Healthcare Analytics Certificate Program

healthcare professional at computer
Program at-a-Glance
15 months or less
5 online classes
$6,125

Improving Health Care Through Analytics

The increasing availability of electronic health data creates an incredible opportunity to apply large-scale, clinical analytics to improve health care, manage risks and improve patient outcomes. UC Davis Division of Continuing and Professional Education’s online Healthcare Analytics Certificate Program gives you the knowledge and practical skills to become a leader in this high-demand niche of the healthcare industry.

What You’ll Learn

This career-oriented program gives you the knowledge to succeed as a clinical and operational analyst in health care. Providing a strong foundation in the structure of healthcare data, it dives into hands-on coding, leaning more toward a data scientist, and exposes you to leading industry applications such as SQL, SAS and Tableau. You’ll graduate from the program with a comprehensive understanding of the use and implementation of healthcare analytics, including:

  • The changing context of healthcare services, the trend from volume to value-based purchasing and the role of data in promoting improved outcomes
  • How to construct data files using advanced statistical and data programming techniques
  • How to design data models that integrate patient data from multiple sources to create comprehensive, patient-centered views of data
  • Analytic strategy to frame a potential issue and solution relevant to health improvement of patient populations
  • Integrating clinical and business data to assess or compare the cost effectiveness of clinical interventions or processes
  • Analysis of the distribution of disease and health outcomes in relevant populations of interest
  • The application of clinical analytics to various contexts of quality improvement

How You’ll Benefit

The program features:

  • Online convenience
  • World-class curriculum developed in partnership with the nationally regarded UC Davis School of Medicine
  • Access to industry-leading instructors, including UC Davis faculty, who have significant experience in healthcare analytics
  • Hands-on access to analytics software and live data sets
  • Practical knowledge you can use immediately in the workplace
  • Small class sizes with exceptional networking opportunities
  • $96,116 average salary for data scientist (Glassdoor)
  • Data scientist is one of Glassdoor’s 25 Highest-Paying Jobs in the U.S. for 2018
  • Data scientist positions at U.S. companies has grown by over 650 percent since 2012, making it the number two job on LinkedIn’s top 20 emerging jobs list (LinkedIn 2017)
  • $80,357 average salary for healthcare analyst (Glassdoor)
  • $81,914 average salary for clinical analyst (Glassdoor)

Required Prerequisite: Completion of an introductory statistics course (Statistics 1 or equivalent) is required for Applied Healthcare Statistics. Students should understand and be able to apply the following concepts: variables and distributions, correlations, Null Hypothesis, regressions, group comparisons (t-tests and ANOVAs), generalized linear models. Students not comfortable with the preceding should take a refresher course. If you are unsure if a refresher course is necessary, review the Self-Exam for Applied Healthcare Statistics.

Recommended Prerequisite: Prior professional experience in health care or a previous background working with data and understanding of relational databases is strongly recommended but not required. Students with little or no relational database experience should include the SAS Primer course as part of their curricular plan.

Program Requirements: Courses may be taken individually or as part of the certificate program. The certificate is awarded upon the successful completion of five required courses (15 units), with a minimum grade of ‘C’ in each course and an overall average of ‘B’ or higher.

For more details please review our FAQs page.

Courses must be taken in sequential order: Introduction to Healthcare Analytics, Healthcare Data Acquisition and Management, Applied Healthcare Statistics, Data Mining for Healthcare Analytics, and Quantitative Methods of Decision Analysis.

Required Courses

Applied Healthcare Statistics
Quarter Academic Credit
3

Examine epidemiological concepts in health outcomes research and their use in evaluating the patterns, causes and effects of health in patient populations. Topics include study design; generalized linear models; internal and external validity; and methods to minimize bias, adjusting for confounding and measuring effect modification. Participants will learn to develop a testable hypothesis, build and refine analytic models and interpret results relevant to health outcomes.  

This is not a self-paced course. Students will progress through the course together. Lessons will be posted one week at a time. The previous week's lesson will remain available for the duration of the course. Students who enroll after the start date of the course will have to contact the instructor regarding missed lessons. 

Course Code
500052
Healthcare Data Acquisition and Management
Quarter Academic Credit
3

Learn to navigate complex data structures and efficiently retrieve the data needed to answer a question or solve a problem. Explore the types and sources of healthcare data, along with methods for selecting, preparing, querying and transforming healthcare data.

Examine the range of data sources, including:

  • Administrative, clinical, patient-reported and external data (e.g., CCDs, HL-7 messages)
  • Common representations of data in health information systems (ICD, CPT)
  • Strategies for optimizing data quality
  • Querying tools and methods
  • Data preparation/transformation
  • Ethics, data ownership and privacy

Also covered are new models of healthcare data organization and analytics, such as clinical registries and query health.  

