Request for Implementation Authorization

Master of Science in Biomedical Informatics, CIP: 26.1103

The proposed program is designed to meet the rapidly growing need for professionals with preparation that integrates technological expertise in the information sciences / computer science, the biosciences and mathematical statistics with an understanding and ability to work in the clinical environment of the healthcare professions.

The core program will feature a two semester sequence of courses specifically designed to bring together clinicians and researchers in teams, applying new developments in informatics theory to clinical practice. A common theme among the constituencies surveyed to understand the needs to be served by this program was the need for integrating theory and practice in biomedical informatics. The MS Program in Biomedical Informatics at ASU will address this theme with the core curriculum, and with two concentrations: one clinical that addresses the need for application, the other analytic that addresses the need for developmental understanding. This objective of integrating the clinical and analytic tracks will be challenging, but is strongly supported by our collaborators including: the University of Arizona College of Medicine, Phoenix Program; Mayo Clinic; Barrow Neurological Institute; and Banner Health. Though challenging, this approach will make the MS Program in Biomedical Informatics at ASU distinctive, if not unique, among biomedical informatics programs in the United States.

Building on the core program students will have the option of following either of two concentrations:

• 
  a clinical concentration for immediate professional practice applying biomedical informatics in the healthcare professions (e.g., hospital information systems, nursing informatics, public health informatics, medical imaging, laboratory instrumentation systems). Graduates with this concentration will typically enter or continue professional careers in clinical practice.
  
• 
  an analytical concentration preparatory to a research career in areas such as biostatistical analysis, data mining in health records, medical imaging, genomic analysis, and epidemiological informatics. Graduates with this concentration will typically come members of research groups in the rapidly expanding biomedical research and development industry, or continue on for the Ph.D.
  

1. 
   DEGREE(S), DEPARTMENT AND COLLEGE AND CIP CODE
   

Department of Biomedical Informatics

/ School of Computing and Informatics

Ira A. Fulton School of Engineering

CIP code: 26.1103 (Bioinformatics)

2. 
   PURPOSE AND NATURE OF PROGRAM
   

3. 
   PROGRAM REQUIREMENTS -- List the program requirements, including minimum number of credit hours, required courses, and any special requirements, including theses, internships, etc.
   

1. 
   Admission
   

• 
  Core concepts of computer programming, data structures and algorithms (similar to CSE 200 at ASU),
  
• 
  Fundamentals of genetics (equivalent to BIO 187 + 188 at ASU),
  
• 
  Introductory probability and statistics (equivalent to STP 226, 231, 326 or 420),
  
• 
  Mathematical foundation for information scientists (similar to SCI 200, pending approval as part of proposed undergraduate SCI Certificate), or mathematical methods for geneticists (equivalent to MAT 351 at ASU)
  
• 
  Concepts of patient care processes, as demonstrated by coursework or practice in one of the healthcare professions
  

Students may be admitted conditionally with deficiencies in two of the background areas above, and will automatically convert to regular admission when the background courses are completed with grades of B (3.0) or better.

2. 
   Program
   

Minimum credit hours: 30

• 
  BMI 510 (new) Introduction to Bioinformatics (3 credits)
  
• 
  BMI 520 (new) Theory of Informatics in Clinical Practice I (3 credits)
  
• 
  BMI 521 (new) Theory of Informatics in Clinical Practice II (3 credits)
  
• 
  SCI 410 (new – proposed course as part of SCI Certificate)
  

• 
  HSM 561 Biostatistics I (3 credits)
  
• 
  BMI 585 (new) Bioethics and professional seminar (3 credits)
  
  • 
    1 credit in each of three semesters)
    

• 
  HSM 571 Biostatistics II (3 credits)
  
• 
  Electives (3 credits)
  

• 
  BMI 592 Research (3 credits)
  
• 
  BMI 599 Thesis (3 credits)
  

• 
  BMI 540 (new) Health Information Systems (3 credits)
  
