Literature DB >> 30301448

Integrating Predictive Modeling Into Mental Health Care: An Example in Suicide Prevention.

Greg M Reger1, Mary Lou McClure1, David Ruskin1, Sarah P Carter1, Mark A Reger1.   

Abstract

Recent advances in statistical methods and computing power have improved the ability to predict risks associated with mental illness with more efficiency and accuracy. However, integrating statistical prediction into a clinical setting poses new challenges that need creative solutions. A case example explores the challenges and innovations that emerged at a Department of Veterans Affairs hospital while implementing REACH VET (Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment), a suicide prevention program that is based on a predictive model that identifies veterans at statistical risk for suicide.

Entities:  

Keywords:  Computer technology; Self-destructive behavior; Suicide; predictive models; veterans

Mesh:

Year:  2018        PMID: 30301448     DOI: 10.1176/appi.ps.201800242

Source DB:  PubMed          Journal:  Psychiatr Serv        ISSN: 1075-2730            Impact factor:   3.084


  11 in total

1.  Reaching Those at Highest Risk for Suicide: Development of a Model Using Machine Learning Methods for use With Native American Communities.

Authors:  Emily E Haroz; Colin G Walsh; Novalene Goklish; Mary F Cwik; Victoria O'Keefe; Allison Barlow
Journal:  Suicide Life Threat Behav       Date:  2019-11-06

2.  Jiang et al. Respond to "Quantitative Bias Analysis".

Authors:  Tammy Jiang; Jaimie L Gradus; Timothy L Lash; Matthew P Fox
Journal:  Am J Epidemiol       Date:  2021-09-01       Impact factor: 4.897

3.  Suicide Among Veterans: Veterans' Issues in Focus.

Authors:  Rajeev Ramchand
Journal:  Rand Health Q       Date:  2022-06-30

4.  What health records data are required for accurate prediction of suicidal behavior?

Authors:  Gregory E Simon; Susan M Shortreed; Eric Johnson; Rebecca C Rossom; Frances L Lynch; Rebecca Ziebell; And Robert B Penfold
Journal:  J Am Med Inform Assoc       Date:  2019-12-01       Impact factor: 4.497

5.  Patient perspectives on acceptability of, and implementation preferences for, use of electronic health records and machine learning to identify suicide risk.

Authors:  Bobbi Jo H Yarborough; Scott P Stumbo
Journal:  Gen Hosp Psychiatry       Date:  2021-03-04       Impact factor: 3.238

Review 6.  Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.

Authors:  Ellen E Lee; John Torous; Munmun De Choudhury; Colin A Depp; Sarah A Graham; Ho-Cheol Kim; Martin P Paulus; John H Krystal; Dilip V Jeste
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2021-02-08

7.  Addressing Suicide in the Veteran Population: Engaging a Public Health Approach.

Authors:  David Carroll; Lisa K Kearney; Matthew A Miller
Journal:  Front Psychiatry       Date:  2020-11-23       Impact factor: 4.157

8.  Learning health systems: Driving real-world impact in mental health and substance use disorder research.

Authors:  Amy M Kilbourne; Emily Evans; David Atkins
Journal:  FASEB Bioadv       Date:  2021-04-07

9.  Association of Online Risk Factors With Subsequent Youth Suicide-Related Behaviors in the US.

Authors:  Steven A Sumner; Brock Ferguson; Brian Bason; Jacob Dink; Ellen Yard; Marci Hertz; Brandon Hilkert; Kristin Holland; Melissa Mercado-Crespo; Shichao Tang; Christopher M Jones
Journal:  JAMA Netw Open       Date:  2021-09-01

10.  Evaluation of the Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment Suicide Risk Modeling Clinical Program in the Veterans Health Administration.

Authors:  John F McCarthy; Samantha A Cooper; Kallisse R Dent; Aaron E Eagan; Bridget B Matarazzo; Claire M Hannemann; Mark A Reger; Sara J Landes; Jodie A Trafton; Michael Schoenbaum; Ira R Katz
Journal:  JAMA Netw Open       Date:  2021-10-01
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.