The Learning Health System Competency Appraisal Inventory (LHS-CAI): A novel tool for assessing LHS-focused education needs.

competency‐based learning learning health systems research education

Journal

Learning health systems
ISSN: 2379-6146
Titre abrégé: Learn Health Syst
Pays: United States
ID NLM: 101708071

Informations de publication

Date de publication:
Apr 2021
Historique:
received: 30 07 2019
revised: 09 12 2019
accepted: 02 01 2020
entrez: 23 4 2021
pubmed: 12 2 2020
medline: 12 2 2020
Statut: epublish

Résumé

There is increasing interest in health care organizations functioning as learning health systems (LHSs) to improve the quality and efficiency of health care delivery while generating new knowledge. Individuals must be trained in associated concepts and competencies and subsequently positioned (or embedded) within the delivery system for maximum effect as they perform their scholarship. Potential researchers within LHSs come from many different training backgrounds; therefore, each LHS scholar requires a goal-directed plan tailored to his or her needs. There are few tools available to guide development, training, or evaluation of individuals interested in becoming leaders of research in LHSs. In this paper, we present a newly developed tool for guiding the training of such researchers, the Learning Health Systems Competency Appraisal Inventory (LHS-CAI). The LHS-CAI is modeled after the Clinical Research Appraisal Index (CRAI) used within Clinical and Translational Science Award sites across the United States. The LHS-CAI is a tool for trainees at all levels to use with their mentors in an interactive manner. The tool can then identify areas in which more training is needed and at what level to ensure success as a researcher within LHSs. We further modified the CRAI format to better leverage the LHS-CAI as a key part of an LHS scholar's individual development plan. To implement the LHS-CAI, we have identified key points within the Minnesota Learning Health System Mentored Career Development Program (MN-LHS) at which assessment of expertise for each competency would be useful to LHS scholars, mentors, and program leaders. Scholars in this program come from various clinical and academic backgrounds but are all targeting their career trajectories toward leading embedded LHS research. They will reevaluate their expertise upon completion of the program, with comparison to baseline serving as a key program evaluation tool. The LHS-CAI is currently being implemented with the first cohort of scholars in the MN-LHS program.

Identifiants

pubmed: 33889729
doi: 10.1002/lrh2.10218
pii: LRH210218
pmc: PMC8051341
doi:

Types de publication

Journal Article

Langues

eng

Informations de copyright

© 2020 The Authors. Learning Health Systems published by Wiley Periodicals, Inc. on behalf of the University of Michigan.

Déclaration de conflit d'intérêts

All authors assert that they have no conflicts of interest.

Références

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Auteurs

Alexandra J Greenberg-Worisek (AJ)

Epidemiology Mayo Clinic College of Medicine Rochester Minnesota USA.

Nathan D Shippee (ND)

Division of Health Policy and Management University of Minnesota School of Public Health Minneapolis Minnesota USA.

Cory Schaffhausen (C)

Division of General Internal Medicine Hennepin Healthcare Research Institute Minneapolis Minnesota USA.

Kelli Johnson (K)

Division of Health Policy and Management University of Minnesota School of Public Health Minneapolis Minnesota USA.

Nilay D Shah (ND)

Division of Health Care Policy and Research Mayo Clinic College of Medicine Rochester Minnesota USA.
Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery Mayo Clinic Rochester Minnesota USA.

Mark Linzer (M)

Department of Medicine, Hennepin Healthcare and Hennepin Healthcare Research Institute Minneapolis Minnesota USA.

Timothy Beebe (T)

Division of Health Policy and Management University of Minnesota School of Public Health Minneapolis Minnesota USA.

Felicity Enders (F)

Clinical Statistics Mayo Clinic College of Medicine Rochester Minnesota USA.

Classifications MeSH