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Geospatial identification of high youth suicide risk areas via electronic health records: Avenues for research and prevention efforts
Author(s) -
Hill Ryan M.,
Gushanas Kimberly L.,
Alvis Lauren,
Dodd Cody G.,
Kurian Sherin,
Saxena Johanna,
Saxena Kirti,
Kaplow Julie B.,
Rufino Katrina,
Williams Laurel
Publication year - 2021
Publication title -
suicide and life‐threatening behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.544
H-Index - 90
eISSN - 1943-278X
pISSN - 0363-0234
DOI - 10.1111/sltb.12701
Subject(s) - suicide prevention , public health , poison control , occupational safety and health , injury prevention , medicine , environmental health , geospatial analysis , human factors and ergonomics , risk assessment , medical emergency , emergency department , psychiatry , geography , computer security , nursing , cartography , pathology , computer science
Objective As suicide risk screening becomes more common in healthcare settings, geospatial coding of behavioral health data may offer a means for identifying areas of elevated suicide risk for use in public health prevention efforts. The present study demonstrates an analytic approach for using universal suicide risk screening data to identify areas of elevated suicide risk. Method Data were drawn from standard suicide risk screens recorded in electronic health records of a large pediatric emergency department. A total of 12,400 suicide risk screening responses were recorded, among youth aged 11–19 years (mean = 14.60, SD = 2.16; 57.2% girls, 47.8% Hispanic/Latinx, 72.1% White). A total of 86 unique ZIP codes had at least 50 completed screens, representing 9139 respondents. Results Rates of positive screens ranged from 6.17% to 31.03% (mean = 18.33, SD = 5.14) for any suicide‐related behavior and from 0.0% to 19.61% (mean = 9.14, SD = 3.43) for suicide attempt. Rates of positive screens approximated a normal distribution. Conclusions Results demonstrated several areas with elevated rates of positive suicide risk screens, within the hospital catchment area. The proposed method capitalizes on large‐scale screening data, provides an estimate of areas of relative increased risk, and may be used to inform public health responses to suicide prevention.