Clinical Informatics Fellowship

Training Options

University of Maryland Medical Center

Fellowship Program

We offer a two-year fellowship program, leading to board-eligibility in the Clinical Informatics subspecialty. The program is hosted by the Department of Emergency Medicine in collaboration with faculty holding appointments in Bioinformatics, Computer Science, Diagnostic Radiology, Emergency Medicine, Information Systems, and Internal Medicine. The fellowship compensation package includes a salary, health insurance, and other benefits. Fellows in good standing may pursue moonlighting opportunities. Applicants for the two-year fellowship program must have graduated from a properly licensed medical school located in the United States or Canada, or from a school located elsewhere that is approved by the ABPM. In addition, they must have completed residency training in the United States in any ABMS-approved specialty (such as Emergency Medicine or Internal Medicine), they must be board-eligible or board-certified in this specialty, and they must be licensed to practice medicine (or eligible to be licensed) in Maryland. Applicants do not need to have formal training in Computer Science or a related discipline, but they do need to demonstrate a strong interest or aptitude in Clinical Informatics.

Baltimore VA Medical Center

Board Review Conference

An alternate pathway to board eligibility is available for physicians until 2017. The key requirement is documented practice in Clinical Informatics at least 25% full-time equivalent for 36 months over the past 5 years. For these candidates, our weekly Clinical Informatics Conference is available to review the core curriculum in Clinical Informatics. The Conference meets Tuesday mornings 9am to 1pm, and is available through teleconference for those unable to attend in-person. It is open to participants outside our fellowship program for a fee, with the opportunity to engage in board-review activities and prepare for the examination for certification in Clinical Informatics. Contact the program director for more information.

Non-Physician Training

A tuition-based non-physician tract is available for nurses, pharmacists, biologists, computer scientists, and those in related fields. This tract is also applicable for physicians who do not meet the clinical requirements of our regular fellowship tract (although this tract does not lead to board eligibility). In this tract, fellows do not receive salary or benefits. They have no clinical duties, but they fully participate in all didactic, research, and informatics activities with our clinical fellows. Applicants for this one or two year program must have completed undergraduate or graduate training in nursing, pharmacy, biology, computer science, or a related field. Applicants also need to demonstrate a strong interest or aptitude in Clinical Informatics. Contact the program director for more information.

Application

We are currently not accepting applications for our fellowship program.

Program Overview

Fellows divide their time among a number of scholarly and practical activities over a two-year period.

Practicals - Approximately half of their time (20 hours per week) is spent on practical rotations at the University of Maryland Medical Center, the Baltimore VA Medical Center, the University of Maryland Baltimore County, and other settings. In these environments, fellows will work with interdisciplinary teams to address significant clinical informatics challenges.
Research - Fellows receive close mentoring by faculty with diverse backgrounds in Clinical Informatics, Computer Science, Informatics Systems, Bioinformatics, and Medicine. This is to help each fellow to participate in an active research program in Clinical Informatics, and engage in the publication of peer-reviewed manuscripts.
Didactics - Tuesday mornings are reserved for the weekly Clinical Informatics Conference. Delivered by expert faculty, these didactic sessions cover the core curriculum, journal club, and case studies. Fellows also participate in clincial and research conferences and other educational activities within the Department of Emergency Medicine and the University of Maryland School of Medicine.
Clinical - Fellows maintain their primary board skills by working in their respective clinical areas 12 hours per week. (Fellows in the non-physician tract have no clinical duties.)

Sample schedule.

	Monday	Tuesday	Wedneday	Thursday	Friday
Morning	Research Conference	Informatics Conference	Clinical Didactics	Clinical Duties	Informatics Activities
Afternoon	Informatics Activities	Informatics Activities	Informatics Activities	Clinical Duties	Grand Rounds
Evening	Informatics Activities			Clinical Duties

Learning objectives of the training program, broken down by year.

Junior Fellows - Our first-year fellows focus on mastery of the core curriculum. They develop critical skills in information technology, process improvement, decision-support, and leadership. They refine their skills by working on a number of significant informatics challenges. They learn to do independent research. They also take on clinical responsibilities as junior attendings.
Senior Fellows - In their second year of training, our fellows have the opportunity to declare an area of specialization in clinical decision making, health information systems, personalized medicine, software engineering, telehealth, or other areas. They serve as mentors for junior fellows, residents, medical students. They also begin work on an approved senior research project.
Master Fellows - Fellows have the opportunity to complete a master’s degree in Information Systems or Computer Science at the University of Maryland. This is an optional requirement for fellows with the appropriate background, and may require a third year of training.

Research Activities

In collaboration with the University of Maryland Clinical Informatics Group, we focus on innovative applications of biomedical informatics that expand the scope of clinical medicine, have a strong theoretical basis in computer science, and are of strategic importance to the University of Maryland Medical Center. Key areas of research include personalized medicine, clinical data and image mining, clinical decision support systems, electronic health record systems, mobile and ubiquitous computing, patient safety, and emergency preparedness.

Knowledge Representation and Reasoning with Big Data - We are developing new methods for knowledge representation and reasoning that are optimized for very large clinical repositories, and which can be correlated with genomic and environmental data. Our clinical focus is on coronary artery disease, diabetes, lower respiratory disease, chronic kidney disease, rheumatoid arthritis, certain cancers, addiction, and mental illness. This work will lead to new approaches to quantify clinical risk and enable clinical decision support. It can be applied to disease prediction, critical event prediction, and treatment efficacy. We are currently working with a large clinical repository with data on more than 20 million patients from roughly 150 medical centers and 800 outpatient clinics that contains over one billion patient encounters with associated vital sign, laboratory, radiology, health screening, and pharmacy data.
Patient Safety and Quality Measures in Emergency Medicine - Patient safety is one of the nation's most important health care challenges. The widely-cited report by the Institute of Medicine estimates that as many as 44,000 to 98,000 people die in U.S. hospitals each year as the result of lapses in patient safety. This is especially important in the emergency department, where health care teams are challenged to rapidly diagnose and treat multiple patients, some of whom present with potentially life-threatening illness. Safety events can be difficult to measure, in part, because identification often depends on self-reporting, and also because we tend to discover only those events that result in significant harm to patients. We are therefore developing new computational methods to identify patient safety events that are based on semantic analysis and situational awareness, and which can be used by health care teams for computationally-enabled clinical decision support. We are also conducting research in the nature of clinical expertise in decision-making by individuals and by health care teams, to assist with the development of new approaches for computational systems.
Computer-Aided Risk Assessment for Suicide, Mental Illness, and Addiction - Suicide is a significant and preventable public health problem, and the tenth leading cause of death in the U.S. In addition, war veterans have a higher risk of suicide, due to a combination of war-related mental illness and physical health problems. While certain known risk factors exist, such as mental illness and addiction, suicidal behavior is complex and often hard to predict. We are therefore developing new computation approaches for risk assessment for suicide surveillance, mental illness, and addiction. This includes the development of a risk ontology along with a set of risk indicators that will be validated through an analysis of clinical, environmental, and genomic data.
Wearable and Mobile Computing for Clinical Decision Support at the Bedside - We are working with Google Glass, which is a wearable computer with an optical head-mounted display, video camera, speech interface, and gesture interface. It is essentially a head-mounted Android-powered cloud-enabled computer. We hypothesize that a wearable computer, with access to essential clinical data and timely alerts, can help clinicians make better decisions at the point of care. We are developing a number of hands-free decision support tools, which can be used by emergency medicicine physicians at the point of care.

Additional Information

If you are interested in applying to the fellowship or would like further information, please contact Dr. Michael Grasso.