Mental illness is extremely common the United States, with one in five adults living with a psychiatric disorder.
Mental illness can take a toll on an individual's life, adversely impacting interpersonal relationships, professional and educational advancement, and general life satisfaction. Mental illness can even, tragically, lead to suicide.
Given the severe gravity of mental illness, more research must be done to understand these conditions, their impact, and neurodiversity more broadly.
Our Goal
We are aiming to create an extensive database containing demographic and clinical data from patients at the University of Iowa Hospitals and Clinics who are at an increased risk for mental illness. This database, the Neurodiversity and Mental Health Knowledgebase (NDVR KB), will serve as a resource for researchers from various disciplines, who can utilize its ample and diverse data to answer questions about neurodiversity, mental health related conditions, and overall brain health.
Included Data
The data in the database will will be compiled from the Epic electronic medical record system, hospital billing records, and additional sources as available, such as neuroimaging, cytogenetics, and linguistic labs and facilities. Researchers interested in knowing the exact types of data available can reach out to jacob-michaelson@uiowa.edu.
Data Protection and Privacy
All working datasets will have identifying information removed and replaced with either a letter or numeric code. Only key study personnel will have access to the database that links this code to identifying information. The database will be stored on a password-protected, secure server. Finally, sub-project investigators will delete individual level data upon completion of their research project.
Project Advantages
The data held in this database is retrospective, beginning from 1/1/2005 (the creation of Epic medical record system) to the present day. This data is readily accessible and analyzable, providing a convenient introduction to research for students and trainees, as well as the opportunity to define and refine the performance of various techniques and methodologies in large datasets.
Additionally, given that IRB review and approval often takes longer than the research time available to conduct researcher project, this endeavor increases efficiency by adding researchers' projects as sub-projects under one parent IRB. Each individual sub-project will still undergo IRB review and approval (as a "modification" to the parent IRB) but the time and administrative burden for this to occur will be significantly reduced than if the project were to stand alone.