Master's in Healthcare Analytics: Best Online Programs & Full Directory

Make a real difference in the world with a master’s degree in healthcare analytics. Whether you’re approaching this field from a technical background or a clinical background, there will be a graduate program to suit. Dig into our rankings of the best online & on-campus degrees in the country. Decide if you want to pursue healthcare analytics or health data science. Learn what health data analysts are saying about the job market. Or skip ahead to our listings to begin comparing coursework, admissions requirements, and costs!

What is Healthcare Analytics?

What Do Healthcare Analytics Professionals Do?

Health data analysts use statistical, analytical, and computational methods to solve complex problems within the healthcare industry. Healthcare analytics specialists are fascinated by the challenges of saving patient’s lives, improving healthcare delivery systems, lowering medical costs, and optimizing the efficiency of healthcare operations. On any given day, they might be seeking to:

• Use predictive modeling to identify high-risk patients and implement a care coordination program
• Analyze a wide range of data sources in order to personalize treatment plans for diabetes patients
• Monitor patient admission data to optimize staffing levels, reduce overtime costs, and improve wait times
• Create digital platforms to help patients keep track of conditions and medical interventions in real-time
• Recommend strategic public health measures to prevent the spread of infectious diseases
• Triage patient needs to reduce the time from primary care diagnosis to treatment
• Apply AI to Electronic Health Records (EHRs) to flag patients who are candidates for early interventions
• Pinpoint fraud and misuse in healthcare insurance claims
• Save on the cost of medical supplies by refining supply chain processes
• Analyze incident reports to reduce the prevalence of hospital-acquired infections
• Automate and streamline clinical paperwork tasks

This is just a taste of what the field can offer. And once you’ve reached the realms of health data science, the work gets even more stimulating.

Why Choose Healthcare Analytics?

We don’t usually get overly excited about topics, but this a field where you can really carve out a unique career for yourself! In the past decade or so, healthcare has been dealing with an explosion of clinical & non-clinical data and major lurches forward in technology integration. That means the industry is desperately in need of data-literate experts who know how to wield the right technical tools.

But it does pay to plan. Find out if a master’s degree is required. Take a look at a typical job description. Learn what sectors are hiring graduates. And then go hunting through our rankings and listings to start narrowing down your choices. From business-focused MSHA degrees to high-octane data science/biostatistics programs, there is something here for everyone.

Healthcare Analytics Rankings

2024 Rankings Methodology

Wondering what goes into a quality graduate program? Explore our rankings of the top 10 schools with the best online master’s degrees in healthcare analytics and the top 5 schools for on-campus programs in healthcare analytics and health data science. To ensure you’re getting the most out of your educational investment, we’ve used a weighted algorithm that considers quality, reputation, and cost.

• Focus: For the online rankings, we considered any degree that had a healthcare analytics major or a dedicated healthcare analytics concentration. That’s why you’ll see majors in areas like health informatics to business analytics. For the on-campus rankings, we’ve profiled programs in healthcare analytics AND health data science. This should give you a sense of whether you’re ready to make the jump to a data science master’s degree.
• Accreditation: In order to qualify for our rankings, all universities had to be non-profit and regionally accredited. Although we didn’t consider other accreditations for this algorithm, we have listed any relevant quality markers in our summary. If the School of Business has AACSB accreditation or the School of Public Health has CEPH accreditation, it’s noted!
• Reputation: Our algorithm gives points to schools that feature in U.S. News & World Report rankings—both nationally and within specific healthcare analytics domains (e.g. Statistics, Computer Science, and Biostatistics).
• Outcomes: Utilizing IPEDS data, we included the completion rates of graduate programs in the fields of biostatistics, computer science, and statistics. Our algorithm also takes into account the average earnings of graduates at 1 year, 2 years, and 4 years post-graduation.

2024 Rankings Highlights

Step right up to the smorgasbord—our 2024 rankings of the best graduate programs in healthcare analytics are full of unique and unusual offerings! Some schools are building on expertise in existing subjects (e.g. health informatics). Others are turning to Departments of Computer Science and Computer Engineering. Here are a few more highlights from this year’s selection:

• The Ivies Are Making a Play in Analytics: We’re talking about names like Columbia and Harvard, as well as prestigious non-Ivy schools like Duke and Rutgers. It’s no accident that these universities also have impressive medical schools, massive research budgets, and ties to large healthcare systems. They’re dealing with a lot of data!
• Online Programs Can Be Under $30,000: If you’re on a very tight budget, consider distance learning—you won’t have to sacrifice quality for price. Schools like Iowa State and BU’s MET may not have the same name caché as Carnegie Mellon, but they are regionally respected.
• Dual Graduate Degrees Are Available: And they may go a long way when you’re applying to consulting or senior-level positions. For instance, healthcare business leaders can combo a technical MSHA with an MBA or MHA. For public health experts who need hard skills in data, consider marrying an MPH with an analytics or data science master’s degree.
• MS or MPH in Data Science—You Decide: In our rankings of campus master’s degrees in health data science, you’ll notice both MS and MPH programs. Although all of them are offered by Departments of Biostatistics, they do have different feel. MS programs may be focused on a lot of technical work; MPH programs often step back and consider wider public health issues.

What Does a Master’s in Healthcare Analytics Look Like?

Why Pursue a Graduate Degree in Healthcare Analytics?

