Can routine primary care records help in detecting suicide risk? A population-based case-control study in Barcelona

Objectives To characterize people who died by suicide after having previous contacts with public health system using the data available in a primary care setting. Method A retrospective, population-based case-control study identified through autopsy reports subjects who died from suicide between 2010 and 2015 in Barcelona province. Those who had previous interaction with primary healthcare […]

Frequency of clinicians’ assessments for access to lethal means in persons at risk for suicide

Objective We measured the frequency of clinicians’ assessments for access to lethal means, including firearms and medications in patients at risk of suicide from electronic medical and mental health records in outpatient and emergency settings. Methods We included adult patients who reported suicide ideation on the PHQ-9 depression screener in behavioral health and primary care […]

Translating promise into practice: A review of machine learning in suicide research and prevention

In ever more pressured health-care systems, technological solutions offering scalability of care and better resource targeting are appealing. Research on machine learning as a technique for identifying individuals at risk of suicidal ideation, suicide attempts, and death has grown rapidly. This research often places great emphasis on the promise of machine learning for preventing suicide, but […]

Prediction of suicide attempts using clinician assessment, patient self-report, and electronic health records

Objective  To predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems. Design, Setting, and Participants  This prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was […]

Perceived utility and characterization of personal Google search histories to detect data patterns proximal to a suicide attempt in individuals who previously attempted suicide: Pilot cohort study

Background: Despite decades of research to better understand suicide risk and to develop detection and prevention methods, suicide is still one of the leading causes of death globally. While large-scale studies using real-world evidence from electronic health records can identify who is at risk, they have not been successful at pinpointing when someone is at risk. […]

Machine learning assessment of early life factors predicting suicide attempt in adolescence or young adulthood

Importance  Although longitudinal studies have reported associations between early life factors (ie, in-utero/perinatal/infancy) and long-term suicidal behavior, they have concentrated on 1 or few selected factors, and established associations, but did not investigate if early-life factors predict suicidal behavior. Objective  To identify and evaluate the ability of early-life factors to predict suicide attempt in adolescents and young […]

Prospective validation of an electronic health record-based, real-time suicide risk model

Objective  To evaluate performance of a suicide attempt risk prediction model implemented in a vendor-supplied electronic health record to predict subsequent (1) suicidal ideation and (2) suicide attempt. Design, Setting, and Participants  This observational cohort study evaluated implementation of a suicide attempt prediction model in live clinical systems without alerting. The cohort comprised patients seen for any […]

Comparing the predictive value of suicide risk screening to the detection of suicide risk using electronic health records in an urban pediatric emergency department

Objective To compare the accuracy, sensitivity and utility of brief screening to predictive modeling for identifying suicide-related outcomes in a pediatric emergency department. Our hypothesis was that predictive modeling would be more accurate and useful compared to brief screening. Methods This was a retrospective cohort study at an urban pediatric Emergency Department (PED) in the United States. […]

COVID-19 risk and outcomes in patients with substance use disorders: Analyses from electronic health records in the United States

The global pandemic of COVID-19 is colliding with the epidemic of opioid use disorders (OUD) and other substance use disorders (SUD) in the United States (US). Currently, there is limited data on risks, disparity, and outcomes for COVID-19 in individuals suffering from SUD. This is a retrospective case-control study of electronic health records (EHRs) data […]

Relative accuracy of social and medical determinants of suicide in electronic health records

Objective This paper compares the accuracy of predicting suicide from Social Determinants of Health (SDoH) or history of illness. Population Studied 5 313 965 Veterans who at least had two primary care visits between 2008 and 2016. Study Design The dependent variable was suicide or intentional self‐injury. The independent variables were 10 495 International Classification of Disease (ICD) […]

Identifying and predicting intentional self-harm in electronic health record clinical notes: Deep learning approach

