There is no required GPA for admission into the Master of Science in Health Data Analytics program. However, students in the program will need to maintain a 3.0 to graduate. Grades in previously taken courses relevant to the degree (math, statistics, etc.) will be a strong indication of student success in this program.
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Cassie Thompson
Online Enrollment Counselor
Online Master of Science in Health Data Analytics
The online Master of Science in Health Data Analytics is designed for professionals who want to start or build a career that advances the healthcare industry through data-driven actions and decisions.
Offered by the School of Public Health and Information Sciences at the University of Louisville (UofL), the online master’s in Health Data Analytics is designed to teach students how to leverage data, models, analytics methods and tools to solve challenges within the healthcare industry. Our graduates learn to combine healthcare tools and data analysis with patient care and service to form a unique perspective and develop actionable procedures for implementation and evaluation.
How Much Will I Pay?
$830 per credit hour
$250 per credit hour active-duty tuition rate
This program is a Title IV federal financial aid eligible program. Tuition rate does not include costs associated with a specific course or program, such as textbooks.
Please note that other fees apply – check our tuition page for all applicable costs.
Tuition, fees, and charges are subject to change and effective on the date enacted.For additional information on educational expenses and the Cost of Attendance, please visit the Student Financial Aid Office website.
Highlights
- Join a reputable graduate program from a top Public Health school (Ranked by U.S. News & World Report, 2020)
- Gain expertise and highly marketable skills in a rapidly growing field
- Prepare for the Certified Health Data Analyst (CHDA) Examination
- Learn from world-class faculty with extensive applied experience
- Complete your degree in as little as 3 semesters; extended part-time option also available
- Take advantage of the convenience of 100% online classes
- Access courses and resources anytime, anywhere
Online Graduate Certificates
Specialize your knowledge and add valuable credentials to your career portfolio by pursuing an online certificate while completing your master’s degree. Several MSHDA courses are a part of the online Certificate in AI Medicine and the online Certificate in Biostatistics curriculum. Leverage your MSHDA course requirements towards the following certificates*:
- Graduate Certificate in Artificial Intelligence in Medicine (15 credit hours)
- Graduate Certificate in Biostatistics (15-16 credit hours)
*Additional courses in other areas are required for certificate completion in Biostatistics and AI Medicine.
100% ONLINE COURSES
Complete this degree on your own time through fully online classes.
Learn More
33 CREDIT HOURS
Complete just 9 core courses, 1 CHDA prep course and a practicum in your local community to earn your health data analytics master's degree.
Learn More
1 PRACTICUM
Complete at any healthcare-focused data analytics organization in your local area.
Learn More
"Graduates of the online health data analytics program will be prepared for careers as health care analytics consultants, big data scientists, clinical analysts, analytics managers, professional services, along with positions in IT, finance and insurance."
DR. BERT LITTLE
PROGRAM DIRECTOR
M.S. IN HEALTH DATA ANALYTICS
LEARN MORE
Outcomes
A Master of Science in Health Data Analytics from UofL prepares students for a wide variety of career paths within the healthcare industry and beyond. They may choose to pursue jobs such as:
- Chief Information Officer
- Chief Population Health Officer
- Clinical Data Manager
- Corporate Strategy Manager
- Health Analytics Specialist
- Health Informatics/Data Consultant
- Healthcare Data Analyst
- Implementation Specialist
| Preferred Application Deadline | Term | Start |
|---|---|---|
| May 15 | Priority Deadline for scholarships/internships* for Fall & Spring | August |
| July 1 | Fall | August |
| Applications are not accepted at this time for the Spring 2025 term. | ||
*Contact Deepti Jain for more Information about department scholarships and internships.
Note: We admit students on a rolling basis. The preferred deadlines help you complete the application process on time, be notified of acceptance and enroll before the term begins. We review applications as they become complete, and admit students for a specific term up to the day classes start. We recommend you work on and submit your complete application well in advance of the preferred deadline, as obtaining transcripts and other materials may take more time.
