PREDICTING SUICIDE ATTEMPTS AND SUICIDE DEATHS FOLLOWING OUTPATIENT VISITS USING ELECTRONIC HEALTH RECORDS

Details

• Alternative Title:
  Am J Psychiatry
• Personal Author:
  Simon, Gregory E ; Johnson, Eric ; Lawrence, Jean M ; Rossom, Rebecca C ; Ahmedani, Brian ; Lynch, Frances L ; Beck, Arne ; Waitzfelder, Beth ; Ziebell, Rebecca ; Penfold, Robert B ; Shortreed, Susan M
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• Description:
  Objective ; Develop and validate models using electronic health records to predict suicide attempt and suicide death following an outpatient visit. ; Methods ; Across seven health systems, 2,960,929 patients aged 13 or older (mean age 46, 62% female) made 10,275,853 specialty mental health visits and 9,685,206 primary care visits with mental health diagnoses between 1/1/2009 and 6/30/2015. Health system records and state death certificate data identified suicide attempts (n=24,133) and suicide deaths (n=1240) over 90 days following each visit. Potential predictors included 313 demographic and clinical characteristics extracted from records for up to five years prior to each visit: prior suicide attempts, mental health and substance use diagnoses, medical diagnoses, psychiatric medications dispensed, inpatient or emergency department care, and routinely administered PHQ-9 depression questionnaires. Logistic regression models predicting suicide attempt and death were developed using penalized LASSO variable selection in a random 65% sample of visits and validated in the remaining 35%. ; Results ; Mental health specialty visits with risk scores in the top 5% accounted for 43% of subsequent suicide attempts and 48% of suicide deaths. Of patients scoring in the top 5%, 5.4% attempted suicide and 0.26% died by suicide within 90 days. C-statistics (equivalent to AUC) for prediction of suicide attempt and suicide death were 0.851 (95% CI 0.848 to 0.853) and 0.861 (95% CI 0.848 to 0.875). Primary care visits with scores in the top 5% accounted for 48% of subsequent suicide attempts and 43% of suicide deaths. C-statistics for prediction of suicide attempt and suicide death were 0.853 (95% CI 0.849 to 0.857) and 0.833 (95% CI 0.813 to 0.853). ; Conclusions ; Prediction models incorporating both health records data and responses to self-report questionnaires substantially outperform existing suicide risk prediction tools.
• Source:
  Am J Psychiatry. 175(10):951-960
• Pubmed ID:
  29792051
• Pubmed Central ID:
  PMC6167136
• Document Type:
  Text
• Funding:
  U18 DP006133/DP/NCCDPHP CDC HHS/United States ; U19 MH092201/MH/NIMH NIH HHS/United States
• Genre:
  Journal Article
• Volume:
  175
• Issue:
  10
• Download URL:
  https://stacks.cdc.gov/view/cdc/76892/cdc_76892_DS1.pdf
• File Type:
  [PDF - 260.94 KB]
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:d153078bcddae3d3ad70df356a85908302e17a676e376f9e3f85d5dc350324b097898b778024fe764150bab9c3aea6c676feccf06780abf275a8aa01976ec389