Folks often enter the field of health analytics from two directions—the clinical side or the technical side. In the ideal scenario, earning a master’s degree is going to bust open a whole new realm of data-focused career options. Here are a few scenarios where a graduate program could be worth your time and investment:

• You’re working in a role that involves healthcare data (e.g. medical billing, clinical research coordinator, healthcare assistant, medical record technician, etc.), but you’re bored by the drudgery and would like to qualify for analyst openings that involve strategy and decision-making.
• You’ve been trained as a clinician (e.g. nurse, doctor, pharmacist, etc.), but you need to acquire data-driven management skills to qualify for leadership roles and/or analytics skills for your clinical research projects.
• You’re a public health expert, but you feel like you have a gap in your skill sets when it comes to big data. You’d like to understand the machinery behind analytics and data science in order to work on solving complex healthcare challenges within the community.
• You’ve come up through the ranks as a business analyst or data analyst, but you’re seeing all kinds of opportunities to improve healthcare outcomes, optimize hospital processes, or increase profits for insurance & pharmaceutical companies. You want to work in healthcare, but you need to learn how data within the industry functions.
• You’re a STEM undergraduate who is willing to pay for a master’s degree in order to take advantage of the university’s resources, including health analytics research centers, corporate & hospital partnerships, peer networking, internships, and alumni connections. You prefer guided learning over self-directed study.

Unless you’re a career changer or focusing on clinical analytics roles, you won’t usually need a master’s degree to get started in analytics. Many folks will qualify for junior health data analyst positions with a bachelor’s degree, relevant experience (e.g. internships), and analytics certifications. However, a graduate degree can be very handy when you want to take control of your trajectory. See our section on Career Pathways for more details.

Popular Majors for Healthcare Analytics Master’s Students

We were so impressed with graduate options in this field that we expanded our listings to include all kinds of healthcare analytics and data science pathways. Our first tip is to never settle for a generic qualification. You’ll always be able to find a degree that closely aligns with your interests!

• Master of Science (MS): These will be available in a range of unique majors (e.g. Biostatistics and Health Analytics, Health Data Science, Quantitative Management, etc.). MS programs will ground you in advanced research, analysis, and technical skills. They’ll often allow you to dig deep into a topic of interest. Some may even contain a thesis in lieu of a capstone.
• Master of Science in Health Analytics (MSHA): The MSHA is relatively new, so universities are still sorting out what it looks like. Some may be hyper-focused on computing & analytics credits. Others may tilt towards business applications and healthcare operations. Look at which School is offering the degree—if it’s the School of Business, it’s going to have a corporate flavor.
• Master of Science in Health Informatics (MSHI): Many universities have retained their original health informatics programs and tacked on analytics or data science as a concentration. The MSHI can be a useful choice for clinicians, since health informatics also deals with topics like the administration of health information systems, health data management, EHRs, insurance, and legal & privacy issues.
• Master of Public Health (MPH): An MPH is always going to lead off with general coursework in public health issues & concerns before transitioning into analytics coursework. It’s probably not going to be as technically advanced as an MS, so you’ll need to decide what skills you want to acquire for your job (e.g. Python). But it may be ideal for public health practitioners who need to become data literate.
• Master of Science in Business Analytics (MSBA): Some schools will offer health analytics as a concentration within the MSBA. That means you’ll start by investigating the role of analytics in business realms (e.g. operations research, supply chains, marketing, etc.) before being allowed to specialize in healthcare concerns. You’re interested in helping your employer both save money and make money.
• Master of Business Administration (MBA): The MBA is designed for aspiring corporate leaders, not folks who want to become technical experts. It will always have a core of high-level business courses (e.g. accounting, management, finance, etc.) and a focus on C-level training. You’ll be able to talk to your healthcare analytics teams intelligently, but you’ll also have your eye on larger market issues.
• Master of Science in Health Data Science (MS HDS): If you’re in love with the idea of creating new tools & algorithms, using predictive models to tackle knotty healthcare problems, exploring the possibilities of big data, and working beyond the boundaries of traditional analytics, then consider a data science degree with a healthcare focus. These are often interdisciplinary collaborations (e.g. School of Medicine + School of Engineering).
• Master of Public Health (MPH) or MS in Public Health Data Science (PHDS): These kinds of degrees are almost always going to come from the Department of Biostatistics and School of Public Health and lean heavily toward research applications.

You could even mix and match. Our listings contain plenty of hybrid majors (e.g. Healthcare Analytics & Operations) as well as schools that offer dual degree pathways that combine strategic and technical programs (e.g. MHA and MS; MPH and MS; MBA and MS). You should be able to create a qualification that has just the right coursework for your job goals.

How to Choose a School

Our second tip is to find out what School or Department is offering the degree. In our rankings, you may have noticed that a healthcare analytics degree can be offered by the:

• School of Business
• School of Public Health
• School of Health Professions
• College of Medicine
• College of Health Sciences
• Department of Computer Science
• Department of Health Information Management
• Department of Health Administration & Policy
• Multiple Schools/Colleges

This is going to have a big influence on the flavor of the degree and the curriculum. For example, a degree from a School of Health Professions might contain scores of informatics credits. But a degree from a School of Business could feature healthcare supply chain electives. We’ve included coursework links in our listings so you can see how this plays out in real life.

