Chief, Applied Clinical Informatics Branch, Lister Hill National Center Biomedical Communic

Chief, Applied Clinical Informatics Branch, Lister Hill National Center for Biomedical Communications

The National Library of Medicine (NLM) is recruiting a Chief of the Applied Clinical Informatics Branch (ACIB) in the Lister Hill National Center for Biomedical Communications (LHNCBC). In 1968, Congress established LHNCBC to further biomedicine through innovations in computer and digital communications technology, data science research, and computer applications development.

LHNCBC focuses on advancing the use of real‑world clinical data for cutting edge biomedical research and development by judicious application of data science, computational sciences, and biomedical informatics in the diagnosis, prevention and management of diseases and to promote health. LHNCBC is comprised of an Office of the Director and two branches: the Applied Clinical Informatics Branch (ACIB) and the Scientific Computing Branch (SCB).

The ACIB has a $9M annual budget and a highly skilled staff of about 30 personnel. Activities include research and development (R&D) in biomedicine, and the development and assessment of biomedical products. The ACIB is responsible for:

• Identifying and developing innovative solutions for complex biomedical informatics challenges related to the use of various forms of clinical data (such as electronic health record, imaging, and sensor data) that scale across institutional boundaries and applications.
• Translating new research results into operational solutions that can be implemented in healthcare and research environments.
• Exploring and improving upon emerging solutions in the use of clinical data, including standards for terminology and data communications.
• Collaborating with other entities within NIH and HHS agencies to develop data science solutions to address issues of mutual interest.
• Participating in interdisciplinary, cross‑divisional collaborations and project.
• Developing and assessing biomedical products and innovative methods to lower barriers to use real‑world clinical data in biomedical research. Examples include more efficient methods to create metadata about clinical datasets to help researchers to identify relevant datasets for their work, development and assessment of computer algorithm products for automated text analysis, and new data science techniques applied to biomedical image and signal processing, artificial intelligence, and machine learning to support electronic health record systems and automated clinical decision‑making (e.g., image analysis to automatically identify malaria parasites in blood smears.)

Job Summary

The ACIB Chief is responsible for setting the overall direction and adherence to the mission to devise approaches to strengthen clinical data and improve its value to the research enterprise. The incumbent is responsible for overall program development, program evaluation, product assessment, policy formulation, and strategic direction of ACIB activities. He/she serves in a key leadership role in overseeing a highly skilled scientific and technical workforce of Federal staff and contractors.

Specifically, the duties of the ACIB Chief are as follows:

• Directing all ACIB’s operations, programs, and staff through assessment, reorganization and modernization of the technology product development activities
• Applying biomedical research and product assessment methodologies in healthcare to support improvement in clinical workflows, health information exchange, electronic health records, health data standards, and associated regulatory requirements.
• Developing assessment criteria for reviewing ACIB projects to continue, identifying new areas to pursue, and providing oversight to the expanding portfolio of new and continuing projects within ACIB
• Enhancing and strengthening the Center for Clinical Observational Investigations (CCOI), which will provide profiles and characterizations as well as product assessment about the datasets, and proxy access to support observational research and provide informatics and statistics support while lowering the barrier for adoption of research based on observational data across NIH and making it possible to…