Online Master's in Healthcare Operational Excellence (HOPEX)

Medication Use System Analyses and Improvement

Medication use system analysis, system improvement, pharmacy automation, quality assurance, utilization of pharmacy staff, facility design, and lean process.

Biostatistics & Research Methods

The course begins with basic statistical concepts, introduces essential descriptive and inferential statistical tests, demonstrates some data analysis tools and collection instruments, then discusses common research methodology for pharmaceutical and cosmetic sciences.  Students will learn how to use statistics and research designs to evaluate scientific evidence to make individual and population-based decisions.  Students will conduct some simple statistical analysis based on given data sets and interpret the results, as well review clinical research literature. 

Pharmacoeconomics & Decision Analytical Modeling 

This course is designed to provide an understanding of the theory and application of economic evaluation methods used in healthcare decision-making. Various methods such as cost-effectiveness analysis, cost-utility analysis, cost-minimization analysis, and cost-benefit analysis will be discussed to evaluate healthcare services, pharmaceuticals, and medical device products. Additionally, techniques to measure costs and outcomes will be discussed in detail along with assigning the monetary value to outcomes. Different types of models such as decision trees and Markov models will be taught. Students will have a chance to conduct independent group projects using a decision-analytic software package by which they will be able to conduct a cost-effectiveness analysis to compare different therapeutic options.

Ethics in Scientific Research- Pharmacy

Students will learn about the various ethical and moral issues that are often encountered in scientific research including ways to identify and analyze them in the practice of research. The course is designed as an option to meet the NIH and NSF requirements for training in RCR (Responsible conduct of research).   Topics to be covered include:  RCR principles and guidelines, mentorship, collaborative research, conflict of interests, authorship and plagiarism, intellectual property and data handling, research involving human and animal subjects, scientific integrity and misconduct and social responsibility.

Lean Six Sigma I
Introduction to Lean Six Sigma

To become more competitive, industry is looking for individuals that understand how to both problems solve and eliminate waste within an organization. This course provides students with the tools, techniques and methodologies that will enable them to lead LSS projects in their organization. Students will learn how to apply the problem-solving framework for improving processes – Define, Measure, Analyze, Improve and Control (DMAIC), develop knowledge of using the tools and methodologies for streamlining end-to-end processes by eliminating non-value-added activities and reduce variation in processes to improve quality and reduce rework. The course will utilize lectures and various case studies to demonstrate the understanding and application of these principles.

Lean Six Sigma II
Management in Healthcare 

In this course, students will gain knowledge in the application of quality improvement methodology in both manufacturing and service environments related to healthcare. Emphasis will be placed on philosophical approaches to quality improvement and quantitative methods of quality control. The following topics will be included: Corporate Quality Programs, Applications for Quality Improvement, Measurement System Analysis, Statistical Process Control, Experimental Design, Root Cause Analysis, and Design for Quality. Students will be expected to use MS Office, especially Excel, and Minitab in this course to complete assignments and the final project.

Lean Six Sigma III
Standard Work and Sustainability 

This course focuses on the essential elements of a Lean Management System, providing students with the tools and techniques and thinking way to effectively communicate and control plans, processes, activities, deliverables, responsibilities, and results through visual management. Students will learn to design and utilize visual displays that share information and workplace standards and develop and apply visual controls to make key performance indicators visible across various areas including safety, delivery, quality, cost, and morale. Additionally, the course covers strategies for workplace organization and standardization, effective performance review, and various problem-solving techniques to identify, analyze, and resolve issues efficiently - called the 4 plays. By the end of the course, students will be equipped with the skills and knowledge to lead Lean Six Sigma projects and drive continuous improvement in their organizations.

Introduction to Applied Artificial Intelligence and Machine Learning Tools*

This course is designed for professionals who already have basic knowledge of Python programming and basic algorithms, but are looking to refresh their knowledge and expand their hands-on skills on recent Machine Learning tools. Students will be introduced to popular AI techniques conceptually and will learn to evaluate the performance of the algorithms themselves, taking advantage of the latest tools available. Furthermore, they will learn how to adapt and customize the algorithms on new problems reviewing examples. Supervised learning techniques (regression, classification, neural networks and SVM), unsupervised learning techniques (clustering, SOM, PCA) and anomaly detection algorithms will be covered.   

*By Permission Only

Industrial big data includes all types of data generated from industry applications consisting of machine operation, manufacturing process and maintenance events, etc. In today’s competitive business environments, companies have urgent needs to use advanced analytical tools to manage their industrial data to gain more insights of their operations. This course will introduce students to advanced technologies—such as advanced signal processing, pattern recognition & machine learning and predictive analytics—that ultimately enable the conversion of industrial big data into actionable information that can be used to improve the design, the productivity and the efficiency of manufacturing operations.

Leading Quality Management in Pharmacy

This course present students  with a comprehensive overview of quality management principles, concepts and tools used in healthcare with a special emphasis in pharmacy practice.  Through an analysis of pharmacy -related cases, students will have the opportunity to evaluate the relationship between leadership principles and quality  improvement. Topics include quality performance measurement, culture of quality, techniques for quality  leadership, patient engagement in quality  and the use of technology in quality improvement.

Medication Use System Management

This course covers the elements of the medication use system and will assist students in developing skills to assume a leadership role in devising and implementing process improvements of use of health care technologies (electronic health record, bar codes, robotics, smart devices) in the medication system along with HIT standards for interface and integration, and mobile health technologies.  Students will gain an understanding of personal health records and models of community and regional information networks. Course content will include activities in workflow process mapping and workflow redesign, project management, and processes for documentation and coding.

Accounting and Financial Decision- Making for Pharmacy Leaders

This course covers selected financial and managerial aspects of healthcare financial management, specifically designed for Pharmacists. It provides a broad introduction to key concepts, issues, tools, and vocabulary useful for managers, department heads, and owners. There are three main topic areas covered in the course: financial accounting; finance; and managerial accounting. The focus is on the understanding and application of the accounting information in healthcare with emphasis on addressing use within the pharmacy.

The Healthcare MarketPlace- Pharmacy Economics

This course provides an overview of economics and  marketplace topics related to pharmacy, with particular emphasis on topics relevant to the pharmaceutical industry and health benefit payment models.  This course will provide an introduction to the fundamentals of Pharmacoeconomics and outcomes research. Pharmacy business aspects of pharmaceutical  regulation and pricing, contracts and purchasing  models, group purchasing organizations, MTM reimbursement, specialty pharmacy, and value based clinical and financial models for future health care delivery will all be addressed in the course  content.  Innovation and marketing will also be included with cases and application activities.