How to Choose a Program

Our final tip is to look for quality markers. Obvious quality markers include the School’s reputation, job placement record, national rankings, and the qualifications of faculty. But you can go a step further and investigate areas like:

• School Accreditation: In addition to regional accreditation (e.g. HLC), universities can seek accreditation for specific Schools and programs. For Schools of Business, focus on AACSB accreditation. For Schools of Public Health, concentrate on Council on Education for Public Health (CEPH) accreditation. For health informatics programs, look for CAHIIM accreditation and HIMSS approved education partners.
• Proximity to Healthcare Systems: Even if you’re studying online, you should still be asking whether the School has connections to local healthcare systems. For example, MS programs in Massachusetts may include opportunities for high-level analytics research within the Longwood area. MS programs in Kentucky and West Virginia may be concerned with rural data and health inequities. Location dictates focus.
  
• Class Profiles: We always appreciate master’s programs that go the extra mile and provide breakdowns of their annual intakes. Class profiles feature info on demographics, average age ranges, undergraduate majors, average GPAs, GRE test scores, and more. It’s a great way to see if you’re in the right ballpark before applying. Don’t see anything on the website? Ask the program coordinator.
• Advisory Boards & Adjunct Professors: Schools of Business love creating advisory boards for their MS programs, so find out where these folks are working. Some may be leading up big data teams in hospitals, pharma, and insurance. We’ve also seen Schools bringing in corporate healthcare leaders and doctors from the university’s medical system to teach concentration courses. These are your future mentors and employers—know who they are before applying.
• Research Strengths in Healthcare Data: One School of Public Health may be brilliant on global health research; another might be deeply entrenched with community & urban data science projects in Chicago. When you’re assessing the School’s research centers & labs, think about how their work will intersect with your capstone project and practicums. You’re paying for the privilege of using their resources.
• Real-World Opportunities: We favor master’s degrees in health analytics and data science that include consulting electives, industry internships, practicums, conference presentations, journal articles, and capstones. Pretty much anything that involves creating real-world projects that you can put on your résumé. In some cases, these opportunities may secure you a job well-ahead of graduation.

Healthcare Analytics Coursework & Requirements

Admissions Requirements for Master’s in Healthcare Analytics

To speed your search, we’ve included a direct link to the program’s admissions section in our listings. Because it’s hard to find any consistency in application requirements for a health analytics master’s degree, we recommend you draw up a shortlist of titles. Then you can use the admissions link to make sure you’re eligible to apply.

Here are some points to be aware of as you’re assessing your options:

• Undergraduate Degree: You’ll need to check. If it’s a highly technical program (e.g. MS in Health Data Science), universities may favor candidates with a degree in computer science, information systems, mathematics, software engineering, or a related discipline. But many health analytics and informatics programs are willing to consider folks with degrees in medicine, nursing, biology, chemistry, biochemistry, and other STEM fields.
• Undergraduate GPA: The standard minimum is 3.0 GPA, but we have seen lower thresholds (e.g. 2.75). Any program with a Class Profile will typically give you the average GPA for successful entrants. In some cases, it can be as high as 3.5 or 3.6.
• Technical Skills: Varies widely between programs. A number of schools will be looking for evidence of undergraduate coursework in calculus, linear algebra, probability, statistics, and/or programming. However, almost all of these schools will allow you to complete any prerequisites prior to matriculation.
• GRE/GMAT: It’s up to the school. Scores may be mandatory for highly ranked and rigorous graduate programs in healthcare analytics. But waivers can also be available for candidates with high GPAs or a terminal degree (e.g. PhD or MD).
• Work Experience: Again, it’s up to the school. For instance, Brown wants at least 2 years of professional work experience for its MS In Biostatistics: Health Data Science. But plenty of master’s programs are willing to consider recent undergraduates who acquired relevant skills during their studies (e.g. internships).

Want the good news? Almost every university has created separate pathways for clinical or technical entrants who need to get up-to-speed in baseline skills. For example:

• Technical Entrants: If you don’t have any healthcare experience, you would start with a graduate-level course in clinical thinking, healthcare, medical terminology, or the like.
• Clinical Entrants: If you don’t have a lot of technical experience, you would start with a graduate-level course in programming, computer information systems, or the like.

Coursework for Master’s in Healthcare Analytics

Standard Courses

Healthcare analytics is a developing field, so you’re going to see a lot of variation in graduate coursework! Some programs may be preoccupied with lean operations, EHRs, and value-based care. Others will be all about practical Machine Learning and AI. We’ve provided curriculum links in our listings to help you get a quick read on the university’s approach.

This is a cookie-cutter list of courses that you might see cropping up in a master’s program in health analytics, but it’s only the start. It’s just as important to think about the main thrust of the degree (e.g. MSBA, MSHI, MPH, etc.) and the goals of the School that’s offering it (e.g. School of Business vs. School of Public Health vs. School of Data Science).

• Healthcare Analytics
• Healthcare Information Systems
• Healthcare Data Management
• Data Visualization and Storytelling
• Advanced Statistical Methods for Healthcare
• Predictive Modeling in Healthcare
• Healthcare Quality & Performance Improvement
• Ethics & Legal Issues in Healthcare Analytics
• Capstone Project

Look for healthcare analytics programs that will drill you in fundamental technical skills required by employers. We’re talking about proficiency in SQL & database management, programming in Python & R, training in statistical analysis tools & techniques (e.g. SAS), expertise in data visualization tools (e.g. Tableau, Power BI, etc.), and experience in Machine Learning, AI, and big data platforms (e.g. Hadoop).