• 
  BMI 541 (new) Health Info. Sys. Management (3 credits)
  
• 
  BMI/NUR 538 Evidence Based Practice (3 credits)
  

• 
  BMI 593 Applied Project (3 credits)
  

1. 
   Biology
   
2. 
   Bioengineering
   
3. 
   Computational Biology
   
4. 
   Computer Science
   
5. 
   Health Sector Management
   
6. 
   Industrial Engineering
   
7. 
   Nursing
   
8. 
   Quantitative Business Analysis
   
9. 
   Statistics and Probability
   

Course # and Title
	Clinical Elective	Analytical Elective
Biology
BIO 508 Scientific Data Presentation		X
BIO 545 Populations: Evolutionary Genetics		X
BIO 547 Techniques in Evolutionary Genetics		X
BIO 552 Developmental Genetics		X
BIO 591 Controversy in Biotechnology, Health, and Developing Countries	X	X
BIO 591 Time Series Analysis		X
BIO 594 Statistical Methods in Molecular Evolutionary Genetics		X
BIO 598 Visualization and Computation		X
Biomedical Engineering
BME 566 Medical Imaging Instrumentation		X
BME 568 Medical Imaging
BME 598 Analytical and Diagnostic Instrumentation in Bioengineering		X
BME 598 Intro to Molecular, Cellular and Tissue Engineering
BME 598 Modeling and Simulation of Physiological Systems		X
Computational Biology
CBS 520 Modeling and Computational Biology		X
CBS 521 Problem Solving in Computational Biosciences		X
CBS 530 Introduction to Structural and Molecular Biology
CBS 598 Applications of AI to Molecular Biology		X
CBS 598 Database Management
CBS 598 Databases: Biological Applications		X
CBS 598 Genomics: Sequencing and Mapping		X
CBS 598 Mathematical Biology I
CBS 598 Mathematical Methods for Genetic Analysis
CBS 598 Scientific Computing-Bioinformatics		X
Computer Information Systems
CIS 502 Management Information and Decision Support Systems		X
CIS 512 Intelligent Decision Systems and Knowledge Management		X
CIS 520 Systems Design and Evaluation	X
CIS 535 Distributed and Mixed-Media Information Systems	X
Computer Science Courses
CSE 591 Computational Molecular Biology		X
CSE 591 Data Mining		X
CSE 591 Data Warehousing and Data Mining		X
CSE 591 Genomics: Sequencing and Mapping		X
CSE 591 Random Approximate Algorithms		X
CSE 591 Semantic Web Mining		X
CSE 598 Introduction to Data Mining		X
Health Sector Management
HSM 505 Managerial and Population Epidemiology		X
HSM 522 Health Sector Information and Knowledge Management	X	X
HSM 540 Health Care Outcomes
HSM 560 Health Services Administration and Policy	X
HSM 572 Bioinformatics and Microarray	X
HSM 566 Basic Principles of Epidemiology	X
Industrial Engineering
IEE 511 Analysis of Decision Process		X
IEE 572 Design of Engineering Experiments		X
IEE 578 Regression Analysis		X
IEE 598 Data Mining: Analysis of Massive Data Sets		X
Mathematics Courses
MAT 598 Math Biology II		X
MAT 598 Mathematical Methods for Genetic Analysis		X
MAT 598 Population Biology		X
MAT 598 Self-Organization in Biological Systems		X
Quantitative Business Analysis
QBA 525 Applied Regression Models		X
QBA 530 Experimental Design		X
Statistics and Probability
STP 526 Theory of Statistical Linear Models		X
STP 530 Applied Regression Analysis		X
STP 531 Applied Analysis of Variance		X

4. 
   NEW COURSES NEEDED -- List any new courses which must be added to initiate the program; include a catalog description for each of these courses.
   

BMI 510 Introduction to Biomedical Informatics (3 credits)

Fundamentals of informatics applied to health care, including computer-based medical records, knowledge-based systems, telehealth, decision support, human-computer interfaces, systems integration, and digital libraries.

