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Online Masters Degrees & Certificate from Boston College

Developing Tomorrow’s Leaders

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  • 8-week courses with 3 starts per year

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Core Requirements

Provides students with an overview of healthcare services in the United States, including their historical development within a unique social, economic and political environment. Current institutional structures and delivery systems are described, as are the evolving health needs of Americans. Emphasis is placed upon the basic concepts and issues associated with the management and regulation of healthcare providers and the delivery of services.

This course explores the theoretical foundations and application of quality improvement methods, tools and strategies needed to increase organizational effectiveness. The course focuses on measurement and accountability in health care delivery systems through the examination and analysis of data, structures, processes and outcomes. Process improvement theories and models are explored with the goal of preparing students to lead and practice in organizations that advance high reliability principles, patient safety, inter-professional teamwork and continuous learning.

The course reviews innovation-based strategies as a source of competitive advantage in an industry with strict regulation and limited financial resources, and then examines how to build and design organizations that excel at innovation. Students are given fundamentals of strategy and then engage, alongside industry and healthcare organizational leaders in Boston, in the basics every healthcare manager needs to organize successful innovation. This intensive short course is offered onsite at Boston College.

Federal and state-level healthcare policies affect a wide range of issues, including access to care, quality, cost, and modes of delivery. Effective healthcare managers must interpret and anticipate a changing policy landscape, and strategically apply that interpretation as part of the process of organizational planning and execution. In this course, the social and economic implications of contemporary healthcare policies are explored. Emphasis is placed on how public policy (e.g., Patient Protection & Affordable Care Act of 2010) influences human resources/capacity, values, needs, reimbursements and regulation of individuals, insurers, and medical and healthcare organizations.

This course includes the application of management and organizational behavior theory to explore factors affecting behavior, performance and job satisfaction of people working in organizations. The course focuses on theories and observations of team behaviors and techniques, with special emphasis on the individual as a team member, and on change management as a challenge and opportunity for healthcare organizations. Students will learn and apply best practices for managing individuals and teams within healthcare organizations.

The course introduces leadership models, theories, and skills needed to successfully manage and lead healthcare organizations through transformational versus transactional leadership-styles. Students use a variety of self-assessment tools (e.g., Myers-Briggs, SWOT analysis of self, leadership-style inventory) to develop self-awareness and to better understand the role of emotional intelligence in effective leadership. Students gain knowledge and skills for building and growing the interpersonal relationships and political skills required to develop and lead teams, and to successfully advance from organizational management roles to leadership roles.

In this course, ethical and moral considerations associated with the management of healthcare facilities and the provision of health services are examined. Treatment of ethical and moral issues emphasize the understanding of diverse viewpoints and methods for resolving conflicting moral obligations. Students apply course concepts through the exercises and cases in ethical decision making for leaders of healthcare organizations.

Human resources issues face the healthcare managers, from benefits to grievances to labor relations management in health organizations with organized labor. This course covers personnel practices such as job analysis and description, recruitment, selection, and compensation in various health delivery system settings. The course focuses on skill development in dealing with personnel at all levels of education, licensure and skill sets.

This course explores the critical role of e-health and information systems in the planning, operation, and management of healthcare organizations. Students will learn how to assess and evaluate health information systems and business requirements in a variety of settings such as health systems, hospitals and medical practices. Students will develop skills in healthcare technology implementation design that addresses such industry-specific requirements as translating HIPAA and other regulations into specific technology decisions while implementing medical systems (EMR, lab, clinical services, medical database providers, etc.). In addition, students will learn how to manage multi-institutional relationships as they are expressed in technology implementations, including the many vendor configurations but also cross-provider organization relationships. Specific topics include data and systems integrations, communications protocols, security standards, procurement, and authentication and authorization.

