The Clinical Assessment and Remote Administration Tablet

Electronic data capture of case report forms (CRFs), demographic, neuropsychiatric, or clinical assessments, can vary from scanning hand-written forms into databases to fully electronic systems. Web-based forms can be extremely useful for self-assessment; however, in the case of neuropsychiatric as...

Full description

Bibliographic Details
Main Authors: Jessica A Turner, Susan R. Lane, Henry Jeremy Bockholt, Vince D. Calhoun
Format: Article
Language:English
Published: Frontiers Media S.A. 2011-12-01
Series:Frontiers in Neuroinformatics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fninf.2011.00031/full
Description
Summary:Electronic data capture of case report forms (CRFs), demographic, neuropsychiatric, or clinical assessments, can vary from scanning hand-written forms into databases to fully electronic systems. Web-based forms can be extremely useful for self-assessment; however, in the case of neuropsychiatric assessments, self-assessment is often not an option. The clinician often must be the person either summarizing or making their best judgment about the subject’s response in order to complete an assessment, and having the clinician turn away to type into a web browser may be disruptive to the flow of the interview. The Mind Research Network (MRN) has developed a prototype for a software tool for the real-time acquisition and validation of clinical assessments in remote environments. We have developed the Clinical Assessment and Remote Administration Tablet (CARAT) on a Microsoft Windows PC tablet system, which has been adapted to interact with various data models already in use in several large-scale databases of neuroimaging studies in clinical populations. The tablet has been used successfully to collect and administer clinical assessments in several large-scale studies, so that the correct clinical measures are integrated with the correct imaging and other data. It has proven to be incredibly valuable in confirming that data collection across multiple research groups is performed similarly, quickly, and with accountability for incomplete datasets. We present the overall architecture and an evaluation of its use.
ISSN:1662-5196