Health Informatics Courses

To register for courses, please go to the following site: https://dhsi.jhmi.edu/Courses/

Information on tuition remission for eligible JHU employees can be found here

The ME course numbers are for students registering through the School of Medicine or School of Nursing. Students enrolled at the Bloomberg School of Public Health should register for these courses through the SPH using the course numbers assigned through the Department of Health Policy and Management. If no SPH number is listed, SPH students should register inter-divisionally using the SOM course number.

If any questions about the registration process please contact staff at JHInformatics@jhu.edu.

To access the entire School of Medicine Academic Year Calendar, please find the link here, located at the bottom of the Registrar's General Information page.

PLEASE NOTE THE DROP/ADD DATES FOR THE 2021/22 ACADEMIC YEAR

Date for withdrawal from a masters or certificate program with full refund is September 10, 2021, based on two weeks from start of classes.

Quarter 1 August 30 – October 25, 2021

Add date – September 3, 2021
Drop date – September 10, 2021

Quarter 2 October 26 – December 22, 2021

Add date – November 1, 2021
Drop date – November 8, 2021

Quarter 3 January 24 – March 18, 2022

Add date – January 28, 2022
Drop date – February 4, 2022

Quarter 4 March 28 – May 20, 2022

Add date – April 1, 2022
Drop date – April 8, 2022

Summer June 15  – August 5, 2022
Drop/add date – June 24, 2022

 

CORE COURSES

  • Introduction to Precision Medicine Data Analytics​
  • Intro to Public Health & Biomedical Informatics​
  • Applied Clinical Informatics ​
  • Health Science Informatics: Knowledge Engineering and Decision Support
  • Health Information Systems: Design to Deployment​
  • Database Querying in Health

 

First Quarter

ME 250.953.0 Introduction to Public Health and Biomedical Informatics
(SPH Registrants: 315.707.81)

Harold Lehmann, MD, PhD & John Loonsk, MD, FACMI
1st quarter, 3 credits *online

Live on Zoom 7:00 - 8:30 pm ET: (8/30 Mon: Intro; 9/13 Mon; 9/30 Thurs; 10/4 Mon; 10/13 Wed)

Introduces students to the core principles of informatics as applied to the entire range of health, from prevention, through illness, to population and public health. Focuses on frameworks within which to describe and explain health information systems. Provides to non-clinicians basic exposure to the terminology and concepts of clinical care and public health. Provides to technical novices basic exposure to IT terminology. Provides all students entry-level concepts and skills for later courses in the informatics sequences.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.955.0 Applied Clinical Informatics

Krishnaj Gourab, MD & Carrie Stein, MSN, MBA
1st quarter, 3 credits *online

Live on Zoom 7:00-8:30 pm ET: (9/1 Wed, 9/16 Thurs, and 9/30 Thurs)

This course introduces students to the field of Applied Clinical Informatics, which is focused on leveraging clinical information systems and technology to improve patient and family-centered care. Students will be exposed to a range of clinical workflows as well as patient/caregiver needs and how these may be supported by health information technology. Topics include: workflow analysis, clinical decision support (CDS), electronic health record (EHR) and patient portal best practices, health information exchange (HIE), integrated laboratory, imaging and pharmacy information, telehealth and digital health strategies, and evaluation. Each of these topics will be examined across the care continuum and within the appropriate context of clinical care transitions, patient safety and care quality, regulatory requirements, information security, organizational governance and project management.

ME 250.771.0 Introduction to Precision Medicine Data Analytics

Paul Nagy, PhD
1st quarter, 3 credits *online

Live on MS Teams: (Tuesdays 7:00 – 8:30 pm ET)

This course will introduce students to the rapidly evolving field of precision medicine and the role of big data analytics in improving patient care, clinical decision making, and population health management. Students will be provided access to the Johns Hopkins Precision Medicine Analytics Platform (PMAP) and learn how the infrastructure is built to support clinical research by integrating data from multiple research and clinical information systems such as the enterprise wide electronic medical record (EMR). The class will provide students access to a de-identified EMR curated dataset of 60k patients with a diagnosis of Asthma. The class will utilize Python and Jupyter notebooks to learn how to analyze EMR data. The PMAP cookbook of Jupyter notebook recipes and Datacamp accounts will be provided for students. After completing the course, students will have an overview of the full lifecycle of a learning health system, from understanding the data elements needed to address their problem, to figuring out the right analysis tools, and finishing with how to take their algorithm and deploy it in the clinical setting as a clinical decision support application.

