Statistical methods and modelling techniques for analysing hospital readmission of discharged psychiatric patients: a systematic literature review

• Published in: BMC psychiatry 2016-11, Vol.16 (1), p.413-413, Article 413
• Main Authors: Urach, Christoph, Zauner, Günther, Wahlbeck, Kristian, Haaramo, Peija, Popper, Niki
• Format: Article
• Language: English
• Subjects: Admission and discharge; Analysis; Care and treatment; Hospitals; Humans; Male; Medical research; Medicine, Experimental; Mental Disorders - therapy; Patient Readmission - statistics & numerical data; Psychiatric patients; Psychiatry; Registries - statistics & numerical data; Systematic review
• ISSN: 1471-244X; 1471-244X
• DOI: 10.1186/s12888-016-1128-7

Psychiatric services have undergone profound changes over the last decades. CEPHOS-LINK is an EU-funded study project with the aim to compare readmission of patients discharged with psychiatric diagnoses using a registry-based observational record linkage study design and to analyse differences in the findings for five different countries. A range of different approaches is available for analysis of the available data. Although there are some studies that compare selected methods for evaluating questions on readmission, there are to our knowledge no published systematic literature reviews on commonly used methods and their comparison. This work shall therefore provide an overview of the methods in use, their evolution throughout history and new developments which can further improve the research quality in this area. Based on systematic literature reviews realized in the course of the CEPHOS-LINK study, this work is a systematic evaluation of mathematical (statistical and modelling) methods used in studies examining psychiatric readmission. The starting point were 502 papers, of which 407 were analysed in detail; Methods used were assigned to one of five categories with subcategories and analysed accordingly. Our particular interest next to survival analysis and regression models is modelling and simulation. As population sizes and follow-up times in the included studies varied widely, a range of methods was applied. Studies with bigger sample sizes conducted survival and regression analysis more often than studies with fewer patients did. These latter relied more on classical statistical tests (e.g. t-tests and Student Newman Keuls). Statistical strategies were often insufficiently described, posing a major problem for the evaluation. Almost all cases failed to provide and explanation of the rationale behind using certain methods. There is a discernible trend from classical parametric/nonparametric tests in older studies towards regression and survival analyses in more recent ones. Modelling and simulation were under-represented despite their high usability, as has been identified in other health applications and comparable research areas.