In this course, legal issues related to the organization and delivery of healthcare are examined. Topics include government regulation of healthcare facilities and occupations, civil rights regulations regarding diversity, fraud and abuse, institutional and personal liability for negligence and malpractice, patient consent requirements, termination of care, confidentiality of medical information, medical staff credentialing, peer review of care, utilization review, and managed care regulations. Student will apply course concepts through the development of a compliance plan to prevent fraud, waste, and abuse in billing.

In today’s highly competitive healthcare environment, data-driven decision making is key to assuring quality, increasing access, and minimizing cost. In an industry focused on evidence-based practices, healthcare managers must be able to use analytic tools and methods to critically evaluate care and practice to better inform decisions. Tomorrow’s leaders must be able to make decisions based on research, evidence, and data to inform continuous improvement and innovation. The course will review data analysis principles and statistical analysis (e.g., probability, regression modeling, decision science, predictive forecasting, and time series analysis. Students will conduct data analyses and use results to make decisions. Students will focus on how to analyze and interpret data to optimize the decision-making process and assure evidence-based management practice.

This course introduces basic theory and principles of finance as applied to the healthcare industry. Financial statements, cost measurement, budgeting, capital investment decisions and reimbursement models are explored. Students are given an overview of health economic concepts (e.g., sustainability), and are introduced to performance-based payments and value purchasing concepts.

Decisions involving strategy and marketing must be based on a manager’s overall understanding of the organization’s mission, goals and objectives. This applied research project provides methods to evaluate organizational performance and productivity, analyze internal and external resources, and perform needs assessment. The course presents various models and methods for planning, branding, and positioning of healthcare services. It also emphasizes the importance of creating a strategic planning process.

As the culmination and synthesis of the program experience, the applied research project requires each individual student to develop a business plan for the expansion of or development of a new healthcare facility. The business plan must address the major themes of each prior course, including relevant policies, quality initiatives, financial planning, human resource planning, technology planning, and planning for regulatory compliance.

Core Requirements

This course covers the theory and practice of macroeconomics. The course focuses on the underlying determinants of economic growth, unemployment and inflation by developing and assessing a variety of simple models. The course will also teach the skills needed for interpreting and using macroeconomic data to formulate macroeconomic policy. A central feature of the course includes understanding the ability and limitations of policy for stabilizing the business cycle and promoting long-term growth.

This course examines the basic models economists use to study the choices made by consumers, investors, firms, and government officials, and how these choices affect markets. The course focuses on both policy applications and business strategies. Topics include optimization, consumer choice, firm behavior, market structures, risk and uncertainty, and welfare economics.

This course is designed to introduce students to the concepts and data-based tools of statistical analysis commonly employed in Applied Economics. In addition to learning the basics of statistical and data analysis, students will learn to use the statistical software package Stata to conduct various empirical analyses. Our focus will be on learning to do statistical analysis, not just on learning statistics. The ultimate goal of this course is to prepare students well for ADEC 7320.01, Econometrics.

This course focuses on the application of statistical tools used to estimate economic relationships. The course begins with a discussion of the linear regression model, and examination of common problems encountered when applying this approach, including serial correlation, heteroscedasticity, and multicollinearity. Models with lagged variables are considered, as is estimation with instrumental variables, two-stage least squares, models with limited dependent variables, and basic time-series techniques.

Prerequisite: ADEC 7310 Data Analysis or department approval.

The focus of the course is to ascertain how public policy makers decide to either regulate or legislate how an industry/firm will operate in society. We will examine the process from three different vantage points: ethics, economics, and policy. The first part of the course will be spent examining the role (or lack thereof!) that ethical thinking plays in motivating public policy makers to take action. The second part of the course examines how economic pressure comes into play as policy makers try to establish bounds on an industry or a firm. Finally, we explore the role that social pressures such as the media and various interest groups play in influencing how public policy makers react to various issues that confront an industry or a firm.

Pre-requisite: ADEC 7201 Applied Microeconomic Theory, ADEC 731001 Data Analysis, and ADEC 7320 Econometrics, or department approval.