This class is supported by DataCamp, the most intuitive learning platform for data science and analytics. Learn any time, anywhere and become an expert in R, Python, SQL, and more. DataCamp’s learn-by-doing methodology combines short expert videos and hands-on-the-keyboard exercises to help learners retain knowledge. DataCamp offers 350+ courses by expert instructors on topics such as importing data, data visualization, and machine learning. They’re constantly expanding their curriculum to keep up with the latest technology trends and to provide the best learning experience for all skill levels. Join over 6 million learners around the world and close your skills gap.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

Second Quarter

ME 250.952.0 Leading Change Through Health Informatics
(SPH Registrants: 315.703.81)

Richard Schreiber, MD & Peter Greene, MD
2nd quarter, 3 credits  *online

Live on Zoom - (Wednesdays, 7:00-8:30 pm ET)

Prepares learners to lead organizations implementing new IT systems. Covers the knowledge and skills that enable clinical and public health informaticians to lead and manage changes associated with implementation, adoption, and evaluation of effective use of health information systems.​ The course covers the following topics: Leadership & Governance in Health IT, Effective Teams in Health IT, Project Management, Strategic Planning for Health Information Systems, Workflow Re-eingineering, and Change Management.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.957.0 Database Querying in Health

Paul Nagy, PhD, FSIIM & Jay Syed
2nd quarter, 3 credits  *online

Live on MS Teams: (Tuesdays 7:00 – 8:30 pm ET)

This course introduces core concepts of relational databases using SQL along with special issues related to databases used in health information systems. Students will learn how to answer key questions using data originating from their Electronic Medical Record using SQL. This course builds upon the Intro to Precision Medicine course and is a prerequisite for Clinical Data Analytics with Python. Students will utilize the Precision Medicine Analytics Platform with access to de-identified medical records of 60k patients with Asthma with over 100 Million data elements including labs, medications, encounters, procedures, symptoms, and vitals.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.756.0 Informatics and the Clinical Research Lifecycle: Tools, Techniques, and Processes 

Diana Gumas, MS
2nd quarter 3 credits *online

Live on Zoom - (Mondays, 7:00 - 8:30 pm ET)

Research informatics deals with how informatics can and should support research and how research is altered by that support. The course addresses the entire life cycle of a clinical-research program: idea generation, team building, protocol development, obtaining funding, addressing ethical concerns, obtaining permissions, recruiting participants, providing the intervention and associated care, data collection, data analysis, data archiving, and results dissemination. The course addresses the related topic of translational informatics, incorporating the results of clinical and bioinformatics research into health practice. In each case, the course will highlight novel principles involved, tools available, evidence for their success, and implications for the future.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.770.0 Clinical Data Analysis with Python

Paul Nagy, PhD
2nd quarter, 3 credits *online

Live on MS Teams - (Mondays, 5:00 - 6:30 pm ET)

Pre-requisite ME 600.721 Introduction to Precision Medicine Data Analytics

Through class discussion and interactive Python data exercises, this course provides practical experience working with electronic medical record data.  The class will provide students access to the Johns Hopkins Precision Medicine Analytics Platform (PMAP) to conduct analysis on a de-identified EMR curated dataset of 60k patients with a diagnosis of Asthma.

The class will introduce Python and Jupyter notebooks to learn how to analyze EMR data.

The topics will include exploratory data analysis, data cleaning, feature extraction, model construction, and evaluation.