Once you reach the level of health data science graduate programs, you’re likely to see more coursework in:

• Biostatistics
• Public Health
• Computing with Big Data
• Advanced Statistical Analysis
• Machine Learning & AI

When you’re working on high-level biomedical research, creating new medical tools & devices, and wrangling huge amounts of unstructured data to solve healthcare problems, you need to take your training up to eleven.

Concentrations & Electives

After you’ve selected your major, you can personalize your experience with a concentration and/or electives. Almost all of the programs in our listings will allow you to choose some courses. For example, if you’re leading off with a master’s degree in health informatics, health information management, business administration, or public health, you can add a data-focused concentration in:

• Healthcare Analytics
• Health Services Analytics
• Health Data Science

However, if you’re starting with a dedicated major in health analytics or data science, you could concentrate on business analytics, biostatistics, advanced computing applications, genomics, or clinical trials.

Here are some of the elective categories you’ll frequently spot in healthcare analytics graduate programs:

• Data Science (e.g. Knowledge Discovery and Data Mining)
• Statistics (e.g. Applied Time Series Analysis)
• Business Analytics (e.g. Spreadsheet Modeling and Decision Making)
• Management (e.g. Six Sigma Quality Management)
• Supply Chains (e.g. Enterprise Supply Chain Information Systems)

Note the inclusion of corporate subjects! Universities are aware that many health data analysts work on the business side of healthcare.

Internships

Health analytics internships are a strategic choice. If you’re already happy with your employer, you may find them a waste of time. But they can be particularly valuable for career-changers and folks without a lot of prior work experience. Sticking a summer internship with the Mayo Clinic on your résumé wins a lot of brownie points.

A number of healthcare analytics and health data science in our listings contain internship opportunities. For example:

• At Iowa State, you might use the mandatory internship to train in a field like healthcare data security or risk management. Or you could simply choose to work on a project with your current company.
• At universities like Carnegie Mellon, UNC Charlotte, and Rutgers, internships may be available as electives or as an option for your final project (in lieu of a capstone).

Ask the program coordinator for a list of typical internship placements and chat to recent graduates about their experiences. They’ll tell you how much time they had to put into securing a position.

Capstone Projects

Capstone projects are a standard ingredient in healthcare analytics & health data science graduate programs. This is where you’ll be able to apply your skill sets to a real-world industry challenge. You could be working for a healthcare system in the local area, collaborating with one of your program’s corporate partners, or tackling an analytics project for your current employer.

1. Ask the program coordinator for a list of recent capstone projects. This will give you a sense of the caliber of the capstone companies and the technical skill level of the master’s students.
2. Think about your capstone project options before you apply for the program. You’ll get a lot more out of the experience if you can take advantage of faculty expertise and research center resources.
3. Find out if the capstone involves group work and team presentations. If so, how do students divide up responsibilities?

To get you started, here are a few examples of real-life MS capstone projects in healthcare analytics and health data science. We’ve also included some ideas from GitHub:

• Analysis of Patient Safety Event Reports Data
• Case Study to Improve CMS Hospital Ratings
• Implementation of Clinical Analytic Program in a Molecular Laboratory
• Create an eQTL Visualization Tool
• Nice Healthcare: Predicting Nice Healthcare Utilization
• Time Series Forecasting for COVID-19
• Package Pricing at Mission Hospital

Can You Earn a Master’s in Healthcare Analytics Online?

Yes! Examine our rankings of the 10 Best Online Healthcare Analytics Graduate Programs for examples. We’ve also marked any distance learning programs in our listings with an “Offered Online” label.

• You’re going to have a lot more choice with health analytics programs than with health data science programs. For instance, Schools of Business are usually more than happy to offer graduate programs online. But Departments of Biostatistics still like to train health data scientists in a campus program.
• Bear in mind that some schools will expect you to visit the campus for an orientation or launch experience, optional training intensives, and/or conferences & networking events.
• We also noticed that online master’s programs in healthcare analytics have a fair number of synchronous components. For instance, you may be asked to join live virtual sessions on a weekday evening or participate in online weekend activities.

We favor the inclusion of collaborative elements. They’ll help you build your professional network of healthcare data experts and student peers. But you’ll need to decide if you can fit them into your work calendar.

Since this is a technical degree, you should also be asking the program coordinator some hard questions about the nuts & bolts:

• What types of analytics software will be provided? Is the cost covered by the university?
• Will you be working with real-world data sets and EHRs? Where do online master’s students typically source their healthcare data?
• Can you utilize the university’s career resources? Can you take advantage of résumé reviews, job coaching, and mock interviews?

What Can You Do with a Master’s in Healthcare Analytics?

What Does a Job in Healthcare Analytics Look Like?

Your daily responsibilities as a health data analyst will depend on who you’re working for! A supply chain analyst working for a drug manufacturer won’t have the same priorities as a public health analyst focusing on environmental health inequities. But everyone will be focused on getting the most out of data.

We combed through Reddit discussions and job descriptions to see what might be expected in a typical day-to-day routine for healthcare analytics professionals. As always, we recommend you chat to real people in real positions to get a better sense of their experiences.