Electives

This is a course in a specialized topic of student and professor’s choosing.

The purpose of this course is to demonstrate how economists think about and analyze health and medical care issues. The course emphasizes the distinction between health as an output and medical care as one input into the production of health. This distinction leads to a discussion of models of the production of health, the demand for health and the demand for medical care. Specific topics include the economic, social, and demographic factors determining the demand for medical care, the production and supply of various kinds of medical care

services, the financing of medical care services and alternative systems of health care delivery and financing. The role of and economic justification for government involvement in the medical care system will be analyzed. The course includes in-depth analysis of the structure, conduct, and performance of the markets for private health insurance, physician services, hospital services, and pharmaceuticals.

This is an advanced course in urban and regional economics. The field of urban and regional economics addresses a wide variety of questions and topics. At the most general level, the field introduces space into economic models and studies the location of economic activity. The course will use microeconomic models to address general and interesting questions about the existence and emergence of cities: why do cities exist and why do some grow more rapidly? Why do people live in cities? How do firms and households decide where to locate within given metropolitan areas? What determines the growth and size of a city? Which policies can modify the shape of a city? The course will also analyze the economic issues that arise because people and firms locate in cities. It will focus on many specific urban economic issues such as firm location, crime, transportation, housing, education, inner-city economic development and local government economics.

This course explores the role of the financial system in the overall economy. Topics include study of the structure of the monetary and banking system, interest rates, monetary policy and role of central bank in the economy. Focus is on the empirical investigation/study of these topics.

This course teaches the practical application of finance theory to decisions made in industry. We will learn how individuals and firms choose investment portfolio decisions under uncertainty with a particular focus on topics such as the capital asset pricing model, market imperfections, borrowing constraints, market efficiency and security valuation. Understanding how interest rates, exchange rates, and risk work will aid your understanding of multiple firm problems such as why does a firm chooses a specific investment or place of manufacturing. In addition, studying term structures and discounted cash flows are important to understanding the decision to invest over time.

Since the financial crisis of 2008, banks and bank holding companies in the United States have faced increased regulation. One of the recent changes to these regulations is known as the Comprehensive Capital Analysis and Review (CCAR). At the core of these new regulations, specifically under the Dodd-Frank Wall Street Reform and Consumer Protection Act and the stress tests it mandates, are a series of “what-if” or “scenario analyses” requirements provided by the Federal Reserve. In this course we will examine these new regulations and build models which help to satisfy these requirements and will build both “bottom-up” and “top-down”

models which incorporate external economic scenarios. We will also spend time with the creation of these scenarios. The final project will involve presenting results to experienced banking professionals. Experience with some statistical computing software is required (R, Stata or E-Views). Pre-requisite: ADEC 731001 Data Analysis and ADEC 7320 Econometrics, or department approval.

At its root, the study of health economics is the study of market failure and of government failure. We will begin the course by studying the ways in which incentives facing players in the health care industry are different from those present in other industries. We will use economics to explore how firms in the health care sector should behave, given the sometimes perverse incentives they face. As the course progresses, our emphasis will shift: in small groups, students will complete and present a data-driven (or empirical) project investigating a question relevant to healthcare providers, pharmaceutical companies, insurance companies, and/or government regulators. Skills developed in this class will allow students to think critically about incentives present in health care settings, analyze various types of health care data, and present ways to improve the performance of different players in the health care industry.

Pre-requisite: ADEC 731001 Data Analysis and ADEC 7320 Econometrics, or department approval.

This course focuses on a study of money, banking and financial markets with a clear emphasis on central banking and conduct of monetary policy. An in depth analysis of fixed income markets in addition to equities and other financial instruments in this course provides students with the opportunity to master intricacies of financial markets and investing in them. Additionally, the connection between movements in the financial markets and monetary policy is examined on a daily basis. An extended use of Bloomberg Professional LP in this course makes this very applied class particularly valuable to anyone interested in bridging the gap between the economic theory and practice.

