The HSE program produces graduates with strong fundamental skills in systems engineering along with a strong background in healthcare delivery systems and processes. Graduates will be ideally positioned for skilled professional management roles aimed at improving quality, streamlining processes, and improving efficiency in the constantly evolving healthcare systems. Students encounter courses that involve quality processes, financial and information management in healthcare, and classic industrial and systems engineering foundation courses, as well as an industry capstone project.
HSE uses systems modeling as the base for its education. Some of the models HSE students will use include project management, engineering economics and financial engineering, statistics and stochastic processes, operations research, process flow and queuing, discrete event simulation, tools for failure and proactive analysis, and simulation, optimization and information technology.
The curriculum which can be taken on campus or via our Distance Education department, is as follows:
CORE HSE COURSES
Students are required to take the HSE’s core courses. These provide students with the necessary background, specialized knowledge, and management skills required to identify inefficiencies in healthcare systems and propose appropriate alternatives to reduce cost and improve the overall quality of our health care system.
- Introduction to Healthcare Systems - IE470
The state of healthcare from economic, systems, quality, and historical perspectives. Components of the healthcare system including, facilities, delivery and treatment systems, and personnel. System costs, reimbursement methods and financial aspects in healthcare. Healthcare policy, laws and ethics. System performance measures including access, cost effectiveness and quality of care.
- Quality and Process Improvement in Healthcare - IE471
The dimensions of healthcare quality and their definitions, quality metrics, accreditation and other benchmarking and evaluation methods. Change management, project planning and team management. Continuous improvement tools including “lean”, “six-sigma”, and “TQM”.
- Financial Management in Healthcare - IE 472
Engineering economics in healthcare; value metrics (net present value, return on investment, etc.), cost-benefit analysis, capital projects and improvements. Accounting methods in healthcare systems. Reimbursement methods, organizations, and alternatives. Financial strategy, planning, pricing and capital formation in “for”, and “not for” profit settings.
- Information Technology in Healthcare - IE473
Introduction to information systems in healthcare. Components of the system; electronic medical records, patient monitoring and data collection (clinical information systems), ancillaries (lab, pharmacy, radiology), imaging and digital technology, financial, inventory and management information systems. Enterprise systems in healthcare, IT driven cost, efficiency and treatment quality metrics. Data warehousing, sharing, mining, protection and privacy issues.
SYSTEMS FOUNDATION COURSES
Nine credit hours are dedicated to foundation courses that will provide students with fundamental industrial and systems engineering technical knowledge and skills. Students must select three of the four foundation courses listed below.
- Simulation - IE 404
Applictions of discrete and continuous simulation techniques in modeling industrial systems. Simulation using a high-level simulation language. Design of simulation experiments.
- Design of Experiment - IE 410
Experimental procedures for sorting out important causal variables, finding optimum conditions, continuously improving processes, and trouble-shooting. Applications to laboratory, pilot plant and factory.
- Optimization Modeling - IE 426
Modeling and analysis of operations research problems using techniques from mathematical programming. Linear programming, integer programming, multi-criteria optimization, stochastic programming and nonlinear programming using an algebraic modeling language.
- Stochastic Models & Applications - IE 429
Introduction to stochastic process modeling and analysis techniques and applications. Generalization of the Poisson process; renewal theory, queuing, and reliability; Brownian motion and stationary processes.
Six credit hours are drawn from an approved pool of cross-disciplinary courses; these courses have been selected to allow students to to tailor a program to their particular interests.
Elective courses come from various sectors of systems and engineering as well as accounting, business, and economics. The pool of elective courses is listed below.
- Accounting Information Systems
- Financial Accounting
- Cost Accounting
- Project Management
- Human Resource Management
- Strategic Supply Management
- Technology, Operations, and Competitive
- Managerial Economics
- Health Economics
- Management of Information Systems
- Quality Control
- Data Communications Systems
- Systems Engineering Design
- Queuing Systems
- Advanced Database Analysis and Design
- Advanced Data Communications Systems
- Analysis and Design
- Discrete Event Dynamic Systems
- Financial Optimization
Students also take on an industry-related healthcare systems engineering capstone project, completed with supervision and guidance from Lehigh faculty and industry partners. Students work individually or in small groups on projects that are relevant to their interests and the broader needs of the industry, in topics that range from operational to clinical management. Recent capstone projects have focused on projects such as quality management, patient flow capacity optimization, operating room scheduling, hospital occupancy planning, healthcare supply chains, data mining and health informatics, ER patient throughput optimization, optimal patient care delivery, hospital acquired infections (HAI), therapeutic optimization, medical decision making, pharmaceutical applications, epidemic simulation, optimal cancer treatment, chronic care modeling, and organ transplant assignment.
MATH / STATISTICS REFRESHER CLASSES
Courses to build or refresh background knowledge of those who need to refresh, or build quantitative knowledge base and skills:
- Engineering Statistics - ISE 328 (3)
Random variables, probability functions, expected values, statistical inference, hypothesis testing, regression and correlation, analysis of variance, introduction to design of experiments, and fundamentals of quality control. Prerequisite: MATH 23 or equivalent. This course cannot be taken by IE undergraduates.
- Introduction to Industrial Engineering Mathematics - ISE 357 (3)
A review of linear algebra and an introduction to quantitative analysis, manipulation of matrices, core concepts associated with systems of linear equations and linear optimization, algebraic and geometric models. The credits for this course cannot be applied to any undergraduate or graduate degree offered by the Industrial & Systems Engineering Department or the Healthcare Systems Engineering master’s program. Credit will not be given for both ISE 357 and Math 205. (Prerequisite: Departmental Approval)