BMI 520 Theory of Informatics in Clinical Practice I (3 credits)

A survey course exploring transformational leadership skills, ethics and applied informatics in a merged culture of healthcare and computer science. Prerequisite: BMI 510

BMI 521 Theory of Informatics in Clinical Practice II (3 credits)

In-depth examination and application of transformational leadership skills, ethics and applied informatics in a merged healthcare and computer science culture. Prerequisite: BMI 520

BMI 530 Introduction to Biomedical Imaging Informatics (3 credits) Physical principles, image reconstruction techniques, and clinical applications of the most commonly used medical imaging modalities. Prerequisite: BMI 510

BMI 540 Health Information Systems (3 credits)

Clinical database concepts. Full-text databases, distributed DB services. Architectures of clinical information systems. Reliability and availability, security. Integration of multimodal information.

BMI 541 Health Information Systems Management (3 credits)

Implementation, management, and evaluation of clinical information systems. Project management, human and financial resource allocation, organizational change, group processes. Evaluation of clinical information systems impact. Prerequisite: BMI 520, BMI 540.

BMI 585 Bioethics / Prof. Seminar (1 unit, may be repeated up to 6 credit hours) Graduate level topics in Biomedical Informatics research and ethics presented by distinguished lecturers working in the field.

5. 
   REQUIREMENTS FOR ACCREDITATION -- Describe the requirements for accreditation if the program will seek to become accredited. Assess the eligibility of the proposed program for accreditation.
   

No professional accreditation is available or sought.

2. 
   STUDENT LEARNING OUTCOMES AND ASSESSMENT
   

1. 
   What are the intended student outcomes, describing what students should know, understand, and/or be able to do at the conclusion of this program of study?
   

An initial list of skills was developed based upon interviews with healthcare industry leaders who will be hiring graduates from this program and evaluation of similar programs at universities to which graduates of this program would apply for further graduate work leading to a research career. These skills were grouped into categories and a number of student outcomes have been identified. The intended student outcomes include developing, technical and scientific skills, and have been grouped into content areas:

Ability to lead and organize projects and teams

Ability to ”integrate and bridge” within cross disciplinary project teams --- to recognize cultural differences between the disciplines involved and help people from these disciplines to work together effectively

Ability to communicate across disciplines with the ability to use terminology / vocabulary that spans computer science, biology, medicine, clinical healthcare, and statistical analysis)

Project Management capability, from initial definition through the project life

Ability to effectively communicate and present plans, research results and other relevant information to diverse groups

Understanding of patient-centric thinking / safety and service

Ability to design and implement research

Ability to understand and comply with privacy and security policy and practice

Ability to approach problems conceptually, using appropriate models and abstractions

Ability to recognize practical considerations and opportunities available in the application domain that will lead to effective solutions.

Ability to perform workflow analysis in project design

Demonstrate systems scale approaches to problem solving using interface definition and hierarchical and concurrent module decomposition.

Computer Science Skills

Introductory level ability in software design and project management

Understanding of the core concepts of programming, data structures and algorithms

Ability to apply the basic concepts of computability and intractability

Fundamental understanding of declarative programming paradigms

Demonstrated understanding of cyber-infrastructure and architecture of computing (hardware / software) systems

Ability to understand and apply modeling and visualization tools and techniques

Health Care

Understanding of patient care processes

Understanding of healthcare policy, business practices and law

Understanding of how data and electronic medical records are collected, analyzed and used

Understanding of the definitions and conceptual framework of “evidence based” and “customized “ medicine

Understanding of the concepts of individualized/customized health care

Working understanding of the fundamentals of molecular biology

Working understanding of the fundamentals of functional and/or comparative genomics

Probability/Statistics

Ability to perform trials, experiments; proper analysis

Ability to apply statistics to sampling and data mining
These outcomes have been structured into an integrated common BMI MA degree core curriculum, with additional emphasis on analytic and clinical concentrations.

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