Courses

Virtual Live Talks (Wednesdays, 5:30 – 7:00 PM EST)

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.  

Topics: 

• terminology and concepts of clinical care and public health 
• IT terminology 
• entry-level concepts and skills for later courses in the informatics sequences 

Virtual Live Talks (Tuesdays, 5:00 – 6:30 pm EST)

Introduces 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. Provides 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).  Allows students access to a de-identified EMR curated dataset of 60k patients with a diagnosis of Asthma. Utilizes Python and Jupyter notebooks for analyzing EMR data. The PMAP cookbook of Jupyter notebook recipes and Datacamp accounts will be provided for students.  

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. 

Topics: 

• overview of the full lifecycle of a learning health system 
• data elements needed to address problems 
• how to determine the right analysis tools 
• how to take algorithms and deploy in the clinical setting as a clinical decision support application 

Virtual Live Talks (Thursdays, 5:00 – 6:30 PM EST)

Introduces students to the ways digital health is revolutionizing the practice of medicine, increasing access to data, and diagnosing and treating diseases. For all its potential, digital health is not without risks. Students will explore the promise that digital health devices offer and investigate the legal, quality, and safety protections in place to help ensure responsible and high-quality innovation. 

Topics: 

• key digital health terminology 
• digital health trends 
• regulatory pathways for medical software devices 

Virtual Live Talks Tuesdays, 7:00 – 8:30 PM EST

Students gain 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 reproducible and interoperable observational studies that are becoming the industry standards in emerging healthcare research.  

Topics: 

• data quality 

• data characterization 

• major clinical terminologies 

• research cohort definitions 

• how to frame an observational research question 

• tools for cohort discovery such as Athena and Atlas 

Virtual Live Talks (Wednesdays, 7:00 – 8:30 PM EST)

Students learn how 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.​  

Topics: 

• leadership and governance in Health IT 
• effective teams in Health IT 
• project management 
• strategic planning for health information systems
• workflow re-engineering 
• change management 

Virtual Live Talks (Tuesdays, 5:00 – 6:30 PM EST)

This course introduces core concepts of relational databases using SQL. Students will utilize the Precision Medicine Analytics Platform (PMAP) with access to de-identified medical records of 60,000 patients with asthma with over 100 million data elements including labs, medications, encounters, procedures, symptoms, and vitals. 

Topics: 

• answering key questions on data originating from electronic medical records using SQL 
• special issues related to databases used in health information systems  

Virtual Live Talks Mondays, 5:00 - 6:30 pm EST

Pre-requisite ME 250.771 Introduction to Precision Medicine 

Students gain practical experience working with electronic medical record data through class discussion and interactive Python data exercises. Using the Johns Hopkins Precision Medicine Analytics Platform (PMAP), students will conduct analyses on a de-identified electronic medical record dataset of 60k patients with a diagnosis of asthma. The class will introduce Python and Jupyter notebooks to learn how to analyze electronic medical record data. 

Topics: 

• exploratory data analysis
• data cleaning 
• feature extraction 
• model construction and evaluation  

Virtual Live Talks Tuesdays, 12:00 - 1:30 pm

Students will examine the adoption of digital health innovation through the lens of health care providers and entrepreneurs and will be matched with C-suite executives for mentorship. This course begins by looking at how problems are identified and solutions are sourced by the spectrum of health care provider types. Simultaneously, each student will look at this process from the entrepreneur’s perspective, better understanding how solutions should position themselves in the market, target key stakeholders, and successfully navigate the adoption and implementation process. Mentors will be available for guidance throughout the class, and students will be expected to adopt the mentors’ companies as an avatar through which they will examine this process.   

Topics: 

• procurement process, integration across the buyer’s organization, identification of pitfalls 
• breadth of the health care provider landscape
• key elements of a pitch needed to successfully engage a health care provider  
• how health care providers can productively work with early-stage innovations 
• effective strategies and common mistakes that past digital health solutions have made 

Virtual Live Talks Wednesdays, 5:00 - 6:30 pm EST

This project-oriented class equips clinical investigators with the team, essential knowledge, and skills to effectively leverage the observational medical outcomes partnership (OMOP) common data model (CDM) to engage and conduct network studies for their research endeavors. Students will form investigation-based teams. By the end of the program, participants will have a solid foundation in these crucial aspects, enabling them to conduct robust network studies using the OHDSI community.   

Topics: 

• use case selection
• study design 
• IRB considerations
• protocol development 
• preliminary phenotypes 

All students must seek the instructor’s permission. 