How to Apply for the Online Master of Science in Health Data Analytics
- Start your application for graduate admission
- Submit $65 non-refundable application fee
- Upload required materials*
- Request official transcripts from all previously attended colleges and universities. Transcripts are only accepted directly from the institution(s) by email: gradadm@louisville.edu (recommended) or mail: University of Louisville, Graduate School, 2211 S. Brook St., Louisville, KY 40292.
- Create a financial plan
Online Master of Science in Health Data Analytics Admissions Requirements and Materials
To be considered for admission, applicants must have:
- a bachelor’s degree or its equivalent from an accredited institution
- a minimum undergraduate GPA of 3.0 on a 4.0 scale (applicants who do not meet the minimum GPA may inquire about conditional acceptance)
*Required application packet materials include:
- transcripts showing a degree in biostatistics, statistics, mathematics,computer science or a related quantitative discipline AND competency in statistics and regression analysis; college-level calculus is also recommended
- a statement of goals (i.e., general research interests)
- a current curriculum vitae (CV) or resume
- two letters of recommendation
- interview with the HMSS Health Leadership Committee
*Your Application Portal:
Once you have started the graduate application, you can check the status and review any additional checklist to-do items. Log in to your application using the email address you used to apply for admission and your password. Your checklist items may include additional materials or documentation that facilitate a smooth admissions process. You will also have access to important contact information and next steps after an admissions decision is made.
Online Master of Science in Health Data Analytics for International Applicants
The Health Data Analytics master’s program is open to international students. Additional requirements apply.
- All transcripts not in English must be certified as authentic and translated verbatim in English.
- Students whose primary language is not English must show English language proficiency by attaining one of the following:
- Test of English as a Foreign Language (TOEFL) exam with a minimum score of 79 OR
- IELTS score of 6.5 or higher OR
- Duolingo English score of 105 or higher OR
- Degree from an accredited U.S. institution (requires provisional admission with evaluation of English language competency)
- International students will not be issued a U.S. visa if admitted to an online program, since there are no campus attendance requirements.
For more information on the admission and application process, please contact our Online Learning Enrollment Counselors at 800.871.8635 or by email at online@louisville.edu.
The online Master of Science in Health Data Analytics is a 33-credit hour program that requires:
- 27 credit hours in core courses
- 3 credit hours of practicum in a real-world data analytics program at an organization of choice
- 3 credit hours of capstone course preparation for the Certified Health Data Analyst (CHDA) examination
To graduate, students must have an overall 3.0 GPA in coursework. A part-time degree path is also available.
Full-Time Degree Path
| Course Title | Credit Hours | |
|---|---|---|
| Semester I | PHPH 523 Public Health in the U.S. | [3] |
| PHST 620 Introduction to Statistical Computing | 3 | |
| PHST 680 Biostatistical Methods I | 3 | |
| PHMS 644 Biomedical Foundation for Health Data Analytics | 3 | |
| Semester Total | 9 [12] | |
| Semester II | PHMS 670 Statistical Data Management | 3 |
| PHMS 641 Data Mining I | 3 | |
| PHMS 638 Data Security & Electronic Health Records | 3 | |
| PHMS 639 Health Data Analytics Practicum | 3 | |
| Semester Total | 12 | |
| Semester III | PHMS 671 Statistical Analysis for Population Health | 3 |
| PHMS 643 Data Management In Health Service Research | 3 | |
| PHMS 642 Data Mining II | 3 | |
| PHMS 637 MSHDA Capstone Course | 3 | |
| Semester Total | 12 | |
| DEGREE TOTAL | 33 | |
Part-Time Degree Path
Part-time students must be cognizant that courses are offered on an alternating basis, usually every two years. Thus, part-time students must pursue the recommended course sequence for analytics courses because courses build upon skills acquired in prior courses.
Students enrolled in the part-time option are able to complete their degree in 48 months or less if they take 6 credits per semester and plan their degree path to meet the following course sequence. Note: courses other than the quantitative ones may be taken in any order, throughout the duration of the program.