Pre-requisite: ADEC 7201 Applied Macroeconomic Theory, or department approval.

This course provides an introduction to the use of operations research methods in economics. For this purpose, the course starts with a brief review of the basics from microeconomic theory, calculus and linear algebra, which is followed by the conceptual foundations of economic modeling and the applications of optimization techniques on various economic problems. The course provides a very sound perspective on how to use operations research techniques in any kind of economic and managerial decision making, which has becoming an increasingly sought after skill. We will work on various problems, including portfolio management, resource management, environment and energy related regulations, etc.

This course examines global differences in the standard of living and economic growth. It also explores policies and programs that help in the alleviation of poverty, with emphasis on policies related to education, health, and foreign aid, etc. Focus of the course is on empirical examination of topics, evaluation of research designs, and interpretation of statistical/econometric evidence.

Pre-requisite: ADEC 731001 Data Analysis and ADEC 7320 Econometrics* or department approval. *Students can be concurrently enrolled in the Econometrics course.

This course demonstrates how to merge economic data analysis and applied econometric tools with the most common machine learning techniques, as the rapid advancement of computational methods provides unprecedented opportunities for understanding ?big data?. This course will provide a hands-on experience with the terminology, technology and methodologies behind machine learning with economic applications in marketing, finance, healthcare and other areas. The main topics covered in this course include: advanced regression techniques, resampling methods, model selection and regularization, classification models (logistic regression, Naive Bayes, discriminant analysis, k-nearest neighbors, neural networks), tree-based methods, support vector machines, and unsupervised learning (principal components analysis and clustering). Students will apply both supervised and unsupervised machine learning techniques to solve various economics-related problems with real-world data sets. No prior experience with R or Python is necessary.

Pre-requisite: ADEC 7310 Data Analysis and ADEC 7320 Econometrics, or department approval.

The course will focus on the role of the private sector in achieving sustainable economic growth in developing countries. Core concepts and analytical frameworks will be introduced primarily from a practitioner’s perspective. Investment Fund Managers, World Bank Project Officers, and Incubator Management Teams will contribute to lectures providing students with an opportunity to deepen their knowledge and broaden their networks in the field of economic development. Topics will include entrepreneurship, SME development, and impact investing. The course will also analyze the role of government in supporting private sector development through investment climate reform and public-private dialogue.

This course will expose students to the most popular forecasting techniques used in industry. We will cover time series data manipulation and feature creation, including working with transactional and hierarchical time series data as well as methods of evaluating forecasting models. We will cover basic univariate Smoothing and Decomposition methods of forecasting including Moving Averages, ARIMA, Holt-Winters, Unobserved Components Models and various filtering methods (Hodrick-Prescott, Kalman Filter). Time permitting, we will also extend our models to multivariate modeling options such as Vector Autoregressive Models (VAR). We will also discuss forecasting with hierarchical data and the unique challenges that hierarchical

reconciliation creates. The course will use the R programming language though no prior experience with R is required.

Pre-requisite: ADEC 7310 Data Analysis and ADEC 7320 Econometrics, or department approval.

The essence of Law and Economics is the study of how markets function. This class will begin with an analysis of the economics of firms and the interrelationship with markets. This will lead to a focus of the course on market regulation as to competition, innovation, pricing and other strategies. In particular, economic analysis germane to Antitrust law will be studied as well as Securities, Intellectual Property, and Environmental Law. The course will also delve into how applied economic thinking is useful from a regulatory perspective for a particular industry or two. Finally, the course will cover aspects of social regulation, including the classic concepts of law and economics pertaining to property rights. Students will learn the thought patterns, concepts and tools that both consulting economists and regulators rely upon. The professor will draw upon his rich career in these fields to structure the class in an active learning format to make the material engaging.

Pre-requisite: ADEC 7201 Applied Microeconomic Theory, or department approval.

