protocols, and developing skills using EHR data for research and decision-making. The course emphasizes the ethical and legal considerations surrounding EHRs in public health settings. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
PBHL 6009 Social Determinants of Health. (Formerly MPH 609, MPH 6009) This course explores several social determinants of health (e.g., gender, income, education, social networks), the health disparities that these determinants are associated with, and novel solutions for addressing the health disparities. 3 semester credit hour/s.
Campus: LISLE
LISLE
LISLE
PBHL 6050 Emergency and Crisis Management. (Formerly MPH 650, MPH 6050) Introduces the core principles and practices of emergency response and recovery from all types of hazards, threats, and disasters. Emphasizes managing in times of crisis. 3 semester credit hour/s.
Campus: LISLE
PBHL 6101 Advanced Epidemiology. (Formerly MPH 6101) Focuses on applying epidemiologic study designs and methods to design research studies and interventions to control disease among populations. Prerequisites: PBHL 5504. 3 semester credit hour/s.
Campus: LISLE
PBHL 6110 Applied Linear Models. (Formerly MPH 6110) The course commences with the basic foundations for regression and progresses to simple and multiple linear regression, the associated hypotheses, model assumptions and diagnostics, model building, and common regression pitfalls. Computing and data lab will cover techniques and strategies for linear regression in SPSS. Prerequisites: PBHL 5502 and PBHL 5504. 3 semester credit hour/s.
Campus: LISLE
PBHL 6112 Categorical Data Analysis. (Formerly MPH 6112) Instruction in how to perform categorical data analysis. Topics covered will include estimation and inference for contingency tables, Generalized Linear Models (GLM) for categorical and ordinal data, McNemar’s Test, and Cochran-Mantel-Haenszel methods. Computing and data lab will provide instruction on how to carry out the above analyses in SPSS. Emphasis will be placed on interpreting test and model results within the context of epidemiology and public health. Prerequisites: PBHL 5502 and PBHL 5504. 3 semester credit hour/s.
Campus: LISLE
PBHL 6201 Health Communication and Marketing. (Formerly MPH 664, MPH 6064) Explores concepts of marketing theory, planning, strategy, research, and implementation of marketing plans including social media plans. 3 semester credit hour/s.
Campus: LISLE
LISLE
LISLE
PBHL 6202 Health Communication and Messaging. Health Communication and Messaging. Explores concepts of the social marketing theory, strategic planning, and implementation of health messages and campaigns for multiple populations and settings. 3 semester credit hour/s.
Campus: LISLE
PBHL 6203 Public Health Program Planning and Evaluation. (Formerly MPH 634, MPH 6034) Presents evidence-based methods of health education and promotion addressing major risk factors for death, injury, and disability. Students will learn how to plan, implement, and evaluate health programs and interventions. 3 semester credit hour/s.
Campus: LISLE
PBHL 6300 Approaches and Issues in Public Health Leadership and Management. (Formerly MPH 6300) Apply the values, traits, knowledge base, and competencies of effective public health leaders to pressing problems such as substance abuse, cancer, climate change, health care delivery, and population health. Explore alternative styles of leadership and identify personal leadership style. 3 semester credit hour/s.
Campus: LISLE (Typically Offered: Annually)
PBHL 6301 Strategic Planning and Improvement in Health Organizations. (Formerly MPH 6301) Apply basic tools for the collection, analysis, and presentation of data in support of managerial planning, marketing, and decision making. Build a long-term strategic plan including mission, values, and vision to guide decision making. Apply systematic tools to make thoughtful, informed decisions that have a positive impact on organizational goals. 3 semester credit hour/s.
Campus: LISLE
PBHL 6302 Health System Finance. (Formerly MPH 680, MPH 6080) Addresses the management of financial resources in public health and health care systems. Topics include: payment methodologies, accounting and financial statements, models of delivery, and information technology. 3 semester credit hour/s.
Campus: LISLE
PBHL 6304 Health Ethics, Law, and Regulation. (Formerly 603, MPH 6003) Explores the political, legal, regulatory, and ethical environments in public health and health care and provides tools to analyze and formulate ethical decisions. 3 semester credit hour/s.
Campus: LISLE
PBHL 6409 Applied Epidemiology. (Formerly MPH 696, MPH 6096) Focuses on the processes involved in epidemiologic investigations with application to sample cases. Prerequisite: PBHL 5504. 3 semester credit hour/s.
Campus: LISLE
PBHL 6411 Biological Aspects of Public Health. (Formerly MPH 611, MPH 6011) Explores the biological and molecular context of public health and its incorporation into public health practice and articulates how biological, chemical, and physical agents affect human health. 3 semester credit hour/s.