The class will have access to the PMAP cookbook of Juptyer notebook recipes and Datacamp accounts will be provided for students to master working with major python libraries.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

Third Quarter

ME 250.750.0 Health Information Systems: Design to Deployment
(SPH Registrants: 315.700.81)

Jasmine McNeil, MBA, MA
3rd quarter, 3 credits *online 

Live on Zoom - (Wednesdays, 5:00-6:00 pm ET)

This is a project-based course that will take you from the research stages to deployment of software design and development. You will be tasked with conducting interviews with stakeholders, applying creative decision-making techniques to prioritizing project features, creating a software deployment plan, and more. The course will draw from real-world case studies exploring software in healthcare and leave participants with an applied understanding of the software development lifecycle.  

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.777.0  Clinical Decision Analysis

Harold Lehmann, MD, PhD 
3rd quarter, 2 credits *online

Live on Zoom - (Dates / Times TBD)

This advanced elective introduces students to the basic theory and practice of decision analysis as applied to the clinical context, with an eye towards clinical decision support and the place of decision modeling in the informatics context. Topics include articulating and structuring a decision problem, creating a decision model, skill building in decision trees, and if time permits, exposure to Markov models and discrete event simulation.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.782.0 Observational Research with Observational Medical Outcomes Partnership (OMOP)

Paul Nagy, PhD & Jay Vaidya, MBBS, MPH, PhD 
3rd quarter, 3 credits *online

Live on MS Teams - (Tuesdays 5:00 – 6:30 pm ET)

Through class discussion and interactive exercises, this course provides practical experience working with the OMOP common data model (CDM) from the Observational Health Data Science and Informatics (OHDSI) community. The class will provide students with an understanding of the research challenges posed by traditional healthcare data sources and will highlight the importance of the standardized data model in addressing these challenges, specifically how the CDM can maximize the value of observational health data through facilitation of large-scale analytics. 

The class will explore the use of the CDM in facilitating the kinds of reproducible and interoperable observational studies that are becoming the industry standards in emerging healthcare research. Students will gain familiarity with tools for cohort discovery such as Athena and Atlas.

Topics will include discussion of issues such as data quality, data characterization, major clinical terminologies, research cohort definitions and how to frame an observational research question. 

The class will provide students access to the Ehden Academy, and experience using the Johns Hopkins Precision Medicine Analytics Platform (PMAP) to conduct analysis on a de-identified EMR dataset of 130k patients with over 200 Million data elements.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.778.0 Implementing Fast Healthcare Interoperability Resources (FHIR)

Paul Nagy, PhD, Teri Sippel Schmidt
3rd quarter, 3 credits *online

Live on MS Teams - (Mondays, 5:00-6:30 pm ET)

Fast Healthcare Interoperability Resources, FHIR, is transforming healthcare with an open-web services' standards approach to clinical integration. This course is a hands-on experience working on integrating digital health and clinical interoperability.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.954.0 HIT Standards and Systems Interoperability
(SPH Registrants: 315.708.81)

Anna Orlova, PhD
3rd quarter, 3 credits *online

Live on Zoom - (Dates / Times TBD)

The purpose of this course is to learn the data, information, and knowledge standards critical to the successful implementation of local, regional, and national health-related information systems. Target competencies are to identify the appropriate level of HITSP standards for an informatics problem, and select the appropriate standard within that level; create use cases and an organizational process to define an interoperability standard for a specific healthcare/regional situation; participate in a national standards-creation process.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

Fourth Quarter

ME 250.901.0 Health Sciences Informatics: Knowledge Engineering and Decision Support 
(SPH Registrants: 315.709.81)

Harold Lehmann, MD PhD 
4th quarter, 3 credits *online

Live on Zoom - (Dates / Times TBD)

This course provides a framework for understanding decision support in the workflow of the health sciences. The focus is on the types of support needed by different decision makers, and the features associated with those types of support. A variety of decision support algorithms is discussed, examining advantages and disadvantages of each, with a strong emphasis on decision analysis as the basic science of decision making. Students are expected to demonstrate facility with one algorithm in particular through the creation of a working prototype, and to articulate the evidence for efficacy and effectiveness of various types of decision support in health sciences and practice, in general.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.765.0 Natural Language Processing in the Health Sciences