Virtual Live Talks TBD

2nd quarter, 3 quarter credits *online (1.5 semester credits)

Virtual Live Talks (TBD)
Pre-requisites: ME 250.770 Clinical Data Analysis with Python; ME 250.953 Introduction to Biomedical Informatics 

This course is designed to bridge the gap between engineering and medicine by exploring the application of generative artificial intelligence (AI) technologies in healthcare settings. Through a combination of lectures, case studies, and hands-on projects, students will gain a comprehensive understanding of how generative AI can be leveraged to solve complex health-related problems, while also navigating the ethical, legal, and social implications of these technologies. The course will cover a range of topics, including but not limited to, the fundamentals of generative AI, its current and potential applications in healthcare, data privacy and security, ethical considerations in AI deployment, regulatory frameworks, and the impact of AI on patient care and healthcare systems.

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

Virtual Live Talks Tuesdays, 5:00 -6:30 PM EST

Introduces students to the field of Applied Clinical Informatics with focus on leveraging clinical information systems and technology to improve patient- and family-centered care. Exposes students to a range of clinical workflows as well as patient/caregiver needs and how these may be supported by health information technology. Allows students to examine each topic 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. 

 Topics:  

• 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 

Virtual Live Talks Wednesdays, 5:30 - 7:00 PM EST

* formerly Health Information Systems: Design to Deployment 

This course is the first of the Design for Healthcare Series (it is strongly recommended that Prototyping for Healthcare Design is taken just after this course). Design discovery for healthcare applies design thinking techniques to the beginning stages of digital health app ideation.  

Topics: 

• methods for mapping stakeholders
• user interviews to gain insights about user needs for a digital health app 
• design research methods 
• creating a design research brief 
• design software tools (will not be required to code) 

Virtual Live Talks Wednesdays, 7:00 - 9:00 PM EST

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:

• articulating and structuring a decision problem
• creating a decision model
• skill building in decision trees
• exposure to Markov models and discrete event simulation (if time permits) 

Virtual Live Talks (Mondays, 5:00 – 6:30 pm ET)

Students will learn how Fast Healthcare Interoperability Resources (FHIR) are transforming healthcare with an open-web services’ standards approach to clinical integration.  

Topics: 

• integrating digital health and clinical interoperability 

In Person

NOTE: This is a two-part course. Students must also register for Quarter 4 ME 250.963 Health Information Technology Startup Generator / Accelerator 

Hexcite (Excited for Healthcare) is a medical software start-up generator program for entrepreneurs hosted by the Johns Hopkins Medicine Technology Innovation Center in collaboration with Johns Hopkins Technology Ventures. Weekly, expert-led sessions help teams navigate the first steps of business and technical design using the Lean Start-up methodology which focuses on growing a business with maximum acceleration.  

Topics: 

• customer discovery (interviewing to test assumptions) 

• design thinking process to prioritize technology requirements 

• building a pitch that includes market research and storytelling components   

All students must seek the instructor’s permission. 

Virtual Live Talks TBD

Pre-requisite: ME 250.770 Clinical Data Analysis with Python 

Students will learn how to leverage deep learning models for classification and segmentation of clinical medical imaging data.  

Topics: 

• hands-on experience working with medical images 

• how to integrate AI models in a clinical setting  

• Digital Imaging Communication in Medicine (DICOM) interoperability standard  

Virtual Live Talks Thursdays, 12:00 pm - 1:30 pm ET

This course will teach students how to conduct data characterization, time at risk analysis, and causal inference testing on EHR based observational research data.

Goals:

This course will be a hands-on course leveraging the open-source R based Health Analytics Data Evidence Suite.

Students will get access to de-identified real world EHR data to perform and create computational patient population cohorts and conduct statistical analysis.

Prerequisite: ME.250.782 Observational Health Research Methods on Medical Records (OMOP)

Virtual Live Talks (Wednesdays 7:00-8:30 pm ET)

Students will gain understanding of decision support in the health sciences workflow. The focus is on the types of support needed by different decision makers, and the features associated with those types of support.  

Topics: 

• various decision support algorithms, examining advantages and disadvantages of each 

• strong emphasis on decision analysis as the basic science of decision making 

• facility with one algorithm in particular through the creation of a working prototype 

• evidence for efficacy and effectiveness of various types of decision support in health sciences and practice 

Virtual Live Talks (Mondays, 7:00 – 8:30 pm ET)

Pre-requisites ME 250.771 Introduction to Precision Medicine Data Analytics and ME 250.770 Clinical Data Analysis with Python 

Students will be oriented to the various applications of natural language processing (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.  

Topics: 

• approaches to data mining of free text from the biomedical literature, clinical narratives, and other novel data sources  

• NLP and machine learning algorithms 

• applications of these tools in epidemiologic surveillance, clinical decision support, and other relevant use cases  

All students must seek the instructor’s permission. 

