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      Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments

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          Abstract

          Background

          To date, our ability to accurately identify patients at high risk from suicidal behaviour, and thus to target interventions, has been fairly limited. This study examined a large pool of factors that are potentially associated with suicide risk from the comprehensive electronic medical record (EMR) and to derive a predictive model for 1–6 month risk.

          Methods

          7,399 patients undergoing suicide risk assessment were followed up for 180 days. The dataset was divided into a derivation and validation cohorts of 4,911 and 2,488 respectively. Clinicians used an 18-point checklist of known risk factors to divide patients into low, medium, or high risk. Their predictive ability was compared with a risk stratification model derived from the EMR data. The model was based on the continuation-ratio ordinal regression method coupled with lasso (which stands for least absolute shrinkage and selection operator).

          Results

          In the year prior to suicide assessment, 66.8% of patients attended the emergency department (ED) and 41.8% had at least one hospital admission. Administrative and demographic data, along with information on prior self-harm episodes, as well as mental and physical health diagnoses were predictive of high-risk suicidal behaviour. Clinicians using the 18-point checklist were relatively poor in predicting patients at high-risk in 3 months (AUC 0.58, 95% CIs: 0.50 – 0.66). The model derived EMR was superior (AUC 0.79, 95% CIs: 0.72 – 0.84). At specificity of 0.72 (95% CIs: 0.70-0.73) the EMR model had sensitivity of 0.70 (95% CIs: 0.56-0.83).

          Conclusion

          Predictive models applied to data from the EMR could improve risk stratification of patients presenting with potential suicidal behaviour. The predictive factors include known risks for suicide, but also other information relating to general health and health service utilisation.

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          Most cited references35

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          Comorbidity measures for use with administrative data.

          This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets. The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other aspects of the patient's condition, development of a comorbidity algorithm, and testing on heterogeneous and homogeneous patient groups. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in California in 1992 (n = 1,779,167). Outcome measures were those commonly available in administrative data: length of stay, hospital charges, and in-hospital death. A comprehensive set of 30 comorbidity measures was developed. The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Several comorbidities are described that are important predictors of outcomes, yet commonly are not measured. These include mental disorders, drug and alcohol abuse, obesity, coagulopathy, weight loss, and fluid and electrolyte disorders. The comorbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently among different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive approach to identifying comorbidities and separates them from the primary reason for hospitalization, resulting in an expanded set of comorbidities that easily is applied without further refinement to administrative data for a wide range of diseases.
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            Contact With Mental Health and Primary Care Providers Before Suicide: A Review of the Evidence

            Objective This study examined rates of contact with primary care and mental health care professionals by individuals before they died by suicide. Method The authors reviewed 40 studies for which there was information available on rates of health care contact and examined age and gender differences among the subjects. Results Contact with primary care providers in the time leading up to suicide is common. While three of four suicide victims had contact with primary care providers within the year of suicide, approximately one-third of the suicide victims had contact with mental health services. About one in five suicide victims had contact with mental health services within a month before their suicide. On average, 45% of suicide victims had contact with primary care providers within 1 month of suicide. Older adults had higher rates of contact with primary care providers within 1 month of suicide than younger adults. Conclusions While it is not known to what degree contact with mental health care and primary care providers can prevent suicide, the majority of individuals who die by suicide do make contact with primary care providers, particularly older adults. Given that this pattern is consistent with overall health-service-seeking, alternate approaches to suicide-prevention efforts may be needed for those less likely to be seen in primary care or mental health specialty care, specifically young men.
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              Twelve-month prevalence of and risk factors for suicide attempts in the World Health Organization World Mental Health Surveys.

              Although suicide is a leading cause of death worldwide, clinicians and researchers lack a data-driven method to assess the risk of suicide attempts. This study reports the results of an analysis of a large cross-national epidemiologic survey database that estimates the 12-month prevalence of suicidal behaviors, identifies risk factors for suicide attempts, and combines these factors to create a risk index for 12-month suicide attempts separately for developed and developing countries. Data come from the World Health Organization (WHO) World Mental Health (WMH) Surveys (conducted 2001-2007), in which 108,705 adults from 21 countries were interviewed using the WHO Composite International Diagnostic Interview. The survey assessed suicidal behaviors and potential risk factors across multiple domains, including sociodemographic characteristics, parent psychopathology, childhood adversities, DSM-IV disorders, and history of suicidal behavior. Twelve-month prevalence estimates of suicide ideation, plans, and attempts are 2.0%, 0.6%, and 0.3%, respectively, for developed countries and 2.1%, 0.7%, and 0.4%, respectively, for developing countries. Risk factors for suicidal behaviors in both developed and developing countries include female sex, younger age, lower education and income, unmarried status, unemployment, parent psychopathology, childhood adversities, and presence of diverse 12-month DSM-IV mental disorders. Combining risk factors from multiple domains produced risk indices that accurately predicted 12-month suicide attempts in both developed and developing countries (area under the receiver operating characteristic curve = 0.74-0.80). Suicidal behaviors occur at similar rates in both developed and developing countries. Risk indices assessing multiple domains can predict suicide attempts with fairly good accuracy and may be useful in aiding clinicians in the prediction of these behaviors. © Copyright 2010 Physicians Postgraduate Press, Inc.
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                Author and article information

                Contributors
                Journal
                BMC Psychiatry
                BMC Psychiatry
                BMC Psychiatry
                BioMed Central
                1471-244X
                2014
                14 March 2014
                : 14
                : 76
                Affiliations
                [1 ]Centre for Pattern Recognition and Data Analytics, Deakin University, Geelong 3220, Australia
                [2 ]Department of Computing, Curtin University, Bentley, Australia
                [3 ]Mental Health Services, Barwon Health, Geelong, Australia
                [4 ]School of Medicine, Deakin University, Geelong, Australia
                [5 ]Barwon Health, Geelong, Australia
                [6 ]Mental Health Research Institute, University of Melbourne, Parkville, Australia
                [7 ]Orygen Youth Health Research Centre, Parkville, Australia
                Article
                1471-244X-14-76
                10.1186/1471-244X-14-76
                3984680
                24628849
                94789a25-659e-4eca-8ede-1975952e7739
                Copyright © 2014 Tran et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 February 2014
                : 10 March 2014
                Categories
                Research Article

                Clinical Psychology & Psychiatry
                suicide risk,electronic medical record,predictive models
                Clinical Psychology & Psychiatry
                suicide risk, electronic medical record, predictive models

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