• Data Collection & Management: Extracting, organizing, and maintaining large datasets from various healthcare sources, including EHRs and other health information systems (SQL is a key skill here); reviewing, cleaning, and supplying clinical data to clinicians for research projects.
• Data Analysis: Analyzing healthcare data to identify trends, patterns, and insights that could improve patient care, curb adverse events, and increase operational efficiencies; understanding the intricacies of medical coding in order to analyze billing data.
• Reporting & Visualization: Creating reports, dashboards, and visualizations with tools like Tableau & Power BI to communicate data findings to stakeholders, including healthcare providers, administrators, and policy makers.
• Predictive Modeling: Developing and implementing predictive models to forecast healthcare trends, patient outcomes, and resource utilization.
• Process & Performance Improvement: Identifying areas for improvement in healthcare delivery & operations; suggesting data-driven strategies to enhance performance and patient outcomes; automating tasks with tools like Python and AI.
• Analytics Support: Providing data-driven insights and recommendations to support clinical and administrative decision-making processes; handling ad hoc queries; assisting with grant proposals and market research.
• Integration: Working with multidisciplinary teams—including IT professionals, clinical staff, and management—to integrate analytics into healthcare operations and projects.
• Quality Assurance: Ensuring the accuracy and integrity of healthcare data through regular audits and quality checks; identifying and correcting data inconsistencies or errors.
• Compliance & Security: Ensuring that data handling practices comply with healthcare regulations and standards (e.g. HIPAA); maintaining data security and privacy.
• Training & Documentation: Developing documentation and providing training to other staff on data systems, analytics tools, and methodologies.

Health data scientists are going to have a lot more “play” than health data analysts—they’ll get to tackle complex questions about patient care (e.g. discovering the root causes of repeat ER visits), work with sophisticated predictive models, and create out-of-the-box solutions. Reddit has a great thread on the day in the life of a healthcare data scientist, with plenty of examples of real-world projects (e.g. using NLP and ML to extract insights from medical records). Training in biostatistics is going to go a long way in this role.

Sectors Hiring Healthcare Analytics Graduates

You’ll have to do a bit of soul-searching to decide where you want to work after graduation. The healthcare industry is a massive body made up of a number of sectors, including:

• Providers: Hospitals, clinics, physicians, nursing homes, outpatient centers, home healthcare providers, rehabilitation centers, etc.
• Payers: Health insurance companies, government programs (e.g. Medicaid), employer-sponsored health plans, etc.
• Pharma: Pharmaceutical companies, R&D companies, biotechnology companies, drug manufacturers, etc.
• Medical Devices & Equipment: Manufacturers of diagnostic equipment or surgical devices, producers of medical supplies and consumables, etc.
• Health IT: Health apps, wearable technologies, EHR systems, telemedicine and telehealth services, health informatics companies, healthcare startups, etc.
• Public Health & Governmental Agencies: Public health departments, WHO, FDA, CDC, etc.
• Consulting & Support Services: Healthcare consulting firms, medical billing and coding companies, healthcare staffing and recruitment agencies, etc.
• Academic & Research Institutions: Medical schools, Clinical Research Organizations (CROs), etc.

Hospitals and clinical providers may offer a chance to make a difference in patient care, but you may like the idea of working with healthcare data from the Internet of Things. Or wrangling logistics data for medical materials or supplies. Or analyzing global trends in public health. As one Reddit user noted, “every area and every company have varying levels of data maturity, so it really depends on what you’re looking for.”

5 Key Career Tips from the Pros

Inside knowledge goes a long way in the world of healthcare. You’ll have a much better shot of landing that high-paying and high-satisfaction role if you’ve talked to current experts. Here are a few of the best tips from folks in the field, distilled from Reddit and mingled with our own advice.

1. Learn How the Industry Works: This advice came up time & again. If you haven’t worked in a healthcare setting, you need to get up-to-speed on coding & billing data, healthcare metrics, standard healthcare acronyms, healthcare regulations & compliance, and the work of clinicians—their specialties, their training, and their language. As one Reddit user noted, “we’ve hired dime-a-dozen data scientists who never pan out because they’re not interested in learning how healthcare works.” You can’t fake understanding in this field.
2. Address the Gaps in Your Knowledge: If you’re weak on the clinical side, use internships to work for multiple departments in multiple healthcare companies. Choose master’s degree electives in health informatics and medical realms. Complete IHI Open School training. If you’re strong on clinical & healthcare knowledge, but soft on technical skills, try to secure a mentorship with a data analyst in your organization. Earn analytics certificates and certifications. Take part in bootcamps. Make your own dashboards. Be honest about your shortcomings, whatever they may be.
3. Create a Healthcare Analytics Portfolio: You should be walking into the interview with plenty of real-world projects to lay on the table. One healthcare data analyst showed up with a dashboard for state inpatient data showcasing market share, revenue, and cost by procedure. Another brought pandas projects with patient care analysis, a programming project showcasing Python, and dashboards using public data from the hospital itself. Applied knowledge is everything in analytics.
4. Network Like Crazy During Your Master’s: The reason you’re forking out tens of thousands of dollars for a graduate degree in healthcare analytics is 1) reputation; and 2) connections. You can learn the hard skills anywhere. The real value of a master’s lies in taking advantage of faculty research interests, corporate partner opportunities, expert talks, peer networking, and any ties to your university’s healthcare systems. Never let a chance go by for an informational interview.
5. Understand the Technical Limitations of the Industry: Healthcare is full of weird and often antiquated systems. As an analyst, it can be incredibly frustrating dealing with people who don’t understand basic analytics ideas or databases that seem to have been created in the dark ages. And health data scientists may find it difficult to deploy their skills outside of big healthcare organizations or major research centers. Shadow folks if you can before you take the job.

