title: The use of logistic regression to enhance risk assessment and decision making by mental health administrators.
abstract: Development of policies and procedures to contend with the risks presented by elopement, aggression, and suicidal behaviors are long-standing challenges for mental health administrators. Guidance in making such judgments can be obtained through the use of a multivariate statistical technique known as logistic regression. This procedure can be used to develop a predictive equation that is mathematically formulated to use the best combination of predictors, rather than considering just one factor at a time. This paper presents an overview of logistic regression and its utility in mental health administrative decision making. A case example of its application is presented using data on elopements from Missouri's long-term state psychiatric hospitals. Ultimately, the use of statistical prediction analyses tempered with differential qualitative weighting of classification errors can augment decision-making processes in a manner that provides guidance and flexibility while wrestling with the complex problem of risk assessment and decision making.
authors.affiliation: Missouri Department of Mental Health, Fulton State Hospital, 600 East 5th St., 65251, USA. anthony.menditto@dmh.mo.gov
authors.forename: Anthony A
authors.initials: AA
authors.lastname: Menditto
authors.forename: Donald M
authors.initials: DM
authors.lastname: Linhorst
authors.forename: James C
authors.initials: JC
authors.lastname: Coleman
authors.forename: Niels C
authors.initials: NC
authors.lastname: Beck
mesh_terms: D000328:Adult; D003430:Cross-Sectional Studies; D003657:Decision Making; D005260:Female; D006740:Hospital Administrators; D006778:Hospitals, Psychiatric; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008923:Missouri; D019982:Organizational Case Studies; D018570:Risk Assessment / Q000706:statistics & numerical data*