Long-term outcomes in patients with severe depression after in-hospital treatment - study protocol of the depression long-term Augsburg (DELTA) study.

INTRODUCTION: Depressive disorders are very common diseases entailing a great burden on affected people. However, comprehensive information on long-term disease course in patients with severe depression is lacking so far. The objectives of the DELTA study are to examine long-term outcomes and their predicting factors, to assess clinical response of antidepressant pharmacotherapy by applying therapeutic drug monitoring, to identify predictors of therapeutic non-response, to describe the long-term healthcare utilisation and to investigate the role of biomarkers in disease course. METHODS AND ANALYSIS: A cohort study including all adult hospitalised cases (age range 18 to 75 years) of severe major depression who are admitted to the Bezirkskrankenhaus Augsburg is established. It is planned to include 300 patients. During the hospital stay, information is gathered through personal interview, self-administered questionnaires, cognitive tests and chart review. Furthermore, biomaterials are collected. After hospital discharge, patients are repeatedly re-examined over time (3, 6, 12, 24 and 36 months) to collect information about mortality, relapse, depression severity, health-related quality of life (HRQOL), perceived stigma, cognitive functions, diet, physical activity, treatment and healthcare utilisation. Follow-up blood samples are collected to determine therapeutic drug levels. The primary study aim is to investigate long-term therapeutic response, survival, relapse, HRQOL and cognitive functions. Survival time and time to relapse or re-hospitalisation will be analysed using Cox regression models. Changes of HRQOL, depressive symptoms and cognitive functions over time will be examined using generalised linear regression models for repeated measures or mixed models. Correlates of the disease course will be modelled using suitable generalised linear, mixed, estimating equation and growth curve models. ETHICS AND DISSEMINATION: The study protocol was approved by the Ethics Committee of the Ludwig-Maximilians-Universität München (date of approval: 23 October 2017, reference number: 17-625). Study results will be presented at scientific conferences and published in peer-reviewed scientific journals.

[Quality Indicators for Integrated Care in Patients with Schizophrenia - Results from a Feasibility Study]. / Qualitätsindikatoren für die Behandlung von Menschen mit Schizophrenie ­ Ergebnisse einer Anwendungsstudie.

Objective The study aimed to evaluate the applicability of a set of quality indicators to assess models of integrated care for patients with a diagnosis of schizophrenia. We report first values for these indicators in routine care in Germany. Methods The study is based on a cohort of adult patients with schizophrenia insured by one large German statutory health insurance company, which were assessed two times and gave consent to evaluate their routine claims data. The study tried to use 12 basic and 22 quality indicators from claims data. Results It was possible to estimate most structural indicators using available data, but only half of the quality indicators. This means that while assessment of quality indicators is feasible in general, routine claims data needs to be supplemented by additional (primary) data. Four of the calculated quality indicators had clear targets or red-flag values, which were not met in our cohort in all four indicators. None of the patients had an outpatient mental health related contact within one week (target > 90 %). The readmission rate within 30 days (21 %) was twice as high as the proposed red-flag value of 10 %. Similar figures were seen for antipsychotic polypharmacy (25 %, red-flag value > 10 %) and the proportion of patients with compulsory treatment (15 %) exceeded the red-flag value by 5 %. Conclusion The study shows that it is possible to measure quality indicators, but also demonstrates considerable limitations. There is a need to validate indicators in routine care.