Course Descriptions
PHMS 637 MSHDA Capstone Course
This course is designed to provide final preparation of the student to sit for the Certified Health Data Analyst Examination offered by the Commission on Accreditation for Health Informatics and Information Management (CAHIIM) and the American Health Information Management Association (AHIMA). The certification with the MSHDA degree provides prospective employers evidence of the student’s ability to perform professional level health data analytics. This course is also intended to provide a cumulative, rigorous, and discovery-based project.
PHMS 638 Data Security & Electronic Health Records
The course will focus on the framework, the real-world use, and the critical data security issues in deployment of Electronic Health Records (EHRs) to improve the quality of health care delivery. Students will learn functionality of EHRs through hands-on labs, technical infrastructures require for EHRs (e.g., architecture, network, security design), understand how EHRs change healthcare delivery workflows, best practice for deploying EHRs (e.g., project management, typical budgets, system selection, HIPAA governmental requirements, funding), and data security-related issues critical to EHRs implementation.
PHMS 639 Health Data Analytics Practicum
The practicum experience places the student in a non-academic environment where health data analytics are used for decision support and strategic planning. The deliverables will include (1) a written report to the instructor on the experience gained during the practicum, and (2) an outline on the activities specific to the site where the practicum is completed. The practicum should include no less than 200 contact hours at the practicum site. The manager at the practicum site will be asked to complete an evaluation of the student.
PHMS 641 Data Mining I
The course is first in a two-semester sequence graduate level introduction to data mining/big data analytics. It focuses on practical implementation and interpretation of the most commonly used techniques in analysis of very large datasets.
PHMS 642 Data Mining II
This is the second of a two-semester graduate level course on data mining/big data analytics. It focuses on practical implementation and interpretation of the most commonly used techniques in analysis of very large datasets.
PHMS 643 Data Management in Health Service Research
Course allows students to pursue study with faculty guidance on data management in health service research.
PHMS 644 Biomedical Foundations for Health Analytics
This course will offer an integrative molecular and biological perspective on public health problems and health data analytics. Students will explore population biology and ecological principles underlying public health and reviews molecular biology in relation to public health biology. Lectures focus on specific diseases of viral, bacterial, and environmental origin. Instructors will use specific examples of each type to develop the general principles that govern interactions among susceptible organisms and etiologic agents and devotes special attention to factors that act in reproduction and development. The course will focus on common elements including origin and dissemination of drug resistance, organization and transmission of virulence determinants, modulation of immune responses, disruption of signal transduction pathways, perturbation of gene expression, as well as the role of the genetic constitution of the host.
PHMS 670 Statistical Data Management
The course is designed as an introduction to data management and analysis in SAS (Statistical Analysis System) and Stat (Stat Statistical Software). Data management and graphics will be practiced, and linear regression basics where data summary, regression in levels and logs, correlation analysis, hypothesis testing, specification analysis, prediction, using sampling weights, and model diagnostics will be discussed. This course covers all components of econometric modeling, namely, model selection, estimation, diagnostic checks, and model re-specification. Health data will be used in both midterm and final projects of the course.
PHMS 671 Statistical Analysis for Population Health
Pre-Requisite: PHMS 670 or Instructor permission. This course is designed as an introduction to statistical analysis for population health in IBM SPSS Statistics 26.0 software package. The course covers basic components of statistical analysis for population health including linear regression, logistic regression, Cox regression, propensity score analysis, cluster analysis, discriminant analysis, multivariate analysis of covariance, repeated measures, and regression trees. Health data will mainly be used in examples and the final project of the course.
PHPH 523 Public Health in the U.S.
Course covers the history of and issues facing public health in the United States.
PHST 620 Introduction to Statistical Computing
Prerequisite: Enrolled in PH MPH and PHST 500. This course introduces SAS. It will give students an overview of the SAS system under MS Windows and provide fundamental grounding in the environment for accessing, structuring, formatting and manipulating data. Students will learn how to summarize and display data, and the inference between data steps and procedures to get information out of data.
