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Enhancing early detection of cognitive impairment in the criminal justice system: feasibility of a proposed method
Citation
Jeanneret, R and Spiranovic, C and Eckstein, L and McWhirter, R and Arstein-Kerslake, A and Scanlan, J and Kirkby, K and Watters, P and Vickers, JC, Enhancing early detection of cognitive impairment in the criminal justice system: feasibility of a proposed method, Current Issues in Criminal Justice pp. 1-15. ISSN 1034-5329 (2019) [Refereed Article]
 | PDF (Author manuscript) Available from 10 August 2020 253Kb |
Copyright Statement
© 2019 Sydney Institute of Criminology
DOI: doi:10.1080/10345329.2018.1556283
Abstract
Persons with cognitive impairment(s) are overrepresented 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.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | criminal justice system, cognitive impairment, early detection, natural language processing, data linkage, electronic health records, ethics, privacy, mental health |
| Research Division: | Studies in Human Society |
| Research Group: | Criminology |
| Research Field: | Causes and Prevention of Crime |
| Objective Division: | Law, Politics and Community Services |
| Objective Group: | Justice and the Law |
| Objective Field: | Criminal Justice |
| UTAS Author: | Jeanneret, R (Miss Ruthie Jeanneret) |
| UTAS Author: | Spiranovic, C (Dr Caroline Spiranovic) |
| UTAS Author: | Eckstein, L (Dr Lisa Eckstein) |
| UTAS Author: | McWhirter, R (Dr Rebekah McWhirter) |
| UTAS Author: | Arstein-Kerslake, A (Dr Anna Arstein-Kerslake) |
| UTAS Author: | Scanlan, J (Dr Joel Scanlan) |
| UTAS Author: | Kirkby, K (Professor Kenneth Kirkby) |
| UTAS Author: | Vickers, JC (Professor James Vickers) |
| ID Code: | 128870 |
| Year Published: | 2019 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2018-10-19 |
| Last Modified: | 2019-03-21 |
| Downloads: | 0 |
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