Transfer pricing involves the valuation of goods, services, and other assets exchanged between affiliated companies. Based on economic principles and governed by the U.S. tax code, international transfer pricing has continued to be a focal point for both multinational companies and tax authorities as a means to evaluate the allocation of income resulting from intercompany transactions conducted across borders. This course will include an introduction to basic tax and transfer pricing concepts, accounting and financial statement analysis, and an application of economic principles underlying transfer pricing analysis. Students will use real case studies and work in groups to consider the economics associated with conducting an international business, and apply transfer pricing methods to develop and support their analysis.

This course will focus on the measurement and analysis of business cycles with a special emphasis on business forecasting. Leading indicators are used as forecasting tools to predict when economies move from expansion to recessions and vice versa. Taking an applied empirical approach, we will cover data and tools used for analysis of short term conditions. While business cycle analysis is concerned with short-term fluctuations, understanding the long-term growth path of an economy is important to interpret short-term movements. Applications of trend estimation methods will also be covered. We will study cycles in developing economies which have experienced long periods of continuous growth. Our focus is on important economic indicators and a discussion of data issues such as price indexes, deflation, and seasonal adjustment. How can these indicators be applied and interpreted to understand short term trends in the economy? How can they assist in economic and business decision making?

Pre-requisite: ADEC 7200 Applied Macroeconomic Theory and ADEC 731001 Data Analysis or department approval.

Innovation and entrepreneurship have been the key drivers behind economic growth across developed economies and even more so in the U.S. However, innovations and entrepreneurism develop under a high degree of risk and uncertainty and, in most cases, rupture existing structural and traditional patterns and practices. Economic policies along with regulation set the incentives for innovation and entrepreneurship. Intellectual property rights and competition ensure that innovators receive a fertile and collaborative market structure to reach their potential.

The course provides students with an overview of popular software packages used today for data exploration, analysis and visualization. The first part of the course will offer an overview of the non-programming tools spreadsheet/Excel and Tableau. In Excel we will cover basic method, tools, charts, with the emphasis on pivot tables. In Tableu students will be introduced to data collection, exploration and visualization methods. The second part of the course will provide an intro to using SQL databases, where students will learn how to create SQL queries to select, filter and arrange the data. The third part of the course will cover basic data analysis in statistical software packages Stata and R. Here students will learn how to write their own code for importing, cleaning and exploring large datasets, as well as how to create, modify and export complex charts and summaries for visual, qualitative and quantitative analysis of the data.

Market research is the systematic gathering and interpretation of information and data using the statistical and analytical methods and techniques of the applied economics and statistics to gain insights or support decision making. This course provides you with the skills and tools needed to understand and evaluate market research. Market research and analysis involve

developing research questions, collecting data, analyzing it and drawing inference, with a view to making better decisions. To this end, the course is organized into two basic parts: (1) Data collection and research design, and (2) Tools and applications of research and data analysis. The course will provide a framework for conducting research, knowledge to properly design research, techniques and tools to analyze data and infer insights, and practical information sources.

This course is for students who wish to gain a high-level understanding of the private equity ecosystem. Private equity is no longer niche, but a large and global asset class with trillions of dollars under management that touches many aspects of people’s daily lives all over the world. There are now thousands of private equity firms globally, and the industry has evolved to the point where different players offer distinct investment strategies and execution styles. Topics will include LBOs, venture capital, structures, economics, due diligence, portfolio construction, performance measurement, impact on society, agency issues, and ethical considerations. Through class discussion, guest lectures, and case studies, students will develop an understanding and appreciation for this unique asset class that is not well understood by many.

This course examines where the tension between economic activities and environment stems from, how economic activities cause environmental degradation and what kind of regulatory actions should be taken in order to maintain the balance between economic growth and environmental sustainability. The course has two main parts, theory and applications. We will start with analyzing the underlying economic theory of market failures, economic valuation, economic incentive instruments, and then move onto the applications of the economic theory to real world cases, i.e. air pollution control and climate change mitigation policies, water quality management and waste management.