PHST 680 Biostatistical Methods
A mathematically sophisticated presentation of statistical principles and methods. Topics include exploratory data analysis, graphical methods, point and interval estimation, hypothesis testing, and categorical data analysis. Matrix algebra is required. Data sets drawn from biomedical and public health literature will be analyzed using statistical computer packages.
-
What GPA do I need to enter the program?
-
What GRE score do I need to be accepted into the program?
GRE scores are not required for admission into the program. However, a strong quantitative background is recommended.
-
What is the Certified Health Data Analyst (CHDA) Examination?
In addition to receiving your master’s degree, the CHDA certification from the American Health Information Management Association boosts your professional credentials and reputation as a health data expert. Completing your master’s program with UofL will effectively prepare you to sit for this exam, but it is by no means a requirement for graduating from the program.
-
Where and when will I complete the practicum component of the program?
The practicum is an exciting component of the program that allows you to get hands-on learning experience in the health data analytics field. The practicum will be completed at a location of your choice, within your local community (note: you can complete your practicum with your current employer, but the work completed cannot be part of your day-to-day job tasks). Full-time students will complete the practicum during the summer between their first and second year in the program (part-time students should speak with an enrollment counselor for more information).
-
How does this program differ from the online Master of Science in Biostatistics program also offered from the College of Public Health?
Health Data Analytics and Biostatistics are both viable degree options for a career in healthcare data information analysis. At their core, both programs deal with analysis and interpretation of healthcare data with innovative tools like machine learning, artificial intelligence and analytics.
The differences are in how the data is manipulated, structured, and analyzed. Biostatisticians will typically work with clean data sets, looking for answers to specific, targeted questions related directly to the research project.
Data Analysts take a broader look and are typically responsible for data cleansing and preparation. Data analysts analyze information to explore connections and insights that might not yet be identified. In other words, Biostatistics is a more theory-based, whereas Health Data Analytics includes ‘data wrangling’ and looks at population level health and outcomes.
-
Can I transfer graduate-level credits from another university?
You can transfer up to six credit hours from another regionally accredited university.
However, to be accepted, the content in the courses you have completed must closely match the required courses for the master’s in Health Data Analytics at UofL.
The program will consider your transfer coursework when you submit your application.
How Much Will I Pay?
$830 per credit hour
$250 per credit hour active-duty tuition rate
This program is a Title IV federal financial aid eligible program. Tuition rate does not include costs associated with a specific course or program, such as textbooks.
Please note that other fees apply – check our tuition page for all applicable costs.
Tuition, fees, and charges are subject to change and effective on the date enacted.For additional information on educational expenses and the Cost of Attendance, please visit the Student Financial Aid Office website.
Highlights
- Join a reputable graduate program from a top Public Health school (Ranked by U.S. News & World Report, 2020)
- Gain expertise and highly marketable skills in a rapidly growing field
- Prepare for the Certified Health Data Analyst (CHDA) Examination
- Learn from world-class faculty with extensive applied experience
- Complete your degree in as little as 3 semesters; extended part-time option also available
- Take advantage of the convenience of 100% online classes
- Access courses and resources anytime, anywhere
Online Graduate Certificates
Specialize your knowledge and add valuable credentials to your career portfolio by pursuing an online certificate while completing your master’s degree. Several MSHDA courses are a part of the online Certificate in AI Medicine and the online Certificate in Biostatistics curriculum. Leverage your MSHDA course requirements towards the following certificates*:
- Graduate Certificate in Artificial Intelligence in Medicine (15 credit hours)
- Graduate Certificate in Biostatistics (15-16 credit hours)
*Additional courses in other areas are required for certificate completion in Biostatistics and AI Medicine.
100% ONLINE COURSES
Complete this degree on your own time through fully online classes.
Learn More
33 CREDIT HOURS
Complete just 9 core courses, 1 CHDA prep course and a practicum in your local community to earn your health data analytics master's degree.
