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      Using daily monitoring of psychiatric symptoms to evaluate hospital length of stay

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      , ,
      BJPsych Open
      The Royal College of Psychiatrists

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          Abstract

          Background

          Routine symptom monitoring and feedback improves out-patient outcomes, but the feasibility of its use to inform decisions about discharge from in-patient care has not been explored.

          Aims

          To examine the potential value to clinical decision-making of monitoring symptoms during psychiatric in-patient hospitalisation.

          Method

          A total of 1102 in-patients in a private psychiatric hospital, primarily with affective and neurotic disorders, rated daily distress levels throughout their hospital stay. The trajectories of patients who had, and had not, met a criterion of clinically significant improvement were examined.

          Results

          Two-thirds of patients ( n=604) met the clinically significant improvement criterion at discharge, and three-quarters ( n=867) met the criterion earlier during their hospital stay. After meeting the criterion, the majority (73.2%) showed stable symptoms across the remainder of their hospital stay, and both classes showed substantially lower symptoms than at admission.

          Conclusions

          Monitoring of progress towards this criterion provides additional information regarding significant treatment response that could inform clinical decisions around discharge readiness.

          Declaration of interest

          None.

          Copyright and usage

          © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

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          Most cited references14

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          Patient-focused research: using patient outcome data to enhance treatment effects.

          A program of research aimed at improving the quality of psychological interventions is described. Data from over 10,000 patients were analyzed to understand the association between number of treatment sessions and clinically significant improvement. In addition to a potential dose-response relationship, typical recovery curves were generated for patients at varying levels of disturbance and were used to identify patients whose progress was less than expected ("signal" cases). The consequences of passing this information along to therapists were reported. Analyses of dose-response data showed that 50% of patients required 21 sessions of treatment before they met criteria for clinically significant improvement. Seventy-five percent of patients were predicted to improve only after receiving more than 40 treatment sessions in conjunction with other routine contacts, including medication in some cases. Identification of signal cases (potential treatment failures) shows promise as a decision support tool, although further research is needed to elucidate the nature of helpful feedback. Outgrowths of this research include its possible contribution to social policy decisions, reductions in the need for case management, use in supervision, and possible effects on theories of change.
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            New approaches to studying problem behaviors: a comparison of methods for modeling longitudinal, categorical adolescent drinking data.

            Analyzing problem-behavior trajectories can be difficult. The data are generally categorical and often quite skewed, violating distributional assumptions of standard normal-theory statistical models. In this article, the authors present several currently available modeling options, all of which make appropriate distributional assumptions for the observed categorical data. Three are based on the generalized linear model: a hierarchical generalized linear model, a growth mixture model, and a latent class growth analysis. They also describe a longitudinal latent class analysis, which requires fewer assumptions than the first 3. Finally, they illustrate all of the models using actual longitudinal adolescent alcohol-use data. They guide the reader through the model-selection process, comparing the results in terms of convergence properties, fit and residuals, parsimony, and interpretability. Advances in computing and statistical software have made the tools for these types of analyses readily accessible to most researchers. Using appropriate models for categorical data will lead to more accurate and reliable results, and their application in real data settings could contribute to substantive advancements in the field of development and the science of prevention. Copyright 2009 APA, all rights reserved
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              Progress monitoring and feedback in psychiatric care reduces depressive symptoms.

              To date, the monitoring of patient progress using standardized assessments has been neglected in hospital-based psychiatric care. Findings in outpatient psychotherapy have demonstrated clinically significant benefits for providing feedback to the sizeable minority of patients who were otherwise unlikely to experience positive outcome (Lambert, 2007). However, a similar system for presenting feedback on patient progress has not yet been assessed for group therapy within psychiatric inpatient settings. The current study aimed to develop and evaluate the effectiveness of a feedback system suitable for use in psychiatric services.
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                Author and article information

                Journal
                BJPsych Open
                BJPsych Open
                bjporcpsych
                bjporcpsych
                BJPsych Open
                The Royal College of Psychiatrists
                2056-4724
                1 November 2016
                November 2016
                : 2
                : 6
                : 341-345
                Affiliations
                [1] Andrew C. Page, PhD, School of Psychology, The University of Western Australia, Crawley, Australia
                [2] Nadia K. Cunningham, PhD, School of Psychology, The University of Western Australia, Crawley, Australia
                [3] Geoffrey R. Hooke, BAppSci, Perth Clinic, West Perth, Western Australia; School of Psychology, The University of Western Australia, Crawley, Australia
                Author notes
                Correspondence: Andrew C. Page, School of Psychology, The University of Western Australia, 35 Stirling Highway, Crawley 6009, Australia. Email: andrew.page@ 123456uwa.edu.au
                Article
                bjporcpsych003814
                10.1192/bjpo.bp.116.003814
                5100604
                1134489a-29f1-4aaf-91ea-4c55c0ef93cb
                © 2016 The Royal College of Psychiatrists

                This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 25 August 2016
                : 25 August 2016
                : 30 September 2016
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