Structure and Funding of Clinical Informatics Fellowships: A National Survey of Program Directors.

BACKGROUND: In 2011, the American Board of Medical Specialties established clinical informatics (CI) as a subspecialty in medicine, jointly administered by the American Board of Pathology and the American Board of Preventive Medicine. Subsequently, many institutions created CI fellowship training programs to meet the growing need for informaticists. Although many programs share similar features, there is considerable variation in program funding and administrative structures. OBJECTIVES: The aim of our study was to characterize CI fellowship program features, including governance structures, funding sources, and expenses. METHODS: We created a cross-sectional online REDCap survey with 44 items requesting information on program administration, fellows, administrative support, funding sources, and expenses. We surveyed program directors of programs accredited by the Accreditation Council for Graduate Medical Education between 2014 and 2021. RESULTS: We invited 54 program directors, of which 41 (76%) completed the survey. The average administrative support received was $27,732/year. Most programs (85.4%) were accredited to have two or more fellows per year. Programs were administratively housed under six departments: Internal Medicine (17; 41.5%), Pediatrics (7; 17.1%), Pathology (6; 14.6%), Family Medicine (6; 14.6%), Emergency Medicine (4; 9.8%), and Anesthesiology (1; 2.4%). Funding sources for CI fellowship program directors included: hospital or health systems (28.3%), clinical departments (28.3%), graduate medical education office (13.2%), biomedical informatics department (9.4%), hospital information technology (9.4%), research and grants (7.5%), and other sources (3.8%) that included philanthropy and external entities. CONCLUSION: CI fellowships have been established in leading academic and community health care systems across the country. Due to their unique training requirements, these programs require significant resources for education, administration, and recruitment. There continues to be considerable heterogeneity in funding models between programs. Our survey findings reinforce the need for reformed federal funding models for informatics practice and training.

A Systematic Approach to the Design and Implementation of Clinical Informatics Fellowship Programs.

Clinical Informatics (CI), a medical subspecialty since 2011, has grown from the initial four fellowship programs accredited by the Accreditation Council for Graduate Medical Education (ACGME) in 2014 to more than 50 and counting in the present day. In parallel, the literature guiding Clinical Informatics Fellowship training and the curriculum evolved from the original core content published in 2009 to the more recent CI Subspecialty Delineation of Practice and the updated ACGME Milestones 2.0 for CI. In this paper, we outline this evolution and its impact on CIF Curricula. We then propose a framework, specific processes, and tools to standardize the design and optimize the implementation of CIF programs.

International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study.

BACKGROUND: Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional availability of patient-related information for health care professionals, patients, and care givers are rare. OBJECTIVES: This study aims to present eHealth indicators on cross-institutional availability of relevant patient data for health care professionals, as well as for patients and their caregivers across 14 countries (Argentina, Australia, Austria, Finland, Germany, Hong Kong as a special administrative region of China, Israel, Japan, Jordan, Kenya, South Korea, Sweden, Turkey, and the United States) to compare our indicators and the resulting data for the examined countries with other eHealth benchmarks and to extend and explore changes to a comparable survey in 2017. We defined "availability of patient data" as the ability to access data in and to add data to the patient record in the respective country. METHODS: The invited experts from each of the 14 countries provided the indicator data for their country to reflect the situation on August 1, 2019, as date of reference. Overall, 60 items were aggregated to six eHealth indicators. RESULTS: Availability of patient-related information varies strongly by country. Health care professionals can access patients' most relevant cross-institutional health record data fully in only four countries. Patients and their caregivers can access their health record data fully in only two countries. Patients are able to fully add relevant data only in one country. Finland showed the best outcome of all eHealth indicators, followed by South Korea, Japan, and Sweden. CONCLUSION: Advancement in eHealth depends on contextual factors such as health care organization, national health politics, privacy laws, and health care financing. Improvements in eHealth indicators are thus often slow. However, our survey shows that some countries were able to improve on at least some indicators between 2017 and 2019. We anticipate further improvements in the future.

X Marks the Spot: Mapping Similarity Between Clinical Trial Cohorts and US Counties.

When patients and doctors collaborate to make healthcare decisions, they rely on clinical trial results to guide discussions. Trials are designed to recruit diverse participants. The question remains - how well do trial results apply to me or to people who live in our area? This study compared one complete clinical trial dataset (SPRINT) and one published study (ACCORD) to the Community Health Status Indicators dataset to assess the similarity of the trial populations to US county populations. Counties up to 495 miles to the closest SPRINT trial site and up to 712 miles to the closest ACCORD trial site had populations that were significantly more similar to the study cohort than counties farther away. The investigators detail a generalizable method for both assessing recruitment gaps in large multicenter trials and creating maps for clinicians to provide intuition on trial applicability in their area.