Twin Cities campus

This is archival data. This system was retired as of August 21, 2023 and the information on this page has not been updated since then. For current information, visit catalogs.umn.edu.

 
Twin Cities Campus

Health Informatics M.S.

Health Informatics, AHC Inst
Graduate School
Link to a list of faculty for this program.
Contact Information
Physical Address: 505 Essex St. SE, 330 Diehl Hall, Minneapolis, MN 55455 Mailing Address: MMC 912, 420 Delaware St. SE, Minneapolis, MN 55455
Email: ihi@umn.edu
Website: http://www.bmhi.umn.edu
  • Program Type: Master's
  • Requirements for this program are current for Fall 2014
  • Length of program in credits: 36
  • This program does not require summer semesters for timely completion.
  • Degree: Master of Science
Along with the program-specific requirements listed below, please read the General Information section of this website for requirements that apply to all major fields.
Health informatics is an interdisciplinary field of scholarship that applies computer, information, and cognitive sciences to promote the effective and efficient use and analysis of information, ultimately improving the health, well-being, and economic functioning of society. Students take a sequence of core courses in health informatics and biostatistics, and electives in technical and health science areas. Possible areas of emphasis include health information systems, telehealth, bioinformatics, user interface design, system impact evaluation, database construction and analysis, clinical decision-making, evaluation of health programs, and physiological monitoring and control. The MS is a 36 credit degree that may be completed in as little as two years or up to five years. It is intended for students who are interested in research, but who do not have the background or are not ready to commit to the PhD program. There are two kinds of MS degrees: MS Plan A and MS Plan B. The Plan A culminates in a substantial, 10-credit master's thesis. The Plan B culminates in a smaller, 4-credit, Plan B project. Electives comprise the additional six credits in the Plan B degree.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
  • partially online (between 50% to 80% of instruction is online)
Prerequisites for Admission
The preferred undergraduate GPA for admittance to the program is 3.30.
Applicants are expected to have at least a bachelor of science or equivalent degree from a regionally accredited institution of higher education.
Required prerequisites
Health or Biological Sciences
6-semester credits or 9 quarter-credits of health or biological coursework at the undergraduate or graduate level. HINF 5501 may be used to help meet this requirement.
or Department Consent
Programming Language
Documented work or educational experience working with a programming language such as C, C++, Java, Visual Basic, PASCAL, etc.
or HINF 5502 - Python Programming Essentials for the Health Sciences (1.0 cr)
or Department Consent
Applicants must submit their test score(s) from the following:
  • GRE
    • General Test - Verbal Reasoning: 152
    • General Test - Quantitative Reasoning: 159
    • General Test - Analytical Writing: 4.0
International applicants must submit score(s) from one of the following tests:
  • TOEFL
    • Internet Based - Total Score: 79
    • Internet Based - Writing Score: 21
    • Internet Based - Reading Score: 19
    • Paper Based - Total Score: 550
  • IELTS
    • Total Score: 6.5
  • MELAB
    • Final score: 80
The preferred English language test is Test of English as Foreign Language.
Key to test abbreviations (GRE, TOEFL, IELTS, MELAB).
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
Plan A: Plan A requires 15 to 17 major credits, 9 to 11 credits outside the major, and 10 thesis credits. The final exam is written and oral.
Plan B: Plan B requires 19 to 27 major credits and 9 to 17 credits outside the major. The final exam is written and oral.
This program may be completed with a minor.
Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser approval.
A minimum GPA of 3.00 is required for students to remain in good standing.
At least 1 semesters must be completed before filing a Degree Program Form.
Required HINF Courses
N.b. All students must take AHC Informatics Grand Rounds (HINF 5436) twice for a total of two credits.
HINF 5430 - Foundations of Health Informatics I (3.0 cr)
HINF 5431 - Foundations of Health Informatics II (3.0 cr)
HINF 5436 - AHC Informatics Grand Rounds (1.0 cr)
HINF 5510 - Applied Health Care Databases: Database Principles and Data Evaluation (3.0 cr)
HINF 5520 - Informatics Methods for Health Care Quality, Outcomes, and Patient Safety (2.0 cr)
HINF 5531 - Health Data Analytics and Data Science (3.0 cr)
Other Required Courses
NURS 5116 - Consumer Health Informatics (2.0 cr)
NURS 7113 - Clinical Decision Support: Theory (2.0 cr)
PUBH 6450 - Biostatistics I (4.0 cr)
Final Project/Thesis
Plan A students will take 10 credits of 8777 and Plan B students will take 4 credits of 8770.
HINF 8770 - Plan B Project (4.0 cr)
or HINF 8777 - Thesis Credits: Master's (1.0-18.0 cr)
Electives
Graduate-level electives of your choice; see student handbook for a list of recommended electives. Plan A students will need 4 credits of electives, and Plan B students will need 10 credits of electives.
 
