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      Trajectories of patients with severe mental illness in two-year contact with Flexible Assertive Community Treatment teams using Routine Outcome Monitoring data: An observational study

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          Abstract

          Objective

          Using outcome data collected routinely over a continuous two-year treatment period, we wished to distinguish homogeneous subgroups of patients with a severe mental illness whose psychosocial problems followed a similar pattern over time. By identifying the effectiveness of health services for different patient groups, this approach allowed us to identify patients at risk of deterioration and those recovering from their symptoms.

          Methods

          In total we included 2,660 patients who were in two-year continuous contact with a Flexible Assertive Community Treatment team (FACT). We collected outcome data on psychosocial functioning, needs for care and quality of life. We performed a latent class growth analysis (LCGA).

          Results

          The LCGA identified six homogenous patient subgroups using trajectories of HoNOS scores. On the basis of the patterns of patients’ psychosocial problems over time, we labelled these as follows: 1) stable at a low problem-severity level (N = 709; 27%); 2) stable at a low medium problem-severity level (N = 1,208; 45%); 3) stable at a high medium problem-severity level (N = 528; 20%); 4) stable at a high problem-severity level (N = 116; 4%); 5) amelioration of problems (N = 42; 2%); and 6) deterioration of problems (N = 57; 2%). Patients with stable and a high severity of psychosocial problems had more practical and somatic unmet needs than those in other subgroups, and also had the fewest decrease in the number of unmet needs.

          Discussion

          After linking patient subgroups with clinical features such as the need for care, we found that, over two years, most patients remained relatively stable in terms of psychosocial functioning, but that their unmet needs decreased over time. However, in terms of needs for treatment during two years of contact with a FACT team, patients in the subgroup with a stable and high problem-severity level tended to derive little or no benefit.

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          Most cited references36

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          Missing data: our view of the state of the art.

          Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, discourage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayesian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art.
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            Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic.

            A scaled difference test statistic [Formula: see text] that can be computed from standard software of structural equation models (SEM) by hand calculations was proposed in Satorra and Bentler (2001). The statistic [Formula: see text] is asymptotically equivalent to the scaled difference test statistic T̄(d) introduced in Satorra (2000), which requires more involved computations beyond standard output of SEM software. The test statistic [Formula: see text] has been widely used in practice, but in some applications it is negative due to negativity of its associated scaling correction. Using the implicit function theorem, this note develops an improved scaling correction leading to a new scaled difference statistic T̄(d) that avoids negative chi-square values.
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              Health of the Nation Outcome Scales (HoNOS). Research and development.

              An instrument was required to quantify and thus potentially measure progress towards a Health of the Nation target, set by the Department of Health, "to improve significantly the health and social functioning of mentally ill people". A first draft was created in consultation with experts and on the basis of literature review. This version was improved during four stages of testing: two preliminary stages, a large field trial involving 2706 patients (rated by 492 clinicians) and tests of the final Health of the Nation Outcome Scales (HoNOS), which included an independent study (n = 197) of reliability and relationship to other instruments. The resulting 12-item instrument is simple to use, covers clinical problems and social functioning with reasonable adequacy, has been generally acceptable to clinicians who have used it, is sensitive to change or the lack of it, showed good reliability in independent trials and compared reasonably well with equivalent items in the Brief Psychiatric Rating Scales and Role Functioning Scales. The key test for HoNOS is that clinicians should want to use it for their own purposes. In general, it has passed that test. A further possibility, that HoNOS data collected routinely as part of a minimum data set, for example for the Care Programme Approach, could also be useful in anonymized and aggregated form for public health purposes, is therefore testable but has not yet been tested.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Role: ConceptualizationRole: Writing – original draft
                Role: Writing – original draft
                Role: SupervisionRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                9 January 2019
                2019
                : 14
                : 1
                : e0207680
                Affiliations
                [1 ] Parnassia Group, Bavo-Europoort Mental Healthcare Organization, TA Rotterdam, The Netherlands
                [2 ] GGZ Delfland Mental Healthcare Organization, PL, Spijkenisse, The Netherlands
                [3 ] Parnassia Group, Dijk en Duin Mental Health Centre, AH Castricum, The Netherlands
                [4 ] Tilburg University, Department of Social and Behavioural Sciences, Tranzo Scientific Centre for Care and Welfare, LE Tilburg, The Netherlands
                [5 ] Phrenos Centre of Expertise, BE Utrecht, The Netherlands
                [6 ] ESPRI Epidemiological and Social Psychiatric Research Institute, Department of Psychiatry, Erasmus Medical Center, CA Rotterdam, The Netherlands
                Simon Fraser University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6028-7002
                Article
                PONE-D-18-12464
                10.1371/journal.pone.0207680
                6326457
                30625133
                f531b0ef-3ad3-42dd-afcd-78613ab77403
                © 2019 Kortrijk et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 May 2018
                : 5 November 2018
                Page count
                Figures: 1, Tables: 3, Pages: 16
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Health Care
                Psychological and Psychosocial Issues
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Personality Disorders
                Medicine and Health Sciences
                Health Care
                Quality of Life
                Medicine and Health Sciences
                Health Care
                Patients
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Neuropsychiatric Disorders
                Anxiety Disorders
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Neuroses
                Anxiety Disorders
                Engineering and Technology
                Equipment
                Communication Equipment
                Telephones
                Physical Sciences
                Chemistry
                Chemical Compounds
                Organic Compounds
                Alcohols
                Physical Sciences
                Chemistry
                Organic Chemistry
                Organic Compounds
                Alcohols
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Custom metadata
                Data are stored at the institutional database of the Erasmus Medical Centre in Rotterdam, The Netherlands. The datasets on which the analyses are based are available on request to the Local Ethics Committee of the Erasmus Medical Centre in Rotterdam, due to ethical restrictions and patient confidentiality requirements. To request the data, please contact: Dr Astrid Kamperman: a.kamperman@ 123456erasmusmc.nl of Dr Joke Tulen: j.h.m.tulen@ 123456erasmusmc.nl .

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