Healthcare Analytics Job Titles & Salary Numbers

Sample Job Titles for Healthcare Analytics Graduates

You can plug the following titles into your AI prompts and job site searches. But you’ll also need to think about the employer. In a hospital, you might be responsible for improving patient outcomes. In a research company, you might be helping to catch diseases at the early stage. At a health insurance firm, you could be constantly searching for ways to cut costs. Think about what drives your passion.

Health Analytics

• Clinical Data Analyst
• Health Data Analyst
• Healthcare Analytics Manager
• Healthcare Analytics Senior Advisor
• Healthcare Strategy Consultant
• Health Services Data Analyst
• Medicare Compliance Data Analyst
• Pharmacy Data Analyst
• Public Health Data Analyst
• Senior Healthcare Data Analyst

Health Data Science

• Clinical Research Data Analyst
• Healthcare Data Scientist
• Health Outcomes Data Scientist
• Public Health Data Analyst
• Public Health Data Scientist

Health Informatics

• Clinical Informatics Analyst
• Clinical Informatics Manager
• Clinical Informatics Specialist
• Health Informatics Analyst
• Health Informatics Consultant
• Health Informatics Specialist
• Health IT Developer
• Health IT Project Manager
• Pharmacy Informaticist

Clinical & Management Roles

• Chief Medical Information Officer (CMIO)
• Clinical Informatics Director
• Clinical Research Manager
• Director of Client Strategy & Analytics
• Director of Healthcare Analytics
• Director of Health Informatics
• Health Data Consultant
• Medical Director
• Nurse Practitioner
• Physician
• VP of Quality

Salary Numbers for Healthcare Analytics Professionals

The healthcare industry doesn’t pay as much as the finance market, but it’s usually regarded as one of the more stable and lucrative fields for data analysts. Keep in mind that salary numbers are subject to fluctuations in the healthcare market and government investment.

Salary numbers from Glassdoor and Payscale will provide your AI algorithm with general estimates, but we always like to check in with the Bureau of Labor Statistics (BLS)!

Junior-Level Salaries

The BLS provides state & city wage maps for Health Information Technologists and Medical Registrars who “advise organizations on computerized healthcare systems and analyze clinical data.”

• Although these roles tend be on the junior end, pharmaceutical & medicine manufacturing companies are still willing to pay big bucks for their services. Medical and surgical hospitals hire the most technologists, but pay much less.
• The Northeast, West Coast, and Texas tend offer the best wages, but these areas can come with a high cost of living. Intriguingly, Minnesota also pays well. There’s a lot of healthcare research happening around the universities, Mayo Clinic, and the UnitedHealth Group!

Senior-Level Salaries

Anyone considering a senior-level job can investigate the wage maps for Medical and Health Service Managers who “plan, direct, or coordinate medical and health services in hospitals, clinics, managed care organizations, public health agencies, or similar organizations.”

• Wholesale trade agents and brokers are the top-paying industry for this category (think health insurance). Pharmaceutical & medicine manufacturers will also pay well.
• Senior-level salaries will be highest in healthcare powerhouse centers—think the Northeast and the West Coast, as well as the DC area. But medical adjacent areas (e.g. Southern New Hampshire) can also be generous.

We recommend you compare these data to the maps for Data Scientists and Operations Research Analysts. These wages won’t be specific to healthcare, but they’ll show you the value of data analysts and data scientists in the wider workplace.

Healthcare Analytics FAQ

How Much Does a Master of Science in Healthcare Analytics Program Cost?

The cost of an MSHA or closely related program will depend on multiple factors, including the university (e.g. Ivy League vs. Public), the School that’s offering the degree (e.g. Business vs. Public Health), the format of the program (e.g. campus vs. online), and the degree title. From our research:

• Online degrees in healthcare analytics range from $24,000-$30,000 on the affordable end to $45,000-$57,000 in the middle range. The most expensive options can exceed $70,000.
• Campus programs in healthcare analytics will be more expensive than online degrees. At some public universities, in-state tuition can range from $40,000-$55,000, but this can jump to $50,000-$85,000 for out-of-state students.
• Mid-tier health data science degrees are usually in the same ballpark as analytics offerings (e.g. $40,000-$60,000) but the price can skew much higher if you’re considering programs from prestigious schools like Columbia.

To offset the cost, many graduate students turn to their employers for tuition reimbursement and loan forgiveness plans. Or they apply for assistantships, fellowships, and STEM-focused scholarships. If you’re striking out on all your funding options, consider a part-time online degree with a monthly payment plan. This means you can continue working and avoid the slide into debt.

Is a Master’s Degree in Healthcare Analytics Critical for Job Applications?

Nope. For entry-level and junior data analyst positions in non-clinical positions, a bachelor’s degree in a STEM field is the standard requirement. Employers will probably be much more interested in your healthcare work experience, analytics certifications, and technical portfolio.

Having said that, a master’s degree can be a major selling point when you are:

• Applying for analytics jobs that involve clinical work (e.g. Clinical Analytics Analyst). Pharmaceutical companies and major healthcare systems will be wary of hiring folks who haven’t been properly trained to handle medical & patient data and statistical applications.
• Applying for data science roles (e.g. Healthcare Data Scientist). A master’s degree in data science or a closely related field is usually expected.
• Working toward promotion to a senior-level health analytics role. We always recommend chatting to your employer about the best choice for your degree (e.g. MSHA, MSHI, MSBA, MBA, etc.)—especially if they’re going to help pay for it!
• Interested in data-focused consulting and advisory roles in your field (e.g. public health).