Brant Chee, PhD and Masoud Rouhizadeh, PhD
4th quarter, 3 credits *online

Live on Zoom - (Dates / Times TBD)

Pre-requisites ME 600.721 Introduction to Precision Medicine Data Analytics and ME 250.770 Clinical Data Analysis with Python

There is significant demand in both academia, research and industry for informatics professionals who are well versed in natural language processing (NLP). In this course, students will be oriented to the various applications of NLP in biomedicine, healthcare and public health. The course will emphasize the importance of clearly defining what problem needs to be solved or what questions one seeks to get answered via the use of NLP. Approaches to data mining of free text from the biomedical literature, clinical narratives, and other novel data sources will be covered. There will be opportunities for students to develop NLP and machine learning algorithms. Applications of these tools in epidemiologic surveillance, clinical decision support, and other relevant use cases will be covered.

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

ME 250.--- Survival Analysis with Python

Paul Nagy, PhD & Thomas Woolf, PhD
4th quarter, 3 credits *online

Live on MS Teams - (Dates / Times TBD)

Pre-requisites ME 600.721 Introduction to Precision Medicine Data Analytics, ME 250.770 Clinical Data Analysis with Python, and ME 250.782 Observational Research with Observational Medical Outcomes Partnership (OMOP)

Course description TBD

JHU students, faculty, and staff not matriculated in our formal degree or certificate programs must seek the instructor's permission.

Summer Courses

ME 250.780.0 Information Sources & Search Techniques for Informatics Professionals

Claire Twose MLIS & Julie Nanavati, MLS,MA
Live on Zoom: TBD
1 credit *online

Live on Zoom - (Dates / Times TBD)

As a professional in the health informatics field, you will need to be able to stay current on key topics related to your profession, find evidence to solve informatics problems that cross the disciplinary boundaries of health, computing, and human factors, and contribute publishable papers to the body of informatics scholarship. This course will introduce you to the foundation and skills that you will need to engage in these research endeavors. You will learn about the biomedical sources available to you and how to efficiently and effectively search these sources. You will also learn techniques for evaluating what you find from these sources and what tools to use for storing and managing this information. The course will also address issues in the research field including how open access impacts your work as a scholar and consumer of research. Finally, you will gain the tools for establishing yourself as a professional and staying current in your field.

Only offered to students in the School of Medicine. Instructor permission required

ME 250.781.0 Data Driven Digital Health Entrepreneurship

Staff
1 credit *online

Live on Zoom - (Dates / Times TBD)

This seminar is for graduate students with an interest in digital health innovation who want to explore pathways to entrepreneurship. We are in the midst of a revolution in digital health with the widespread adoption of electronic medical records and increasing adoption of wearable fitness and health tracking devices. Maturing big data analytics, artificial intelligence and clinical decision support tools allow for rapid deployment of innovations. Although we now have the ability to derive insights from text, data and images spanning petabytes of data, learners in this course will have the opportunity to carefully define what the exact healthcare problem is that any particular solution is looking to solve. They will hear from experts in the field about features of digital health solutions that can be used to solve problems. Students will explore the advantages, disadvantages and value proposition for various digital health solutions and the associated market opportunities.

Only offered to students in the School of Medicine. Instructor permission required

Other Courses

ME 250.860.0 Student Seminar & Grand Rounds

Harold Lehmann, MD PhD & Diego Martinez, PhD
1st, 2nd, 3rd, and 4th quarter
1 credit *online
Seminar date and time: 1st and 3rd Thursday of each month from 7pm-8:30pm EST

Grand Rounds date and time:  2nd Thursday of each month from 12pm-1 pm EST

Weekly combined seminar and Grand Rounds during term. 1 credit per quarter provided students attend both seminar and Grand Rounds. Students not matriculated in our formal degree or certificate programs must seek the instructor's permission. Grand Rounds is open to all for those not seeking course credit for attending. Details on speakers and remote access to the lecture may be found here on the Grand Rounds page.