Virtual Live Talks (Wednesdays, 5:30 - 7:00 pm ET)

Pre-requisite ME 250.750 Design Discovery for Health Care 

This course is the second part of the Design for Healthcare series (to directly follow Design Discovery for Healthcare). Participants will build from prior design research and will learn to recognize common patterns and language to promote a seamless user experience and prepare a design plan for hand off. 

 Topics:

• wireframing and prototyping a software application with a team 

• prototype testing with users 

• using feedback for iterative improvements  

• design software tools (will not be required to code) 

Virtual Live Talks (Mondays, 5:00 - 6:30 pm ET)

Pre-requisite: Implementation of Fast Healthcare Interoperable Resources (FHIR) (ME.250.778 Q3)    

Students will learn about informatics and data science driving patient care and how the implementation of Clinical Decision Support (CDS) applications integrate with the practice of medicine. 
   
Topics:  

• current state of CDS implementation in electronic health records 
• advantages of implementing interoperable CDS algorithms in EHRs
• basic interoperability of CDS algorithms using CDShooks and HL7 FHIR
• basic HL7 Clinical Query Language (CQL) queries for HER data to support CDS algorithms 

In Person

NOTE: This is a two-part course. Students must also register for Quarter 3 ME 250.963 Health Information Technology Startup Generator / Accelerator. 

Hexcite (Excited for Healthcare) is a medical software start-up generator program for entrepreneurs hosted by the Johns Hopkins Medicine Technology Innovation Center in collaboration with Johns Hopkins Technology Ventures. Weekly, expert-led sessions help teams navigate the first steps of business and technical design. 

Topics: 

• Lean Start-up methodology which focuses on growing a business with maximum acceleration 
• customer discovery (interviewing to test assumptions) 
• design thinking process to prioritize technology requirements 
• pitch building that includes market research and storytelling components   

All students must seek the instructor’s permission. 

Virtual Live Talks (Wednesdays, 10:00 - 11:00 am ET)

Introduces students to becoming health informatics professionals and the need to stay current on key topics, how to 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. Students will gain the necessary foundation and skills to engage in these research endeavors.  

Topics: 

• available biomedical sources and how to search them efficiently and effectively
• techniques for evaluating what you find from these sources 
• what tools to use for storing and managing this information 
• issues in the research field including how open access impacts your work as a scholar and consumer of research 
• 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. 

Virtual Live Talks (Thursdays, 5:00 – 6:00 pm ET)

Introduces students to the ways digital health is revolutionizing the practice of medicine, increasing access to data, and diagnosing and treating diseases. For all its potential, digital health is not without risks. Students will explore the promise that digital health devices offer and investigate the legal, quality, and safety protections in place to help ensure responsible and high-quality innovation. This course will also introduce students to the rapidly evolving field of digital health regulation and the role of the FDA, FTC, OCR, and other legal and regulatory bodies in this space. 

Topics: 

• key terminology relevant to the fields of digital health innovation and medical device regulation 
• relationships between regulators, technology developers, healthcare providers, and patients 
• requirements for digital health technology to be considered Software as a Medical Device (SaMD) by the FDA 
• various regulatory pathways for SaMD and the main considerations 

Virtual Live Talks Student Seminar (1st & 3rd Thursdays, 7:00 – 8:30 pm EST) Grand Rounds (2nd Wednesday of each month, 12:00 – 1:00 pm EST)

Weekly combined seminar and Grand Rounds during term. Only matriculated students in a BIDS formal degree or certificate program can take this course. Details on the Grand Rounds speakers and remote access to the lecture may be found here on the  Grand Rounds page. 

In Person (Every Thursday, 10:00 – 11:30 am ET)

Location: 2024 East Monument Street, Room 1-207

Please note: In-person attendance required. 

This course 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 guided by a faculty member in BIDS or approved by the program director. The research may originate with the preceptor or with the student and may be at different phases of development. In lab rotation, most of the activity is supervised by the preceptor. In ongoing research, there is supervision by the 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. 

Students gain the opportunity to demonstrate integration of skills and knowledge, develop a significant component of their portfolio, and 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. A presentation will be made of the final report at a Capstone Presentation Seminar, with students, faculty, and capstone preceptors in attendance. 

Independent Study courses must be approved by the Program Director and students must 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 which includes 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 the appropriate course number for registration. 

Students must: 

• gain the commitment of a Hopkins faculty member to work with
• define learning objectives 
• determine with the faculty member a “deliverable” that would reflect having achieved learning objective(s) 
• develop a schedule which includes attending informatics seminars, mentor sessions, reading, and working on the deliverable 

This course applies to the Post Baccalaureate Certificate program students and is a practical experience supervised by Johns Hopkins faculty that enables students to showcase and develop skills gained during the didactic curriculum.  

Students work with a preceptor and an academic advisor to 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.