What is a STEM-Designated Degree?

The U.S. Department of Homeland Security (DHS) grants this designation to undergraduate and graduate programs with significant coursework in Science, Technology, Engineering, and Mathematics (STEM) fields.

• International students graduating from STEM-designated programs can apply for a 24-month extension of their Optional Practical Training (OPT) period on their F-1 visa.
• This extension allows F-1 visa holders to work in the U.S. in their field of study for up to 3 years post-graduation. In contrast, graduates of non-STEM programs are only eligible for 1 year of OPT.

Master’s degrees specifically focused on healthcare analytics are often STEM-designated, but we advise you to confirm this with the program coordinator. Additionally, eligibility for an OPT extension may require enrollment in an on-campus or hybrid program.

What’s the Difference Between Healthcare Analytics & Health Informatics

As one expert on Reddit succinctly notes, health informatics is the “umbrella of all things health in technology and data, with an emphasis on insurance coding and EHR. Data analytics is a subset.”

Take a look at AHIMA’s career map to learn more about the HI umbrella. You’ll notice that informatics experts are also concerned with issues like data quality, revenue cycle management, and privacy, risk, compliance & security.

In a nutshell:

• Health Informatics (HI): The field of HI focuses on the development & management of healthcare information systems (e.g. EHRs); best practices for the collection, storage, and retrieval of health data (e.g. HIE); and the integration of IT solutions into healthcare settings. Think of areas like system design and data management.
• Healthcare Analytics: The field of healthcare analytics focuses on analyzing data from a wide range of sources to create actionable insights, predict future outcomes, and improve healthcare decisions. Examine the job description for more insights on this role.

Here’s what one health informatics expert liked about their job:

• “I can analyze data with the appreciation for what it took to decide why they wanted that data, how it was collected, how health equity was taken into account when collecting the data, how it’s programmed, what network and technological requirements are needed to collect data through an app or website, and then visualization to start determining target areas for improved patient outcomes.”

Here’s what one health data analyst liked about their job:

• “I can list dozens of projects including working directly with the FDA where we impacted patient outcomes in the long-term. We’ve impacted diagnosis rates for rare disease. I’ve gotten pharma companies to spit out free oncology medicine for populations for YEARS at a time. The work is so important and so gratifying.”

What Are Some Common Healthcare Analytics Acronyms?

Current Procedural Terminology (CPT®) Code: CPT codes are a uniform 5-digit code for coding medical services & procedures, performance measurements, and lab analyses. They’re widely used by health data analysts for reporting on areas such as cost analysis and service utilization, as well as for billing & reimbursement and quality improvement. The AMA has a helpful list of CPT types and criteria.

Electronic Data Interchange (EDI): EDI stands for “Electronic Data Interchange”—it’s a computer-to-computer way to securely transmit data between healthcare institutions, patients & insurers using specific data transmission protocols and uniform standards (e.g. EDI 835 transaction set for healthcare claims payment information). The HIPAA requires that all healthcare providers comply with privacy & security requirements when transmitting this kind of information. That’s why you’ll see references to the HIPAA EDI rule.

Electronic Health Record (EHR): An EHR is a real-time, digital version of a patient’s chart that centralizes patient info from multiple healthcare providers. It contains data on a patient’s medical history, diagnoses, treatment plans, immunizations, medications, lab & test results, and more. Because EHRs are pulling data from multiple sources, health data analysts often have to grapple with incompatible EHR systems, different input methods & data standards, and HIPAA regulations on data access & sharing. In addition, some EHR data can be unstructured (e.g. physician notes) and image-based (e.g. radiology results).

Electronic Medical Record (EMR): An EMR is a digital version of a patient’s medical chart from a single practice (e.g. primary care physician). It contains a patient’s medical records and information, but it’s primarily used to determine diagnoses and treatment plans within the practice.

Epic: Epic is the most common software used for EHR systems in hospitals and healthcare systems—it accounted for over 35% of the U.S. hospital market share in 2024. Becoming proficient in Epic gives you an edge in extracting, analyzing, and interpreting data from EHRs. Health data analysts can also use Epic to monitor & evaluate the quality of patient care, generate compliance reports, and track KPIs in order to meet regulatory requirements.

Fast Healthcare Interoperability Resources (FHIR): FHIR is a standard developed by HL7 for exchanging healthcare information using web-based technologies. It creates a common way of sharing information, regardless of the ways that local EHRs are representing & storing data (note the emphasis on “interoperability” in the acronym). FHIR is composed of a set of modular components, which HL7 calls “resources,” which can be integrated & understood across a variety of applications and devices.

Healthcare Common Procedure Coding System (HCPCS): HCPCS is a set of health care procedure codes based on the AMA’s Current Procedural Terminology (CPT®). Medicaid, Medicare, and health insurance programs use HCPCS to process medical claims in a consistent and standardized manner. HCPCS is divided into two main subsystems: Level I and Level II. Level I deals with CPT® codes. Level II deals with products, supplies & services that are not included in CPT® codes (e.g. ambulance services, durable medical equipment, prosthetics, etc.).

Healthcare Effectiveness Data and Information Set (HEDIS®): HEDIS® is a set of performance measures created by the National Committee for Quality Assurance (NCQA) to help rate healthcare plans. It assesses plans using 90+ measures across 6 domains of care, including effectiveness and access/availability. Health data analysts can also use it to benchmark their organization’s performance against national & regional averages and design quality improvement programs to enhance patient care.

