Christine Leonard Westgate1, Brian Shiner1, Paul Thompson1, Bradley V Watts1. 1. Ms. Leonard Westgate is with the Research Service of the White River Junction Veterans Affairs (VA) Medical Center, White River Junction, Vermont, where Dr. Shiner is with the Department of Mental Health and Behavioral Science Service and Dr. Watts is with the National Center for Patient Safety Field Office (e-mail: christine.westgate@va.gov ). Dr. Thompson is with the Veterans Health Administration Office of Informatics and Analytics, Washington, D.C.
Abstract
OBJECTIVE: Many people who die from suicide received recent medical care prior to their death. Suicide risk assessment tools for health care settings focus on a variety of clinical and demographic factors but generally do not examine the text of notes written by clinicians about patients who later die from suicide. This study examined whether clinicians' notes indicated increased use of distancing language during the year preceding patients' suicide. METHODS: The linguistic content of clinicians' notes for outpatients of U.S. Department of Veterans Affairs (VA) medical centers was examined in the year preceding suicide of 63 veterans. Approximately half of the veterans had received mental health services. They were matched based on mental health service use with living VA outpatients. Linguistics software was used to construct quantitative theme-based categories related to distancing language and to examine temporal trends via keyword analysis. RESULTS: Analysis of clinical notes for outpatients who died from suicide and those who did not revealed a significant difference in clinicians' distancing language. Multiple keywords emerged that also were related to distancing language, and their relative frequency increased in the time approaching the suicide. CONCLUSIONS: Linguistic analysis is a promising approach to identify use of distancing language by clinicians, which appears to be a marker of suicide risk. This pilot work indicates that additional analysis and validation with larger cohorts are warranted.
OBJECTIVE: Many people who die from suicide received recent medical care prior to their death. Suicide risk assessment tools for health care settings focus on a variety of clinical and demographic factors but generally do not examine the text of notes written by clinicians about patients who later die from suicide. This study examined whether clinicians' notes indicated increased use of distancing language during the year preceding patients' suicide. METHODS: The linguistic content of clinicians' notes for outpatients of U.S. Department of Veterans Affairs (VA) medical centers was examined in the year preceding suicide of 63 veterans. Approximately half of the veterans had received mental health services. They were matched based on mental health service use with living VA outpatients. Linguistics software was used to construct quantitative theme-based categories related to distancing language and to examine temporal trends via keyword analysis. RESULTS: Analysis of clinical notes for outpatients who died from suicide and those who did not revealed a significant difference in clinicians' distancing language. Multiple keywords emerged that also were related to distancing language, and their relative frequency increased in the time approaching the suicide. CONCLUSIONS: Linguistic analysis is a promising approach to identify use of distancing language by clinicians, which appears to be a marker of suicide risk. This pilot work indicates that additional analysis and validation with larger cohorts are warranted.
Authors: Gregory E Simon; Susan M Shortreed; Eric Johnson; Rebecca C Rossom; Frances L Lynch; Rebecca Ziebell; And Robert B Penfold Journal: J Am Med Inform Assoc Date: 2019-12-01 Impact factor: 4.497
Authors: Qiu-Yue Zhong; Elizabeth W Karlson; Bizu Gelaye; Sean Finan; Paul Avillach; Jordan W Smoller; Tianxi Cai; Michelle A Williams Journal: BMC Med Inform Decis Mak Date: 2018-05-29 Impact factor: 2.796
Authors: Esther Lydia Meerwijk; Suzanne R Tamang; Andrea K Finlay; Mark A Ilgen; Ruth M Reeves; Alex H S Harris Journal: BMJ Open Date: 2022-08-24 Impact factor: 3.006