ME 250.854.0 Mentored Research

Instructor: Casey Overby Taylor, PhD and Hadi Kharrazi, MD PhD

Location: 2024 East Monument Street, Room 1-207

Time: Every Thursday, 10:00 – 11:30 a.m.

Please note attendance must be in person.

This course number applies to MS Applied, Research Masters students and both lab rotations for PhD students and to continuing research for PhD students. The informatics research is precepted by a faculty member in the Division or approved by the Training Program Director. The research may originate with the preceptor or with the student, and may be at different phases of development. In the case of the lab rotation, most of the activity is supervised by the preceptor. In the case of ongoing research, there is supervision by the Training Program Director as well as the research committee assembled by the student. Milestones are set for each quarter. Please note that a comprehensive research plan must be submitted to the program director for approval no later than September 15 of Year 2. Failure to do so will result in probation for the student.

ME 250.858.0 Health Sciences Informatics Capstone 

Edward Bunker, MS, MPH, Director

On campus students 4th quarter and summer
Online students the last year of degree completion

The purpose of the Capstone is to provide students an opportunity to:

  1. Demonstrate integration of skills and knowledge learned
  2. Develop a significant component of their portfolio
  3. Contribute to the field.

The Capstone Project will generally last 2 quarters. Students will join an active work group, supervised directly or indirectly by the capstone preceptor. They will also have a faculty advisor. The student will be responsible for spending time at the Capstone site, with specific timing to be negotiated with the capstone preceptor. Attendance may include participating in project and staff meetings, as well as front-line activity, such as working with clients.

The final report shall document attendance, how (or whether) the learning objectives were met, and shall include the report generated for the preceptor. A presentation will be made of the final report at a Capstone Presentation Seminar, with students, faculty, and capstone preceptors in attendance.

ME 250.856.0 Independent Study

Staff

Independent Study courses must be approved by the Program Director. Please note that it is important to follow the steps outlined below in order to comply with DHSI/SOM registration and grading policies. Students submit a course description to the Training Program Director, Course Instructor and Program Coordinator. The description will include the length of Independent Study (up to 2 quarters or 1 semester), the time commitment (given in hours per week or quarter), the student’s goals and what the deliverable will be. On approval by the Program Director, the Coordinator will supply you with the appropriate course number for registration. It is important that the course instructor be prepared to submit a letter grade on their departmental letterhead to the Program Coordinator.

Students not matriculated in our formal degree or certificate programs must seek the instructor’s permission.

The rules governing independent study are as follows:

  1. Gain the commitment of a Hopkins faculty member to work with you. Independent studies must be completed with a Hopkins faculty member.
  2. Work out your learning objectives.
    "By the end of the course, I will have demonstrated my ability to identify threats to validity of conclusions based on analysis of health system data." You are allowed more than one learning objective.
  3. In advance of starting, work out with the faculty member a "deliverable" that would reflect your having achieved your learning objective(s).
  4. Work out a schedule. This will include attending informatics seminars, mentor sessions, reading, and working on the deliverable.

ME 250.855.0 Health Sciences Informatics Technology Practicum

Staff

3 credits, for Certificate program students

This course applies to the Post Baccalaureate Certificate program students and is a practical experience supervised by Hopkins faculty that enables students to showcase and develop skills gained during the didactic curriculum. With a preceptor and an academic advisor, students articulate a concrete deliverable and work with the preceptor and their team to accomplish the deliverable. Example activities include, but are not limited to, literature review, systems analysis, systems evaluations, data analysis, or plans for any of these.

* Please note:
All students except those attending the School of Public Health should contact staff at JHInformatics@jhu.edu to obtain access to the online learning platform.

*All students with disabilities who require accommodations for this course should contact Kristina Nance, Disability Services Coordinator for Graduate Biomedical Education (knance2@jh.edu or 410-614-3781 ) at their earliest convenience to discuss their specific needs. Please note that accommodations are not retroactive.