This is not a self-paced course. Students will progress through the course together. Lessons will be posted one week at a time. The previous week's lesson will remain available for the duration of the course. Students who enroll after the start date of the course will have to contact the instructor regarding missed lessons. 

Students will learn the basics of SQL programming, or improve their SQL skills, within the concepts of other course topics.

Note: For students starting the Healthcare Analytics Certificate Program, you may take Healthcare Data and Acquisition and Management as your first course if Introduction to Healthcare Analytics is not offered in the quarter you begin the program.

Course Code
396690
Data Mining for Healthcare Analytics
Quarter Academic Credit
3

The proliferation of data in the post-EHR era creates opportunities for large-scale data analysis to discover meaningful patterns and trends. Explore the application of data mining techniques for purposes of big data analytics using administrative and clinical systems data. Topics include an overview of the data mining process, data mining standards and output protocols, and common techniques used in mining healthcare data. Also covered are visual representation methods that increase understanding of complex data.

This is not a self-paced course.  Students will progress through the course together.  Lessons will be posted one week at a time.  The previous week's lesson will remain available for the duration of the course.  Students who enroll after the start date of the course will have to contact the instructor regarding missed lessons.  This class will conduct one-mandatory synchronous Adobe Connect session towards the end of the course, please plan accordingly.

This class will conduct one-mandatory synchronous Adobe Connect session towards the end of the course, please plan accordingly.

Course Code
500006
Introduction to Healthcare Analytics
Quarter Academic Credit
3

With the increasing adoption of electronic health record systems, new forms of data are becoming available that can be used to measure healthcare delivery and improve patient outcomes. In this introductory course, participants explore the value proposition for clinical intelligence and the role of analytics in supporting a data-driven learning healthcare system. Key topics include:

  • The value-driven healthcare system
  • Measuring health system performance
  • Existing quality/performance measurement frameworks (NQF, HEDIS)
  • Comparing healthcare delivery
  • Attributes of high-performing healthcare systems
  • Definition and scope of business and clinical intelligence
  • Key components of healthcare analytics
  • The IT infrastructure and human capital needed to leverage analytics for health improvement

This is not a self-paced course.  Students will progress through the course together.  Lessons will be posted one week at a time.  The previous week's lesson will remain available for the duration of the course.  Students who enroll after the start date of the course will have to contact the instructor regarding missed lessons. Download the syllabus for this course.

Course Code
397120
Quantitative Methods and Decision Analysis
Quarter Academic Credit
3

Examine an array of quantitative methods used by health analytics practitioners to evaluate questions of efficiency and effectiveness in health care. This advanced course integrates and builds on prior coursework in statistics and data mining and provides additional exposure to advanced methodologies such as event sequencing, analytical groupers, simulation and predictive modeling. Heavy emphasis is given to the application of methods to contemporary analytic challenges in health care, including demand/utilization forecasting, risk stratification, population health management, quality measurement, fraud detection, and cost containment from readmissions.  Participants complete a series of hands-on assignments in the use of specific analytic approaches, as well as a final course project. 

This is not a self-paced course.  Students will progress through the course together.  Lessons will be posted one week at a time.  The previous week's lesson will remain available for the duration of the course.  Students who enroll after the start date of the course will have to contact the instructor regarding missed lessons. 

Course Code
500064

Courses must be taken in sequential order: Introduction to Healthcare Analytics, Healthcare Data Acquisition and Management, Applied Healthcare Statistics, Data Mining for Healthcare Analytics, and Quantitative Methods of Decision Analysis.

Required Courses

Required Courses Units Fall Winter Spring Summer
Applied Healthcare Statistics 3 Online Online
Healthcare Data Acquisition and Management 3 Online Online
Data Mining for Healthcare Analytics 3 Online Online
Introduction to Healthcare Analytics 3 Online Online
Quantitative Methods and Decision Analysis 3 Online Online
  • Program cost: $6,000 (or $1,200 per course)
  • See each course offering for discount opportunities
  • A one-time, nonrefundable registration fee of $125 must be paid before completing this certificate program
  • For more details, please review our FAQs page

For information about financing your education, please click here.

Ready to advance your career? Pick the option that best suits your needs and your lifestyle:

  • Register – Complete this brief certificate registration form and pay the registration fee. By doing so, you declare your intent to complete the program and lock in program requirements. Once you register, program staff will be available to answer any questions you may have and assist you with your course plan.
  • Enroll in an individual course Check out individual courses that are currently open for enrollment. Courses will be applied to a certificate program if you later decide to complete your certificate.

Questions? We’re here to help. If you’ve got a question, email us or call (530) 757-8899.