Pre-requisite: ADEC 7201 Applied Microeconomic Theory, or department approval.

Core Requirements

This course demonstrates how to merge economic data analysis and applied econometric tools with the most common machine learning techniques, as the rapid advancement of computational methods provides unprecedented opportunities for understanding ?big data?. This course will provide a hands-on experience with the terminology, technology and methodologies behind machine learning with economic applications in marketing, finance, healthcare and other areas. The main topics covered in this course include: advanced regression techniques, resampling methods, model selection and regularization, classification models (logistic regression, Naive Bayes, discriminant analysis, k-nearest neighbors, neural networks), tree-based methods, support vector machines, and unsupervised learning (principal components analysis and clustering). Students will apply both supervised and unsupervised machine learning techniques to solve various economics-related problems with real-world data sets. No prior experience with R or Python is necessary.

Pre-requisite: ADEC 7310 Data Analysis and ADEC 7320 Econometrics, or department approval.

This course will expose students to the most popular forecasting techniques used in industry. We will cover time series data manipulation and feature creation, including working with transactional and hierarchical time series data as well as methods of evaluating forecasting models. We will cover basic univariate Smoothing and Decomposition methods of forecasting including Moving Averages, ARIMA, Holt-Winters, Unobserved Components Models and various filtering methods (Hodrick-Prescott, Kalman Filter). Time permitting, we will also extend our models to multivariate modeling options such as Vector Autoregressive Models (VAR). We will also discuss forecasting with hierarchical data and the unique challenges that hierarchical

reconciliation creates. The course will use the R programming language though no prior experience with R is required.

Pre-requisite: ADEC 7310 Data Analysis and ADEC 7320 Econometrics, or department approval.

This course is designed to introduce students to the concepts and data-based tools of statistical analysis commonly employed in Applied Economics. In addition to learning the basics of statistical and data analysis, students will learn to use the statistical software package Stata to conduct various empirical analyses. Our focus will be on learning to do statistical analysis, not just on learning statistics. The ultimate goal of this course is to prepare students well for ADEC 7320.01, Econometrics.

This course focuses on the application of statistical tools used to estimate economic relationships. The course begins with a discussion of the linear regression model, and examination of common problems encountered when applying this approach, including serial correlation, heteroscedasticity, and multicollinearity. Models with lagged variables are considered, as is estimation with instrumental variables, two-stage least squares, models with limited dependent variables, and basic time-series techniques.

Prerequisite: ADEC 7310 Data Analysis or department approval.

The

Boston College

Commitment

Located just west of downtown Boston, Massachusetts, Boston College is known for its highly regarded graduate programs and is consistently ranked as a top 40 school by U.S. News & World Report.

• Best Colleges, #37, National Universities, U.S. News & World Report
• Best College Values, #18, Kiplinger’s 2018
• America’s Top Colleges, #49, Forbes 2018
• Best Online MHA Degree, #11, SuccessfulStudent.org 2018
• MHA curriculum based on National Center for Healthcare Leadership (NCHL) Competency Model*

*Our online MHA program builds from the foundation of the National Center for Healthcare Leadership (NCHL) Competency Model and has been refined through collaboration with top healthcare leaders and organizations.

Hear What Our Students Are Saying

I enjoy combining both the MHA Program with my professional life activities because it not only allows me to make well-informed contributions, but also allows me to educate my supervisors and colleagues about the healthcare system. The more time I spend in the MHA Program the more confident I become making decisions in my professional life.

Rebecca Cyr, Operations Coordinator, Brigham and Women’s Faulkner Hospital

With two young children and a full time job this new, online medium has allowed me to focus on the important things in my everyday life while maintaining academic progress.

Rebecca Hayes, Surgical Nurse, Mount Auburn Hospital

Yes! I want to know more about the

Online Master of Healthcare Administration Degree