Campus: LISLE
PBHL 6501 Environmental Health. (Formerly MPH 605, MPH 6005) Studies environmental factors including biological, physical, and chemical factors that affect the health of the community. 3 semester credit hour/s.
Campus: LISLE
PBHL 6502 Public Health Grant Writing. (Formerly MPH 694, MPH 6094) Provides an overview of the grant writing process and funding sources for research, practice, and administration/planning grants; and requires development of a full grant proposal. 3 semester credit hour/s.
Campus: LISLE
PBHL 6503 Global Health. (Formerly MPH 693, MPH 6093) Explores issues in global health including the burden and distribution of disease, mortality, and social and cultural risk factors. Emphasizes the challenges of population health in developing countries. 3 semester credit hour/s.
Campus: LISLE
PBHL 6600 Independent Study. (Formerly MPH 600, MPH 6600) Arranged on a specific topic by teaching/learning contract with instructor. 1-3 semester credit hour/s. Course Repeatable. Maximum number of units allowed: 16. Department Consent Required.
Campus: LISLE
PBHL 6691 Special Topics in Public Health. This course will focus on critical and contemporary issues in the field of public health. Subject matter will vary. 3 semester credit hour/s. Course Repeatable. Maximum number of units allowed: 21.
Campus: LISLE
PBHL 6899 MPH Internship/Practicum. (Formerly MPH 690, MPH 6099) MPH Internship/Capstone: In this course, students have the option to complete either a traditional internship (engage in activities that address the needs of a public health organization) or a capstone project (produce a professional product that addresses a public health need). Both options allow students to integrate knowledge and skills developed in the classroom and apply them to real-world public health issues. Students are advised to identify and plan their internship or capstone project early but take this course later in their program curriculum. A total of 4 credits must be earned to complete this course. 0-4 semester credit hour/s. Course Repeatable. Maximum number of units allowed: 4.
Campus: LISLE
PBHL 6900 Health Informatics Capstone. This course will provide students with a hands-on experience in applying health informatics knowledge and skills in a real-world context where they can develop a deeper understanding of the role of technology in public health and its impact on healthcare delivery and data management. Students will identify a clearly defined project that aligns with their interest and associated with specific objectives and deliverables. The project could be within a healthcare organization, a public health agency, or a research institution, preferably one in which they already work, and students will work under the guidance of a faculty mentor or industry professional. Projects can focus on a variety of topics within the major areas of improving healthcare systems, developing health information technology solutions, and analyzing public health data to address real-world issues. 3 semester credit hour/s. Department Consent Required.
Campus: LISLE (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
MESA (Typically Offered: Spring Term)
Krishna Bhagat (2019), Ph.D., M.P.H.
Public Health
Associate Professor, Nutrition and Public Health - MPH
PhD, 2015, University of Maryland College Park
MPH, 2010, Boston University
Christopher Duffrin (2018), Ph.D., M.Ed., M.S., EMT-P, MCHES
Department Chair for Nutrition and Public Health Sciences, Public Health
Professor, Nutrition and Public Health - MPH
PhD, 2002, Ohio University
MS, 2009, Western Illinois University
MED, 1998, Ohio University
BS, 1991, Western Illinois University
EMT-P, 1986, Southwestern College
Susan Yazdanmehr, M.D., M.P.H.
Public Health
Instructor, Nutrition and Public Health - MPH
M.D. 2004, Educational Commission for Foreign Medical Graduates
M.P.H. 2011, Benedictine University
Students in the M.S. Health Informatics program will achieve the following student learning outcomes (SLO):
Student Learning Outcome 1: Demonstrate a comprehensive understanding of how to collect, store, and manage health data effectively.
• University SLO: 1. Disciplinary Competence and Skills
Student Learning Outcome 2: Demonstrate a thorough understanding of database design and implementation.
• University SLO: 1. Disciplinary Competence and Skills; 5. Analytical Skills
Student Learning Outcome 3: Develop a strong understanding of how to analyze and visualize health data to identify trends and patterns.
• University SLO: 1. Disciplinary Competence and Skills; 2. Critical and Creative Thinking Skills; 5. Analytical Skills
Student Learning Outcome 4: Develop skills to forecast healthcare trends and improve operations.
• University SLO: 1. Disciplinary Competence and Skills; 2. Critical and Creative Thinking Skills; 5. Analytical Skills
Student Learning Outcome 5: Obtain practical experience with applying informatics within various public health arenas.
• University SLO: 2. Critical and Creative Thinking Skills