Background: Suicide is an important public health concern in the United States and around the world. There has been significant work examining machine learning approaches to identify and predict intentional self-harm and suicide using existing data sets. With recent advances in computing, deep learning applications in health care are gaining momentum. Objective: This study aimed to […]

Australian Suicide Prevention using Health-Linked Data (ASHLi): Protocol for a population-based case series study

Introduction In Australia, suicide is the leading cause of death for people aged 15–44 years. Health professionals deliver most of our key suicide prevention strategies via health services, but other efficacious population-level strategies include means restriction and public awareness campaigns. Currently, we have no population-level data allowing us to determine which individuals, in what parts of […]

Predicting death by suicide with administrative health care system data

ABSTRACT Quantifying suicide risk with risk scales is common in clinical practice, but the performance of risk scales has been shown to be limited. Prediction models have been developed to quantify suicide risk and have been shown to outperform risk scales, but these models have not been commonly adopted in clinical practice. The original research […]

Clinician-recalled quoted speech in electronic health records and risk of suicide attempt: A case-crossover study

Objective: Clinician narrative style in electronic health records (EHR) has rarely been investigated. Clinicians sometimes record brief quotations from patients, possibly more frequently when higher risk is perceived. We investigated whether the frequency of quoted phrases in an EHR was higher in time periods closer to a suicide attempt. Design: A case-crossover study was conducted in a […]

Validation of an electronic health record-based suicide risk prediction modeling approach across multiple health care systems

Importance  Suicide is a leading cause of mortality, with suicide-related deaths increasing in recent years. Automated methods for individualized risk prediction have great potential to address this growing public health threat. To facilitate their adoption, they must first be validated across diverse health care settings. Objective  To evaluate the generalizability and cross-site performance of a risk prediction […]

Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records

Suicide is the tenth leading cause of death in the United States (US). An early-warning system (EWS) for suicide attempt could prove valuable for identifying those at risk of suicide attempts, and analyzing the contribution of repeated attempts to the risk of eventual death by suicide. In this study we sought to develop an EWS […]

A systematic review of validated suicide outcome classification in observational studies

BACKGROUND: Suicidal outcomes, including ideation, attempt, and completed suicide, are an important drug safety issue, though few epidemiological studies address the accuracy of suicidal outcome ascertainment. Our primary objective was to evaluate validated methods for suicidal outcome classification in electronic health care database studies. METHODS: We performed a systematic review of PubMed and EMBASE to […]

Which chart elements accurately identify emergency department visits for suicidal ideation or behavior?

In an emergency department (ED) sample, we investigated the concordance between identification of suicide-related visits through standardized comprehensive chart review versus a subset of 3 specific chart elements: ICD-9-CM codes, free-text presenting complaints, and free-text physician discharge diagnoses. The method for this study was review of medical records for adults (≥18 years) at 8 EDs across […]

Ethical and practical considerations in the use of a predictive model to trigger suicide prevention interventions in healthcare settings

Predictive models that utilize data from electronic healthcare records (EHR) have been developed, investigated, and appear to provide an important resource for suicide prevention in medical settings. Actuarial approaches to predicting suicide may be particularly important given the relative inability of clinicians to accurately predict suicide. Although research regarding predictive models that utilize EHR is […]

Team communication within integrated primary care in the context of suicide prevention: A mixed methods preliminary examination

Direct and indirect communication through the electronic medical record play a vital role in helping medical home primary care teams implement suicide prevention efforts. The purpose of this study is to examine how communication related to suicide prevention occurs among primary care team members working within a group of clinics in the Veterans Health Administration […]

Predicting suicide attempts and suicide deaths following outpatient visits using electronic health records.

Objective: The authors sought to develop and validate models using electronic health records to predict suicide attempt and suicide death following an outpatient visit. Method: Across seven health systems, 2,960,929 patients age 13 or older (mean age, 46 years; 62% female) made 10,275,853 specialty mental health visits and 9,685,206 primary care visits with mental health […]