Application of mixture distributions for identifying thresholds of frequent and high inpatient mental health service use in longitudinal data. (2nd January 2023)

• Record Type: Journal Article
• Authors: Suesse, Bianca; Lago, Luise; Westley-Wise, Victoria; Masso, Malcolm; Cuenca, Jose; Pai, Nagesh
• Is Part Of: Journal of mental health. Volume 32:Number 1(2023)
• Page Start: 33
• Page End: 42
• Publication Date: 2023-01-02
• Subjects: Adults -- hospitalisation -- inpatients -- mental health -- statistical model -- threshold; Mental health -- Periodicals; Mental health services -- Periodicals; 362.2
• DOI: 10.1080/09638237.2021.1875407
• Languages: English
• ISSNs: 0963-8237

Abstract

Abstract: Background: There is a need for greater understanding about frequent and high use of inpatient mental health services, and those with ongoing increased needs. Most studies employ a threshold of frequent use (e.g. numbers of admissions) and high use (e.g. lengthy stays) without justification. Aims: To identify model-driven thresholds for frequent/high inpatient mental health service use and contrast characteristics of patients identified using various models and thresholds. Method: Retrospective population-based study using 12 years of longitudinal data for 5631 patients admitted with a mental health diagnosis. Two-component negative binomial and poisson mixture (truncated/untruncated) models identified thresholds for frequent/high use in a 12-month period. Results: The two-component negative binomial mixture model resulted in the best model fit. Using negative binomial-derived thresholds, 5.3% of patients had a period of frequent use (admitted six or more times), 15.8% of high use (hospitalised for 45 or more days) and 3.5% of heavy use (both frequent and high use). The prevalence of specific mental health disorders (e.g. mood disorder and schizophrenia) among frequent and high use cohorts varied across thresholds. Conclusions: This model-driven approach can be applied to identify thresholds in other cohorts. Threshold choice may depend on the magnitude and focus of potential interventions.