Detecting and distinguishing indicators of risk for suicide using clinical records
Abstract Health systems are essential for suicide risk detection. Most efforts target people with mental health (MH) diagnoses, but this only represents half of the people who die by suicide. This study seeks to discover and validate health indicators of suicide death among those with, and without,...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2022-07-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-022-02051-4 |
| _version_ | 1818517805232816128 |
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| author | Brian K. Ahmedani Cara E. Cannella Hsueh-Han Yeh Joslyn Westphal Gregory E. Simon Arne Beck Rebecca C. Rossom Frances L. Lynch Christine Y. Lu Ashli A. Owen-Smith Kelsey J. Sala-Hamrick Cathrine Frank Esther Akinyemi Ganj Beebani Christopher Busuito Jennifer M. Boggs Yihe G. Daida Stephen Waring Hongsheng Gui Albert M. Levin |
| author_facet | Brian K. Ahmedani Cara E. Cannella Hsueh-Han Yeh Joslyn Westphal Gregory E. Simon Arne Beck Rebecca C. Rossom Frances L. Lynch Christine Y. Lu Ashli A. Owen-Smith Kelsey J. Sala-Hamrick Cathrine Frank Esther Akinyemi Ganj Beebani Christopher Busuito Jennifer M. Boggs Yihe G. Daida Stephen Waring Hongsheng Gui Albert M. Levin |
| author_sort | Brian K. Ahmedani |
| collection | DOAJ |
| description | Abstract Health systems are essential for suicide risk detection. Most efforts target people with mental health (MH) diagnoses, but this only represents half of the people who die by suicide. This study seeks to discover and validate health indicators of suicide death among those with, and without, MH diagnoses. This case-control study used statistical modeling with health record data on diagnoses, procedures, and encounters. The study included 3,195 individuals who died by suicide from 2000 to 2015 and 249,092 randomly selected matched controls, who were age 18+ and affiliated with nine Mental Health Research Network affiliated health systems. Of the 202 indicators studied, 170 (84%) were associated with suicide in the discovery cohort, with 148 (86%) of those in the validation cohort. Malignant cancer diagnoses were risk factors for suicide in those without MH diagnoses, and multiple individual psychiatric-related indicators were unique to the MH subgroup. Protective effects across MH-stratified models included diagnoses of benign neoplasms, respiratory infections, and utilization of reproductive services. MH-stratified latent class models validated five subgroups with distinct patterns of indicators in both those with and without MH. The highest risk groups were characterized via high utilization with multiple healthcare concerns in both groups. The lowest risk groups were characterized as predominantly young, female, and high utilizers of preventive services. Healthcare data include many indicators of suicide risk for those with and without MH diagnoses, which may be used to support the identification and understanding of risk as well as targeting of prevention in health systems. |
| first_indexed | 2024-12-11T01:01:16Z |
| format | Article |
| id | doaj.art-dcd6b18a33334bb39db283b291dea0dd |
| institution | Directory Open Access Journal |
| issn | 2158-3188 |
| language | English |
| last_indexed | 2024-12-11T01:01:16Z |
| publishDate | 2022-07-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Translational Psychiatry |
| spelling | doaj.art-dcd6b18a33334bb39db283b291dea0dd2022-12-22T01:26:20ZengNature Publishing GroupTranslational Psychiatry2158-31882022-07-011211910.1038/s41398-022-02051-4Detecting and distinguishing indicators of risk for suicide using clinical recordsBrian K. Ahmedani0Cara E. Cannella1Hsueh-Han Yeh2Joslyn Westphal3Gregory E. Simon4Arne Beck5Rebecca C. Rossom6Frances L. Lynch7Christine Y. Lu8Ashli A. Owen-Smith9Kelsey J. Sala-Hamrick10Cathrine Frank11Esther Akinyemi12Ganj Beebani13Christopher Busuito14Jennifer M. Boggs15Yihe G. Daida16Stephen Waring17Hongsheng Gui18Albert M. Levin19Henry Ford Health, Center for Health Policy & Health Services ResearchHenry Ford Health, Public Health SciencesHenry Ford Health, Center for Health Policy & Health Services ResearchHenry Ford Health, Center for Health Policy & Health Services ResearchKaiser Permanente Washington, Health Research InstituteKaiser Permanente Colorado, Institute for Health ResearchHealthPartners InstituteKaiser Permanente Northwest, Center for Health ResearchHarvard Pilgrim Health Care Institute & Harvard Medical School, Department of Population HealthGeorgia State University & Kaiser Permanente GeorgiaHenry Ford Health, Center for Health Policy & Health Services ResearchHenry Ford Health, Behavioral Health ServicesHenry Ford Health, Behavioral Health ServicesHenry Ford Health, Behavioral Health ServicesHenry Ford Health, Behavioral Health ServicesKaiser Permanente Colorado, Institute for Health ResearchKaiser Permanente Hawaii, Center for Integrated Health Care ResearchEssentia Institute of Rural HealthHenry Ford Health, Behavioral Health ServicesHenry Ford Health, Public Health SciencesAbstract Health systems are essential for suicide risk detection. Most efforts target people with mental health (MH) diagnoses, but this only represents half of the people who die by suicide. This study seeks to discover and validate health indicators of suicide death among those with, and without, MH diagnoses. This case-control study used statistical modeling with health record data on diagnoses, procedures, and encounters. The study included 3,195 individuals who died by suicide from 2000 to 2015 and 249,092 randomly selected matched controls, who were age 18+ and affiliated with nine Mental Health Research Network affiliated health systems. Of the 202 indicators studied, 170 (84%) were associated with suicide in the discovery cohort, with 148 (86%) of those in the validation cohort. Malignant cancer diagnoses were risk factors for suicide in those without MH diagnoses, and multiple individual psychiatric-related indicators were unique to the MH subgroup. Protective effects across MH-stratified models included diagnoses of benign neoplasms, respiratory infections, and utilization of reproductive services. MH-stratified latent class models validated five subgroups with distinct patterns of indicators in both those with and without MH. The highest risk groups were characterized via high utilization with multiple healthcare concerns in both groups. The lowest risk groups were characterized as predominantly young, female, and high utilizers of preventive services. Healthcare data include many indicators of suicide risk for those with and without MH diagnoses, which may be used to support the identification and understanding of risk as well as targeting of prevention in health systems.https://doi.org/10.1038/s41398-022-02051-4 |
| spellingShingle | Brian K. Ahmedani Cara E. Cannella Hsueh-Han Yeh Joslyn Westphal Gregory E. Simon Arne Beck Rebecca C. Rossom Frances L. Lynch Christine Y. Lu Ashli A. Owen-Smith Kelsey J. Sala-Hamrick Cathrine Frank Esther Akinyemi Ganj Beebani Christopher Busuito Jennifer M. Boggs Yihe G. Daida Stephen Waring Hongsheng Gui Albert M. Levin Detecting and distinguishing indicators of risk for suicide using clinical records Translational Psychiatry |
| title | Detecting and distinguishing indicators of risk for suicide using clinical records |
| title_full | Detecting and distinguishing indicators of risk for suicide using clinical records |
| title_fullStr | Detecting and distinguishing indicators of risk for suicide using clinical records |
| title_full_unstemmed | Detecting and distinguishing indicators of risk for suicide using clinical records |
| title_short | Detecting and distinguishing indicators of risk for suicide using clinical records |
| title_sort | detecting and distinguishing indicators of risk for suicide using clinical records |
| url | https://doi.org/10.1038/s41398-022-02051-4 |
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