Division of Health Sciences Informatics Core and Domain Courses

CAHIIM Degree Accreditation Pending

The core curriculum provides training in the fundamental principles of informatics, with examples from across the healthcare continuum. Please note the special registration procedure for online courses at the bottom of the page. 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 www.jhsph.edu/dept/hpm/certificates/informatics/curriculum.html. If no SPH number is listed, SPH students should register inter-divisionally using the SOM course number.

PLEASE NOTE THE ADD/DROP DATES FOR THE 2019/20 ACADEMIC YEAR

Date for withdrawal from a masters or certificate program with full refund is September 13, 2019, based on two weeks from start of classes.

Quarter 1 September 3 – October 25, 2019
Drop date – September 13, 2019
Quarter 2 October 28 – December 20, 2019
Drop date – November 10, 2019
Quarter 3 January 21 – March 13, 2020
Drop date – January 31, 2020
Quarter 4 March 23 – May 15, 2020
Drop date – April 3, 2020
Summer June 15th – August 14th, 2020
Drop date – June 26th, 2020

 

*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.

First Quarter

ME 600.903 Introduction to Public Health and Biomedical Informatics
(SPH Registrants: 315.707.81)

Harold Lehmann, MD, PhD
1st quarter, 3 credits *online

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.

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

ME 600.905 Applied Clinical Informatics

Michael Boland MD PhD and Krishnaj Gourab, MD
1st quarter, 3 credits *online

This course introduces students to the field of Applied Clinical Informatics, which is focused on improving patient care through enhanced use of clinical information systems. Students will be exposed to a wide range of clinical workflows and how health information technology and systems supports them. Topics in this course include: Bar Coding, Clinical Decision Support, Computerized Provider Order Entry, Electronic Health Records, Electronic Prescribing, Health Information Exchange, Master Patient Index, and Telehealth/Telemedicine. Each of these will be examined within the appropriate context of clinical care transitions, patient safety and care quality, inpatient/ambulatory care settings, information security and deployment of HIT.

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

ME 600.716 Informatics and the Clinical Research Lifecycle: Tools, Techniques, and Processes

This course is required for MS Research and is an Elective for MS Applied.  

Casey Overby-Taylor, PhD and Diana Gumas
1st quarter, 3 credits *on campus
Day: Tuesday/Thursday
Time: 1:00 pm.- 2:30 pm
Location: DHSI Conference Room, 2024 E. Monument Street,  Room 1-207

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.

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

ME 600.721 Introduction to Precision Medicine Data Analytics

Paul Nagy, PhD & Ashwini Davison, MD
1st quarter, 3 credits *online

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 Juptyer 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.

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

Second Quarter

ME 600.902 Leading Change Through Health Informatics
(SPH Registrants: 315.703.81)

Ashwini Davison, MD and Peter Greene, MD
2nd quarter, 3 credits  *online

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.

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

PH 309.631.81 Population Health Informatics
(Offered by the School of Public Health)

Hadi Kharrazi, MD PhD and Jonathan Weiner PhD
2nd quarter, 3 credits  *online

Introduces students to concepts, methods, and issues related to the application of health information technology (HIT) to population health. Emphasizes the population health potential of comprehensive electronic health records (EHRs), personal health records (PHRs), mobile health and telemedicine devices; and consumer focused internet-based tools. Covers the uses of HIT to define and identify populations and sub-populations of interest, describe the health status and needs of populations, improve the health of populations, and evaluate services provided to populations. Emphasizes the use of HIT within both local, regional and federal public health agencies and population-based private health care organizations such as integrated delivery systems and health insurance plans. Lessons are mainly US oriented but are also applicable to other high and middle income countries.

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

ME 600.907 Database Querying in Health

Sam Meiselman, MS
2nd quarter, 3 credits  *online

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 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.

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

Third Quarter

ME 600.900 Health Information Systems: Design to Deployment
(SPH Registrants: 315.700.81)

Robert Miller, MD, Gorkem Sevinc
3rd quarter, 3 credits *online 

A review of health information systems, such as patient record, patient monitoring, imaging, public health, educational, bioinformatics and scholarly systems. This offering teaches the core architectures and technologies of these core systems, focusing on commonalities and differences and design.  .

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

ME 600.904 HIT Standards and Systems Interoperability
(SPH Registrants: 315.708.81)

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

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.

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

ME 600.720 Clinical Data Analysis with Python

Paul Nagy, PhD
3rd quarter, 3 credits *on campus or remote elective

Day: Monday
Time: 1:00 pm- 4:00 pm
Location: PCTB (Pre-Clinical Teaching Building) 115 Style Lab
Pre-requisite ME 600.907 Database Querying in Health

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 dataset of 60k patients with over 100 Million data elements.  The class will work with Jupyter notebooks to learn how to prepare EMR data and construct models from encounter, symptoms, lab, procedure, vitals, & medication data.   The topics will include exploratory data analysis, data cleaning, feature extraction, model construction, and evaluation.  Working knowledge of SQL is expected and Python encouraged.  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 Pandas, Matplotlib, Numpy, and Sci-kit. 

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

ME 600.914 Secondary Uses of Electronic Health Record Data
(SPH Registrants: 550.714.81)

Brandyn Lau and Diego Martinez, MBA PhD
3rd quarter, 3 credits *online

Introduces students to concepts, methods, and issues related to the application of analytics to Electronic Health Record (EHR) data. Covers the use of EHR data to define and identify populations and sub-populations of patients, evaluate common metrics in health care, and improve patient safety and care quality. Emphasizes the use of EHR data in hospital settings.