Learn More
1 PRACTICUM
Complete at any healthcare-focused data analytics organization in your local area.
Learn More"Graduates of the online health data analytics program will be prepared for careers as health care analytics consultants, big data scientists, clinical analysts, analytics managers, professional services, along with positions in IT, finance and insurance."
DR. BERT LITTLE
PROGRAM DIRECTOR
M.S. IN HEALTH DATA ANALYTICS
LEARN MORE
Outcomes
A Master of Science in Health Data Analytics from UofL prepares students for a wide variety of career paths within the healthcare industry and beyond. They may choose to pursue jobs such as:
- Chief Information Officer
- Chief Population Health Officer
- Clinical Data Manager
- Corporate Strategy Manager
- Health Analytics Specialist
- Health Informatics/Data Consultant
- Healthcare Data Analyst
- Implementation Specialist
| Preferred Application Deadline | Term | Start |
|---|---|---|
| May 15 | Priority Deadline for scholarships/internships* for Fall & Spring | August |
| July 1 | Fall | August |
| Applications are not accepted at this time for the Spring 2025 term. | ||
*Contact Deepti Jain for more Information about department scholarships and internships.
Note: We admit students on a rolling basis. The preferred deadlines help you complete the application process on time, be notified of acceptance and enroll before the term begins. We review applications as they become complete, and admit students for a specific term up to the day classes start. We recommend you work on and submit your complete application well in advance of the preferred deadline, as obtaining transcripts and other materials may take more time.
How to Apply for the Online Master of Science in Health Data Analytics
- Start your application for graduate admission
- Submit $65 non-refundable application fee
- Upload required materials*
- Request official transcripts from all previously attended colleges and universities. Transcripts are only accepted directly from the institution(s) by email: gradadm@louisville.edu (recommended) or mail: University of Louisville, Graduate School, 2211 S. Brook St., Louisville, KY 40292.
- Create a financial plan
Online Master of Science in Health Data Analytics Admissions Requirements and Materials
To be considered for admission, applicants must have:
- a bachelor’s degree or its equivalent from an accredited institution
- a minimum undergraduate GPA of 3.0 on a 4.0 scale (applicants who do not meet the minimum GPA may inquire about conditional acceptance)
*Required application packet materials include:
- transcripts showing a degree in biostatistics, statistics, mathematics,computer science or a related quantitative discipline AND competency in statistics and regression analysis; college-level calculus is also recommended
- a statement of goals (i.e., general research interests)
- a current curriculum vitae (CV) or resume
- two letters of recommendation
- interview with the HMSS Health Leadership Committee
*Your Application Portal:
Once you have started the graduate application, you can check the status and review any additional checklist to-do items. Log in to your application using the email address you used to apply for admission and your password. Your checklist items may include additional materials or documentation that facilitate a smooth admissions process. You will also have access to important contact information and next steps after an admissions decision is made.
Online Master of Science in Health Data Analytics for International Applicants
The Health Data Analytics master’s program is open to international students. Additional requirements apply.
- All transcripts not in English must be certified as authentic and translated verbatim in English.
- Students whose primary language is not English must show English language proficiency by attaining one of the following:
- Test of English as a Foreign Language (TOEFL) exam with a minimum score of 79 OR
- IELTS score of 6.5 or higher OR
- Duolingo English score of 105 or higher OR
- Degree from an accredited U.S. institution (requires provisional admission with evaluation of English language competency)
- International students will not be issued a U.S. visa if admitted to an online program, since there are no campus attendance requirements.
For more information on the admission and application process, please contact our Online Learning Enrollment Counselors at 800.871.8635 or by email at online@louisville.edu.
The online Master of Science in Health Data Analytics is a 33-credit hour program that requires:
- 27 credit hours in core courses
- 3 credit hours of practicum in a real-world data analytics program at an organization of choice
- 3 credit hours of capstone course preparation for the Certified Health Data Analyst (CHDA) examination
To graduate, students must have an overall 3.0 GPA in coursework. A part-time degree path is also available.
