LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Application of mixture distributions for identifying thresholds of frequent and high inpatient mental health service use in longitudinal data.

Photo from wikipedia

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… Click to show full 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.

Keywords: use; high use; inpatient mental; frequent high; mental health

Journal Title: Journal of mental health
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.