Ask premeds to identify their most challenging course, and many will respond that it’s organic chemistry. Ask a law student, and many will just throw up their hands, saying, “They’re ALL hard.” The truth is, school is challenging. That’s especially true when you’re training to be a well-paid professional and expert.
So, what are the most demanding courses in a Master of Science in Health Informatics program? We scoured curricula, blogs, and Quora and Reddit forums to find the answer—so you don’t have to! If you can’t get enough of health informatics, healthcare-related information systems, and healthcare information technologies, read on to delve into the following essential questions prospective students should be asking:
A Master of Science in Health Informatics teaches professionals how to leverage and interpret the abundant and rapidly proliferating amount of healthcare data generated daily. Healthcare systems are among the most essential information systems in the realm of information technology. Earning a master’s in health informatics and gaining expertise in all areas of health information technology—from electronic health records to health data to clinical informatics—is an excellent way to make a difference in the healthcare and public health spheres.
Essentially, health informatics is where medical records management meets data analytics. People who work in health informatics use AI, databases, software, financial systems, and various other technologies to analyze and optimize health records. It’s the technical component of medical management, and it’s essential for the optimization of the healthcare field itself. Health informatics is meant to improve productivity, regulation, and cost-effectiveness in everything from resource usage to billing systems.
Healthcare data is vast and variable, and the range of jobs in health informatics is correspondingly wide. Here are a few:
Technically you only need a high school diploma to work in health informatics. Still, a master’s degree is necessary if you’re looking to fill a top position, and it will elevate your resume for most other opportunities. For example, a health informatics specialist (an employee who trains staff on healthcare systems and procedures, troubleshoots and assists staff, and makes sure that the facility is up-to-date on compliance standards) may qualify with no more than a high school diploma and tech experience; many postings for this role, however, require a bachelor’s or master’s degree. A health informatics nurse (an employee who evaluates healthcare facility operations, oversees data integration, and trains staff on new tech systems) only technically needs a bachelor’s degree in nursing, but many plum positions require a master’s in health informatics as well. Clinical analysts (employees who create healthcare database systems and evaluate data to enhance workflow) and clinical informatics managers (employees who manage and monitor budgets and staff members alike) need bachelor’s degrees to start and master’s degrees for higher-level positions.
Bottom line: you can work in health informatics with any level of education beyond high school, but the more degrees you have, the more opportunities will open up for you.
Health informatics careers are growing faster than average as more healthcare systems switch to cloud storage databases to sort, organize, and analyze patient data. The job outlook is strong for health informatics professionals, as are salaries, particularly at the management level and above. Approximately 34,300 jobs in the health informatics medical records and health information openings will open each year from 2020 through 2030. (
A Master of Science in Health Informatics (MSHI) broadens your skill set and, as a result, your career options. An advanced degree in this field can offer even more opportunities to make your mark in this growing industry. ( )
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Health care informatics master’s programs can offer numerous specializations, including:
Any track will equip you with the education and skills needed to be a top-salaried employee at the intersection of healthcare, technology, and business management, as well as making you a competitive applicant for various jobs in the health informatics sphere. No university offers all tracks, of course, and most offer only a handful. Here’s a look at the tracks offered by University of Pittsburgh, and how they differ from each other.
Coursework in the data science track is all about understanding how data analytics works across health information technologies— it teaches students how to analyze, extract, and present data in the healthcare field. Students learn the nuances of extricating information from vast, complex datasets across various information systems. Data analytics is the part of health informatics that enables employees to drive performance improvement in quality measurement, patient outcomes, and healthcare organizations’ financial success.
The general health informatics (HI) track teaches students how to evaluate and manage health information technologies and systems in which data is processed. Students who choose this track generally pursue careers in which they analyze, design, and evaluate health information systems, while potentially also managing data analytics projects to improve the quality and accessibility of healthcare services. Graduates of this track ensure that the electronic health records from which healthcare data is extricated are stored in well-designed health information systems.
The healthcare supervision and management (HSM) track teaches students advanced administration and supervisory management skills in healthcare, long-term care, and rehabilitation. The purpose of this track is to help students develop a skill set that combines healthcare management and organization leadership, which should help them engage in complex, dynamic healthcare landscapes in their future careers.
The registered health information administrator (RHIA) track gives students the knowledge and academic accreditation they need to sit for the RHIA exam, which allows them to work as a liaison for care providers, payers, and patients. Graduates of this track pursue careers in which they manage protected health information systems’ input, security, transmission, and storage. The track focuses on health information management issues, including revenue cycle, privacy and security requirements, and clinical documentation requirements. The RHIA track is often filled with professionals hoping to gain specialized experience in their field and people who want to lead and supervise teams. Information systems and Information technology are typically less emphasized in this track.