Full-Time Degree Path
| Course Title | Credit Hours | |
|---|---|---|
| Semester I | PHPH 523 Public Health in the U.S. | [3] |
| PHST 620 Introduction to Statistical Computing | 3 | |
| PHST 680 Biostatistical Methods I | 3 | |
| PHMS 644 Biomedical Foundation for Health Data Analytics | 3 | |
| Semester Total | 9 [12] | |
| Semester II | PHMS 670 Statistical Data Management | 3 |
| PHMS 641 Data Mining I | 3 | |
| PHMS 638 Data Security & Electronic Health Records | 3 | |
| PHMS 639 Health Data Analytics Practicum | 3 | |
| Semester Total | 12 | |
| Semester III | PHMS 671 Statistical Analysis for Population Health | 3 |
| PHMS 643 Data Management In Health Service Research | 3 | |
| PHMS 642 Data Mining II | 3 | |
| PHMS 637 MSHDA Capstone Course | 3 | |
| Semester Total | 12 | |
| DEGREE TOTAL | 33 | |
Part-Time Degree Path
Part-time students must be cognizant that courses are offered on an alternating basis, usually every two years. Thus, part-time students must pursue the recommended course sequence for analytics courses because courses build upon skills acquired in prior courses.
Students enrolled in the part-time option are able to complete their degree in 48 months or less if they take 6 credits per semester and plan their degree path to meet the following course sequence. Note: courses other than the quantitative ones may be taken in any order, throughout the duration of the program.
Course Descriptions
PHMS 637 MSHDA Capstone Course
This course is designed to provide final preparation of the student to sit for the Certified Health Data Analyst Examination offered by the Commission on Accreditation for Health Informatics and Information Management (CAHIIM) and the American Health Information Management Association (AHIMA). The certification with the MSHDA degree provides prospective employers evidence of the student’s ability to perform professional level health data analytics. This course is also intended to provide a cumulative, rigorous, and discovery-based project.
PHMS 638 Data Security & Electronic Health Records
The course will focus on the framework, the real-world use, and the critical data security issues in deployment of Electronic Health Records (EHRs) to improve the quality of health care delivery. Students will learn functionality of EHRs through hands-on labs, technical infrastructures require for EHRs (e.g., architecture, network, security design), understand how EHRs change healthcare delivery workflows, best practice for deploying EHRs (e.g., project management, typical budgets, system selection, HIPAA governmental requirements, funding), and data security-related issues critical to EHRs implementation.
PHMS 639 Health Data Analytics Practicum
The practicum experience places the student in a non-academic environment where health data analytics are used for decision support and strategic planning. The deliverables will include (1) a written report to the instructor on the experience gained during the practicum, and (2) an outline on the activities specific to the site where the practicum is completed. The practicum should include no less than 200 contact hours at the practicum site. The manager at the practicum site will be asked to complete an evaluation of the student.
PHMS 641 Data Mining I
The course is first in a two-semester sequence graduate level introduction to data mining/big data analytics. It focuses on practical implementation and interpretation of the most commonly used techniques in analysis of very large datasets.
PHMS 642 Data Mining II
This is the second of a two-semester graduate level course on data mining/big data analytics. It focuses on practical implementation and interpretation of the most commonly used techniques in analysis of very large datasets.
PHMS 643 Data Management in Health Service Research
Course allows students to pursue study with faculty guidance on data management in health service research.
PHMS 644 Biomedical Foundations for Health Analytics
This course will offer an integrative molecular and biological perspective on public health problems and health data analytics. Students will explore population biology and ecological principles underlying public health and reviews molecular biology in relation to public health biology. Lectures focus on specific diseases of viral, bacterial, and environmental origin. Instructors will use specific examples of each type to develop the general principles that govern interactions among susceptible organisms and etiologic agents and devotes special attention to factors that act in reproduction and development. The course will focus on common elements including origin and dissemination of drug resistance, organization and transmission of virulence determinants, modulation of immune responses, disruption of signal transduction pathways, perturbation of gene expression, as well as the role of the genetic constitution of the host.
