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Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study
OBJECTIVES: The objective of this study was to determine risk factors for those diagnosed with eating disorders who report self-harm and suicidality. DESIGN AND SETTING: This study was a retrospective cohort study within a secondary mental health service, South London and Maudsley National Health Se...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720985/ https://www.ncbi.nlm.nih.gov/pubmed/34972768 http://dx.doi.org/10.1136/bmjopen-2021-053808 |
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author | Cliffe, Charlotte Seyedsalehi, Aida Vardavoulia, Katerina Bittar, André Velupillai, Sumithra Shetty, Hitesh Schmidt, Ulrike Dutta, Rina |
author_facet | Cliffe, Charlotte Seyedsalehi, Aida Vardavoulia, Katerina Bittar, André Velupillai, Sumithra Shetty, Hitesh Schmidt, Ulrike Dutta, Rina |
author_sort | Cliffe, Charlotte |
collection | PubMed |
description | OBJECTIVES: The objective of this study was to determine risk factors for those diagnosed with eating disorders who report self-harm and suicidality. DESIGN AND SETTING: This study was a retrospective cohort study within a secondary mental health service, South London and Maudsley National Health Service Trust. PARTICIPANTS: All diagnosed with an F50 diagnosis of eating disorder from January 2009 to September 2019 were included. INTERVENTION AND MEASURES: Electronic health records (EHRs) for these patients were extracted and two natural language processing tools were used to determine documentation of self-harm and suicidality in their clinical notes. These tools were validated manually for attribute agreement scores within this study. RESULTS: The attribute agreements for precision of positive mentions of self-harm were 0.96 and for suicidality were 0.80; this demonstrates a ‘near perfect’ and ‘strong’ agreement and highlights the reliability of the tools in identifying the EHRs reporting self-harm or suicidality. There were 7434 patients with EHRs available and diagnosed with eating disorders included in the study from the dates January 2007 to September 2019. Of these, 4591 (61.8%) had a mention of self-harm within their records and 4764 (64.0%) had a mention of suicidality; 3899 (52.4%) had mentions of both. Patients reporting either self-harm or suicidality were more likely to have a diagnosis of anorexia nervosa (AN) (self-harm, AN OR=3.44, 95% CI 1.05 to 11.3, p=0.04; suicidality, AN OR=8.20, 95% CI 2.17 to 30.1; p=0.002). They were also more likely to have a diagnosis of borderline personality disorder (p≤0.001), bipolar disorder (p<0.001) or substance misuse disorder (p<0.001). CONCLUSION: A high percentage of patients (>60%) diagnosed with eating disorders report either self-harm or suicidal thoughts. Relative to other eating disorders, those diagnosed with AN were more likely to report either self-harm or suicidal thoughts. Psychiatric comorbidity, in particular borderline personality disorder and substance misuse, was also associated with an increase risk in self-harm and suicidality. Therefore, risk assessment among patients diagnosed with eating disorders is crucial. |
format | Online Article Text |
id | pubmed-8720985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-87209852022-01-14 Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study Cliffe, Charlotte Seyedsalehi, Aida Vardavoulia, Katerina Bittar, André Velupillai, Sumithra Shetty, Hitesh Schmidt, Ulrike Dutta, Rina BMJ Open Mental Health OBJECTIVES: The objective of this study was to determine risk factors for those diagnosed with eating disorders who report self-harm and suicidality. DESIGN AND SETTING: This study was a retrospective cohort study within a secondary mental health service, South London and Maudsley National Health Service Trust. PARTICIPANTS: All diagnosed with an F50 diagnosis of eating disorder from January 2009 to September 2019 were included. INTERVENTION AND MEASURES: Electronic health records (EHRs) for these patients were extracted and two natural language processing tools were used to determine documentation of self-harm and suicidality in their clinical notes. These tools were validated manually for attribute agreement scores within this study. RESULTS: The attribute agreements for precision of positive mentions of self-harm were 0.96 and for suicidality were 0.80; this demonstrates a ‘near perfect’ and ‘strong’ agreement and highlights the reliability of the tools in identifying the EHRs reporting self-harm or suicidality. There were 7434 patients with EHRs available and diagnosed with eating disorders included in the study from the dates January 2007 to September 2019. Of these, 4591 (61.8%) had a mention of self-harm within their records and 4764 (64.0%) had a mention of suicidality; 3899 (52.4%) had mentions of both. Patients reporting either self-harm or suicidality were more likely to have a diagnosis of anorexia nervosa (AN) (self-harm, AN OR=3.44, 95% CI 1.05 to 11.3, p=0.04; suicidality, AN OR=8.20, 95% CI 2.17 to 30.1; p=0.002). They were also more likely to have a diagnosis of borderline personality disorder (p≤0.001), bipolar disorder (p<0.001) or substance misuse disorder (p<0.001). CONCLUSION: A high percentage of patients (>60%) diagnosed with eating disorders report either self-harm or suicidal thoughts. Relative to other eating disorders, those diagnosed with AN were more likely to report either self-harm or suicidal thoughts. Psychiatric comorbidity, in particular borderline personality disorder and substance misuse, was also associated with an increase risk in self-harm and suicidality. Therefore, risk assessment among patients diagnosed with eating disorders is crucial. BMJ Publishing Group 2021-12-31 /pmc/articles/PMC8720985/ /pubmed/34972768 http://dx.doi.org/10.1136/bmjopen-2021-053808 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Mental Health Cliffe, Charlotte Seyedsalehi, Aida Vardavoulia, Katerina Bittar, André Velupillai, Sumithra Shetty, Hitesh Schmidt, Ulrike Dutta, Rina Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
title | Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
title_full | Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
title_fullStr | Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
title_full_unstemmed | Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
title_short | Using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
title_sort | using natural language processing to extract self-harm and suicidality data from a clinical sample of patients with eating disorders: a retrospective cohort study |
topic | Mental Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8720985/ https://www.ncbi.nlm.nih.gov/pubmed/34972768 http://dx.doi.org/10.1136/bmjopen-2021-053808 |
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