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HINF 5502 - Python Programming Essentials for the Health Sciences
Credits: 1.0 [max 1.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall & Spring
Computer programming essentials for health sciences/health care applications using Python 3. Intended for students with limited programming background, or students wishing to obtain proficiency in Python programming language. prereq: Junior or senior or grad student or professional student or instr consent
HINF 5430 - Foundations of Health Informatics I
Credits: 3.0 [max 3.0]
Typically offered: Every Fall & Spring
An introductory survey of health informatics, focusing on foundational concepts. Topics covered include: conceptualizations of data, information, and knowledge; current terminologies, coding, and classification systems for medical information; ethics, privacy, and security; systems analysis, process and data modeling; human-computer interaction and data visualization. Lectures, readings, and exercises highlight the intersections of these topics with electronic health record systems and other health information technology. prereq: Junior, senior, grad student, professional student, or instr consent
HINF 5431 - Foundations of Health Informatics II
Credits: 3.0 [max 3.0]
Typically offered: Every Spring
An introductory survey of health informatics, focusing on applications of informatics concepts and technologies. Topics covered include: health informatics research, literature, and evaluation; precision medicine; decision models; computerized decision support systems; data mining, natural language processing, social media, rule-based system, and other emerging technologies for supporting 'Big Data' applications; security for health care information handling. Lectures, readings, and exercises highlight the intersections of these topics with current information technology for clinical care and research. prereq: Junior, senior, grad student, professional student, or instr consent
HINF 5436 - AHC Informatics Grand Rounds
Credits: 1.0 [max 10.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Presentation/discussion of research problems, current literature/topics of interest in Health Informatics.
HINF 5510 - Applied Health Care Databases: Database Principles and Data Evaluation
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
Principles of database theory, modeling, design, and manipulation of databases will be introduced, taught with a healthcare applications emphasis. Students will gain experience using a relational database management system (RDBMS), and database manipulation will be explored using Structured Query Language (SQL) to compose and execute queries. Students will be able to critically evaluate database query methods and results, and understand their implications for health care. prereq: Junior or senior or grad student or professional student or instr consent
HINF 5520 - Informatics Methods for Health Care Quality, Outcomes, and Patient Safety
Credits: 2.0 [max 2.0]
Typically offered: Every Spring
Application/operation of clinical information systems, electronic health records, decision support/application in health care system. Use of clinical information systems/association with health care delivery, payment, quality, outcomes. prereq: Junior or senior or grad student or professional student or instr consent
HINF 5531 - Health Data Analytics and Data Science
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Data science methods and techniques for the extraction, preparation, and use of health data in decision making. prereq: Junior or senior or professional student or grad student or instr consent
NURS 5116 - Consumer Health Informatics
Credits: 2.0 [max 2.0]
Grading Basis: OPT No Aud
Typically offered: Every Fall
This course examines issues from the consumer?s perspective in the acquisition, understanding, or use of health information. Mobile health, telehealth, sensor technology, and internet sources for improving health are examined. The impact on consumer-provider communication and relationships as well as ethical and legal issues are explored. prereq: Grad student or instr consent
NURS 7113 - Clinical Decision Support: Theory
Credits: 2.0 [max 2.0]
Grading Basis: A-F only
Typically offered: Every Spring
Principles and concepts of knowledge management and decision making for support of clinical practice. Students design a clinical decision support intervention and examine the legal, ethical, and practical issues related to its implementation and maintenance of CDS interventions. prereq: 5115 or HINF 5430/5431 or instr consent
PUBH 6450 - Biostatistics I
Credits: 4.0 [max 4.0]
Grading Basis: A-F only
Typically offered: Every Fall & Spring
This course will cover the fundamental concepts of exploratory data analysis and statistical inference for univariate and bivariate data, including: ? study design and sampling methods, ? descriptive and graphical summaries, ? random variables and their distributions, ? interval estimation, ? hypothesis testing, ? relevant nonparametric methods, ? simple regression/correlation, and ? introduction to multiple regression. There will be a focus on analyzing data using statistical programming software and on communicating the results in short reports. Health science examples from the research literature will be used throughout the course. prereq: [College-level algebra, health sciences grad student] or instr consent
HINF 8770 - Plan B Project
Credits: 4.0 [max 4.0]
Grading Basis: No Grade
Typically offered: Every Fall, Spring & Summer
Research project. Topic arranged between student/instructor. Written report required. prereq: Advanced plan B MS student
HINF 8777 - Thesis Credits: Master's
Credits: 1.0 -18.0 [max 50.0]
Grading Basis: No Grade
Typically offered: Every Fall, Spring & Summer
(No description) prereq: Max 18 cr per semester or summer; 10 cr total required [Plan A only]