PHMS 670 Statistical Data Management
The course is designed as an introduction to data management and analysis in SAS (Statistical Analysis System) and Stat (Stat Statistical Software). Data management and graphics will be practiced, and linear regression basics where data summary, regression in levels and logs, correlation analysis, hypothesis testing, specification analysis, prediction, using sampling weights, and model diagnostics will be discussed. This course covers all components of econometric modeling, namely, model selection, estimation, diagnostic checks, and model re-specification. Health data will be used in both midterm and final projects of the course.
PHMS 671 Statistical Analysis for Population Health
Pre-Requisite: PHMS 670 or Instructor permission. This course is designed as an introduction to statistical analysis for population health in IBM SPSS Statistics 26.0 software package. The course covers basic components of statistical analysis for population health including linear regression, logistic regression, Cox regression, propensity score analysis, cluster analysis, discriminant analysis, multivariate analysis of covariance, repeated measures, and regression trees. Health data will mainly be used in examples and the final project of the course.
PHPH 523 Public Health in the U.S.
Course covers the history of and issues facing public health in the United States.
PHST 620 Introduction to Statistical Computing
Prerequisite: Enrolled in PH MPH and PHST 500. This course introduces SAS. It will give students an overview of the SAS system under MS Windows and provide fundamental grounding in the environment for accessing, structuring, formatting and manipulating data. Students will learn how to summarize and display data, and the inference between data steps and procedures to get information out of data.
PHST 680 Biostatistical Methods
A mathematically sophisticated presentation of statistical principles and methods. Topics include exploratory data analysis, graphical methods, point and interval estimation, hypothesis testing, and categorical data analysis. Matrix algebra is required. Data sets drawn from biomedical and public health literature will be analyzed using statistical computer packages.
-
What GPA do I need to enter the program?
There is no required GPA for admission into the Master of Science in Health Data Analytics program. However, students in the program will need to maintain a 3.0 to graduate. Grades in previously taken courses relevant to the degree (math, statistics, etc.) will be a strong indication of student success in this program.
-
What GRE score do I need to be accepted into the program?
GRE scores are not required for admission into the program. However, a strong quantitative background is recommended.
-
What is the Certified Health Data Analyst (CHDA) Examination?
In addition to receiving your master’s degree, the CHDA certification from the American Health Information Management Association boosts your professional credentials and reputation as a health data expert. Completing your master’s program with UofL will effectively prepare you to sit for this exam, but it is by no means a requirement for graduating from the program.
-
Where and when will I complete the practicum component of the program?
The practicum is an exciting component of the program that allows you to get hands-on learning experience in the health data analytics field. The practicum will be completed at a location of your choice, within your local community (note: you can complete your practicum with your current employer, but the work completed cannot be part of your day-to-day job tasks). Full-time students will complete the practicum during the summer between their first and second year in the program (part-time students should speak with an enrollment counselor for more information).
-
How does this program differ from the online Master of Science in Biostatistics program also offered from the College of Public Health?
Health Data Analytics and Biostatistics are both viable degree options for a career in healthcare data information analysis. At their core, both programs deal with analysis and interpretation of healthcare data with innovative tools like machine learning, artificial intelligence and analytics.
The differences are in how the data is manipulated, structured, and analyzed. Biostatisticians will typically work with clean data sets, looking for answers to specific, targeted questions related directly to the research project.
Data Analysts take a broader look and are typically responsible for data cleansing and preparation. Data analysts analyze information to explore connections and insights that might not yet be identified. In other words, Biostatistics is a more theory-based, whereas Health Data Analytics includes ‘data wrangling’ and looks at population level health and outcomes.
-
Can I transfer graduate-level credits from another university?
You can transfer up to six credit hours from another regionally accredited university.
However, to be accepted, the content in the courses you have completed must closely match the required courses for the master’s in Health Data Analytics at UofL.
The program will consider your transfer coursework when you submit your application.