Your particular strengths and weaknesses will help determine which courses are most challenging for you, of course. That said, these are the courses students tend to find most perplexing.
This course includes:
If you want to work in health informatics and efficiently manage health information technologies, you’ll need this linguistic foundation.
This course covers a vast and diverse array of complex biomedical topics and terms that some students may have little prior knowledge of. You’ll need to not only memorize but also understand the implications and construction of various medical terminologies and master an unfamiliar (but essential) language.
This course surveys the design, implementation, and management of healthcare databases. You’ll learn about strategic healthcare database planning, entity-relationship modeling, healthcare data normalization, and the SQL language. This course should give you an in-depth understanding of where patient data and population health data come from.
You’ll study advanced topics in big data like transforming data, data warehousing and data mining, and analysis and visualization of data. You’ll also likely review ethical issues relating to modern data warehousing techniques in health information technology, and you’ll have to figure out how to manage those issues alongside your burgeoning knowledge of data warehousing.
This course introduces the complex amalgamation of business strategy, information technology, and modeling methods that is data science. The course should provide an overview of modeling methods, analytics software, and information systems while also providing intel on business problems and solutions regarding current data management systems.
Well, data science is a complicated discipline, and data science in health informatics is no exception. You’ll be dabbling in such changeable and nuanced areas as business research, sampling, and survey design via extraordinarily complex modern-day data management systems.
This course will teach you how to strategically plan for and finance health information systems. You’ll understand financial and reimbursement language, concepts, and processes that enhance healthcare leaders’ daily management performance. By the end of the course, you’ll have a comprehensive understanding of healthcare reimbursement and managing the revenue cycle.
Financial and reimbursement language are just that—a different language, similar to medical terminology. Many students are developing foundational financial knowledge as they attempt to cultivate a mastery of financial and reimbursement language throughout the course. You’ll also be required to understand how to manage health information technology assets—from pharmacy equipment to point-of-care solutions to software and imaging equipment—and you’ll have to develop a firm grasp of the financial components of implementing these technologies within the boundaries of a healthcare organization’s strategic goals.
On the leadership side, you’ll learn individual and organizational strategies to influence colleagues, shape culture, manage transition, and facilitate employee engagement in today’s healthcare organizations. On the project management side, you’ll learn how to manage and lead teams of technical, clinical, and professional specialists through workflow and work process activities. You’ll also learn about budgeting, project monitoring, and how to derive meaningful milestone deliverables to track progress for projects of all kinds. Coursework focuses more on decision-making and decision support among employees than on patient data.
This course is complex; it takes a developmental approach (rather than a training approach) to growth. You’ll likely end up having to (gulp) develop as a person, not just a student, by learning through a leadership development framework that guides you in obtaining the skill sets necessary to lead.
This course addresses the legal, ethical, and social issues relevant to healthcare informatics, and gives students the analytical tools necessary for spotting those issues. This course is essential because it protects students and their employers in the highly regulated medical informatics field and healthcare industry in general.
Students must memorize, process, and conceptualize the subtleties and larger implications of such complex legal issues as privacy and security, fraud and abuse, confidentiality, antitrust law, intellectual property, the Joint Commission, disclosure, and compliance programs. You’ll also likely need to gain an understanding of information security in healthcare administrations.
This course will teach you about the theory, design, and practical application of healthcare systems. You’ll learn various machine learning approaches to extracting insight from structured clinical data and unstructured clinical text, and you might even gain real-world experience working with real-world clinical datasets.
By the end of this course, students are expected to have the ability to use statistical and machine learning methods to analyze a variety of complex data sets in healthcare and then extrapolate predictions and recommendations from those findings.
This course equips you with an understanding of basic terminology and clinical healthcare research. It also teaches how to:
Coursework focuses on helping you understand what’s actually being said in the electronic health records you’re sure to pore over as you venture further into the subtleties of health informatics and information systems.
The ability to measure and describe health informatics issues is essential to every healthcare decision, large and small. Students must learn to tailor evaluations to the contexts in which issues arise, an inherently subjective process that must nonetheless be informed by research and often data extricated from various health information technologies and information systems.
This course teaches the fundamental principles of data science programming using popular languages such as R and Python. You’ll become familiar with programming techniques, data manipulation, and data analysis. Coursework will be oriented toward familiarizing you with programming health informatics-oriented information systems.
You’ll delve into stats—a world-renowned nightmare for STEM students—from the perspective of data science in healthcare. Not only will you need to learn a variety of statistical methods, but you’ll also need to learn how to apply each of those methods to data science within the specific sphere of healthcare. Just keep reminding yourself of all the good you’re going to do for population health—your GPA will be fine.
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