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

Fourth Quarter

ME 600.901 Health Sciences Informatics: Knowledge Engineering and Decision Support 
(SPH Registrants: 315.709.81)

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

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.

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

ME 600.715 Natural Language Processing in the Health Sciences

Brant Chee, PhD and Taxiarchis Botsis, PhD
4th quarter, 3 credits *on campus or remote elective
Day: Monday
Time: 9:00 am-12:00 pm
Location: 2024 E. Monument Street,  Room 1-207

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.

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

ME 600.714 Data Visualization

Brandyn Lau
4th quarter, 3 credits *on campus or remote elective
Day: Tuesday/Thursday
Time: 1:00 pm-2:30 pm
Location: 2024 E. Monument Street,  Room 1-207

Rapid comprehension of health information is an increasingly important goal and can be achieved with effective visualization techniques. Information visualization is an extremely powerful tool for patients, clinicians and researchers to understand both simple and complex concepts quickly to enable decision making. This course will explore the science and art of information visualization, demonstrate software options to visualize information, provide use cases of visualization to guide decision making, and enable students to develop and refine skills in information visualization.

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

Summer

ME 600.717 Authoring Effective Teaching Cases in the Simulation EMR Environment

Ashwini Davison, MD
June 15th-August 14th 2020
Live on Zoom: Thursdays 7:00 – 8:00 p.m. ET
2 credits *online

 

This course covers the complexities of designing and deploying high fidelity patient cases in the electronic medical record (EMR) environment. Students will be introduced to the back-end architecture of the training environment as well as key terminology associated with the patient build process. Opportunities will be provided to navigate the simulation EMR from the perspective of a variety of different clinical and operational end-users. Students will gain experience populating standard template (cookbooks) with essential data elements based on pre-existing paper based clinical vignettes.

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

ME 600.722 Unstructured Data Mining to Address Novel Infectious Diseases

Paul Nagy, PhD & Ashwini Davison, MD
June 15th-August 14th 2020
2 credits *online

This research elective is intended for graduate students with a clinical background who have an interest in the applications of natural language processing (NLP) techniques in addressing novel infectious disease outbreaks. During the era of big data in healthcare, there has been no greater catalyst for the importance of health informatics than the COVID-19 global pandemic. Students who are eager to derive insights from unstructured clinical data that can be used to better inform clinical decision making, contact tracing, containment and mitigation efforts will benefit from this opportunity. Faculty with expertise in pulmonology, infectious disease, radiological imaging, and clinical informatics will introduce students to the newly established COVID-19 Clinical Registry. Students will have an opportunity to perform chart abstraction and unstructured data annotation. They will work alongside clinical researchers, data analysts, and text mining experts to gain experience in the real-world application of creating supervised training sets for machine learning algorithms.

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

ME 600.723 Information Sources & Search Techniques for Informatics Professionals

Claire Twose MLIS
June 15th-August 14th 2020
Live on Zoom: Wednesdays 7:30 – 8:30 p.m. ET
1 credit *online

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 600.724 Data Driven Digital Health Entrepreneurship

Mark Komisky, JD
June 15th-August 14th 2020
1 credit *online

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.

live sessions on Tuesday nights, 7-8PM EDT

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

For Medical Students, Residents

ME 600.601 Topics in Interdisciplinary Medicine: Clinical Informatics

Ashwini Davison, MD

This four-day course is offered in April of Year One for medical students. The course introduces students to clinical informatics, an interdisciplinary field that explores effective uses of clinical data, information and knowledge in order to improve health. During the course, students will hear both from Hopkins faculty who conduct research in the field of informatics as well as those with applied experiences in designing clinical decision support tools or deploying telemedicine. Students will learn from a combination of online engaging lectures (that can be viewed remotely), in-person lectures, hands-on time in the Epic playground, demonstrations of MyChart from a patient perspective, a live telemedicine demo, and small group activities. In this course, students will gain insight into the physician’s evolving roles and responsibilities during this transformative time in healthcare.

ME 600.699 Health Sciences Informatics Elective

Harold Lehmann, MD, PhD

Timing dependent on mutual schedules (1 to 2 month's duration)

This elective provides students with basic informatics research skills and knowledge, focused on health sciences applications, data, information, and knowledge, decision support, evaluation. Students participate in program meetings and seminars, conduct self-study, spend time at information technology settings (permission pending), and are responsible for a project report at the end of the elective. The report may range from a literature review, to a system specification, to working code, or other deliverable, depending on the interests and skills of the student.

Requires faculty permission. Inquire at least 3 months before desired start date.

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

Other Required Courses for Degree Candidates

ME 600.810 Student Seminar & Grand Rounds

1st, 2nd, 3rd, and 4th quarter
Twice monthly (dates TBD)
Day: (TBD)
Time: (TBD) 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 600.804 Mentored Research

Staff

3 credits

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 600.808 Health Sciences Informatics Capstone 

Ashwini Davison, MD
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.

Other Courses

ME 600.806 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.

* Please note:
All students except those attending the School of Public Health should contact Stacey Szczypinski
to obtain access to the online learning platform. sszczyp1@jhmi.edu, 443-287-6083