Enhancing early detection of cognitive impairment in the criminal justice system: feasibility of a proposed method. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Jeanneret, Ruthie; Spiranovic, Caroline; Eckstein, Lisa; McWhirter, Rebekah; Arstein-Kerslake, Anna; Scanlan, Joel; Kirkby, Kenneth; Watters, Paul; Vickers, James
• Is Part Of: Current issues in criminal justice. Volume 31:Issue 1(2019)
• Page Start: 60
• Page End: 74
• Publication Date: 2019-01-02
• Subjects: cognitive impairment -- criminal justice system -- data linkage -- early detection -- electronic health records -- ethics -- natural language processing -- privacy; Criminal justice, Administration of -- Periodicals; Criminal justice, Administration of -- Australia -- Periodicals; Criminology -- Periodicals; Criminology -- Australia -- Periodicals; 364.05
• DOI: 10.1080/10345329.2018.1556283
• Languages: English
• ISSNs: 1034-5329

Abstract

ABSTRACT: Persons with cognitive impairment(s) are over-represented in the criminal justice system (CJS), yet many instances of cognitive impairment go undiagnosed. As this article outlines, it would be both desirable and feasible to use automated alerts to flag accused persons who may require assistance in interacting with the CJS either due to a confirmed or likely diagnosis of a cognitive impairment or other relevant condition. A proposed method to develop this alert system is outlined, combining natural language processing (NLP) applied to electronic health records (EHRs) with data linkage (DL) of health and CJS data. Although there are technical barriers, this article focuses on the ethical and legal barriers of this proposed approach. It is concluded that the overall benefits of the proposed alert system would likely outweigh potential adverse outcomes. It is argued that a waiver of consent would be appropriate and that legal barriers, in terms of privacy legislation at both Federal and State levels, which apply varying requirements for the disclosure of personal information, may be overcome in part through de-identification strategies. The examples provided in this paper of criminological data linkage projects support the feasibility of the method proposed.