Health Insurance Portability and Accountability Act (HIPAA): Enacted in 1996, HIPAA is a U.S. law that’s designed to protect sensitive patient health information and prohibit disclosures without the patient’s consent. HIPAA sets national standards for the security & privacy of health data in any form or media. It also includes provisions to streamline electronic healthcare transactions.

Health Level Seven International (HL7): HL7 is a set of global standards used for the exchange, integration, and sharing & retrieval of electronic health information. Older versions of HL7 standards (e.g. V2 and V3) are still used by healthcare organizations, especially in legacy systems. But FHIR provides a more flexible and modular approach to data exchange.

International Classification of Disease (ICD): Developed by the World Health Organization (WHO), ICD is a global diagnostic tool that provides a standardized system for classifying diseases, health conditions, and related health problems. Using ICD codes makes it easier for organizations—and health data analysts—to report and monitor diseases across different healthcare systems, states, and even countries.

SEPTEE: SEPTEE is a set of quality measures that stands for six domains of healthcare quality—Safety, Effectiveness, Patient-centeredness, Timeliness, Efficiency, and Equity—that were established by the Institute of Medicine (IOM), now known as the National Academy of Medicine (NAM). For example, health data analysts can use these domains to identify & mitigate risks, assess treatment outcomes, enhance patient experiences, reduce delays in care, streamline processes, and identify disparities in care.

What Are Healthcare Metrics? What Are Some Popular Metrics?

Healthcare metrics are designed to assess the performance, quality, and efficiency of healthcare services and systems. They’ve been established by organizations such as the Centers for Medicare & Medicaid Services (CMS) and the Agency for Healthcare Research & Quality (AHRQ).

Health data analysts are always using metrics and key performance indicators (KPIs) to generate data-driven insights and dashboards. Here are just a few examples of acronyms you may encounter in the healthcare sphere:

• Adverse Drug Event (ADE)
• Average Length of Stay (ALOS)
• Average Revenue Per Patient Visit (ARPV)
• Bed Occupancy Rate (BOR)
• Cost Per Patient Visit
• Cost Per Procedure
• Discharge Against Medical Advice (AMA) Rate
• ED Wait Times
• Excess Readmission Ratio (ERR)
• Hospital-Acquired Infection (HAI) Rate
• Healthcare-Associated Condition (HAC) Score
• Medication Error Rate
• Mortality Rate
• Patient Safety Indicators (PSIs)
• Patient Satisfaction Score (HCAHPS)
• Readmission Rate

How Do I Become Epic Certified?

Since Epic is the leading software for EHR systems, becoming an Epic certified analyst or Epic consultant can pay dividends in your career. But you can’t do it on your own.

1. Secure Sponsorship: You can start Epic training if you’re employed by a hospital or healthcare organization who has an Epic contract or you’re working for a consulting body that provides technical or operational services to Epic clients. Some employers will also help you earn Epic training as part of the on-boarding process after they hire you. However, you may be required to take the Epic Sphinx aptitude test to see if you’re a good candidate for certification.
2. Train with Epic: You’ll be sponsored by your employer to attend training sessions at the Epic Systems Corporation headquarters in Wisconsin or remotely. You’ll be schooled in the structure & operation of Epic software, as well as domain-specific modules.
3. Complete Modules: Epic offers a range of modules in different fields, including areas like clinical care, patient access, revenue cycles, data warehousing, and more. You’ll need to decide which modules are the most relevant to your work.
4. Pass Exams: Once you’ve completed your training, you’ll be required to pass the appropriate certification exams related to your modules. Hospitals may want you to pass your exams and achieve certification within a certain timeframe (e.g. 6 months).

Healthcare Analytics Resources & Organizations

Certifications

• Certified Analytics Professional (CAP®)
• Certified Coding Specialist (CCS®)
• Certified Health Data Analyst (CHDA®)
• Certified Health Informatics Systems Professional (CHISP®)
• Certified Professional in Healthcare Information and Management Systems (CPHIMS®)
• View Our List of Analytics Certifications

Conferences & Networking Events

• AMIA Annual Symposium
• Epic Expert Group Meetings (XGM)
• Epic Users Group Meeting (UGM)
• Healthcare Analytics Summit (HAS)
• HIMSS Global Health Conference
• View Our List of Analytics Conferences
• ViVE (Digital Health Tech)

Courses & Resources

• Google Data Analytics Certificate & Training
• Institute for Healthcare Improvement (IHI) Open School

Job Boards

• AMIA Job Board (Medical Informatics)
• HDAA Job Board
• HIMSS JobMine

Journals & Publications

• ACM Transactions on Computing for Healthcare
• Artificial Intelligence in Medicine
• Healthcare Analytics
• Health Data Science (HDS)
• Intelligence-Based Medicine
• International Journal of Big Data and Analytics in Healthcare (IJBDAH)
• International Journal of Medical Informatics
• Journal of the American Medical Informatics Association (JAMIA)
• Journal of Medical Artificial Intelligence (JMAI)

Organizations & Associations

• American Health Information Management Association (AHIMA)
• American Medical Informatics Association (AMIA)
• Healthcare Data & Analytics Association (HDAA)
• Healthcare Information and Management Systems Society (HIMSS)
• Institute for Health Metrics and Evaluation (IHME)
• View Our List of Analytics Organizations