Evaluation of a Cross-sectional Coordinated, Severity Stepped, Evidence-based Care Model for Mental Disorders

Overview

This study evaluates a cross sectional, severity stepped, evidence-based care model for patients with mental disorders (RECOVER). RECOVER is a consortium of well-known institutions for the treatment and integrated care of patients with mental disorders, patient associations, relative associations, research institutions, health care insurances and authorities from the care region Hamburg, Germany. This project aims to evaluate the RECOVER care model with treatment as usual (TAU) regarding cost-effectiveness (costs, efficiency and cost utility) for patients with mental disorders. The following questions are examined: 1. Does RECOVER reduce psychiatric health care costs compared to TAU? 2. Does RECOVER improve patient relevant outcomes (i.e. symptom remission, response, daily functioning and quality of life)? 3. Is RECOVER cost effective compared to TAU? (from a payer's and societal perspective) A total sample of 890 patients with mental disorders will be assessed at baseline (before treatment) and randomized into the RECOVER care model or get TAU. Follow-up assessments are conducted after 6 month and 12 month. As primary outcomes, cost reduction, improvement in symptoms (i.e. amount of remission and response to treatment, daily functioning and quality of life) and cost-efficiency-ratios will be measured. In addition, several secondary outcome parameters will be assessed. Impact: The present randomized controlled trial (RCT) evaluates the cross-sectional, severity stepped, evidence-based approach of the RECOVER model in patients with mental disorders. With its focus on effectiveness and cost-effectiveness, the study aims to improve the health care system in Germany.

Participants will be recruited from regular care settings (in-patient and out-patient services, general practitioners, psychotherapists) and via the RECOVER homepage. Upon fulfillment of the inclusion criteria and after having obtained informed consent, participants will undergo a complex baseline psychiatric diagnostic assessment, including among other measures the global assessment of functioning (GAF), severity of illness (CGI-S) and specification of diagnosis (SCID I and SCID II). Based on these three instruments, participants will be divided into four degrees severity: Grade 1 = mild, Grade 2 = medium, Grade 3 = medium to high, Grade 4 = severe mental disorder. Accordingly, there will be four strata of similar sample sizes (planned n=268, including 30% drop out rate; see power analysis below). Each participant will then be randomized either to the RECOVER treatment condition or the treatment as usual (TAU) condition. Randomization will be conducted by an independent person not involved in the RCT or diagnostic assessment, who will receive the pseudonymised participant ID and stratum number. A previously with the STATA 14 program defined list will be used to achieve randomization. When the planned sample size per stratum is achieved, no further patients will be included in this stratum. For a complete list of measures, please refer to outcome measures section. In addition, secondary data will be obtained from external data owners, essential for the achievement of RECOVER's research objective - the determination of health costs. These include personal patient-related data such as data from health insurances companies (e.g. data from inpatient and outpatient medical services, rehabilitation services, transport, medical aid, drug/ medication data, home assistance and care services, work disability and sickness benefit/ allowance data). These will be inquired from the health insurance for the years 2016 to 2021 at the 12-month point in time and continuously assessed within the quality assurance study. Subsequently, a monetary valuation is carried out using standardized monetary valuation rates. Serious adverse events (SAE) will be documented from the first contact (i.e. registry) between patient and study staff and will be included in the participant's record. A copy of each SAE protocol will be directly forwarded to the study's central management. Each SAE is assessed in terms of its causal relationship between the event and the study procedures (""serious undesirable, study-related event"). For each SAE, the SAE protocol must be filled in (with pseudonymised data only) and will be immediately discussed with the study management, who will check the protocol for plausibility and completeness and evaluate the event. Events that have not yet been formally completed are tracked. If the undesired event has been resolved, a final documentation is provided on the SAE protocol. The executive committee is informed by the study management and asked for an assessment. If all assessments have shown that the suspected case is an SAE, all study staff will be informed by the study management immediately, but at the latest within 7 days of notification. The sample size is based on a power calculation to detect a statistically significant difference between the intervention (RECOVER) vs. standard care (TAU) in order to yield a small to medium standardized mean difference between the groups (Cohen's f of 0.175) after 12 months. At a power of at least 80% with a type 1 error rate of 5%, 2-sided testing and 10% of declared variance due to baseline, at least 233 study participants are required. For testing hypotheses involving the interaction of intervention and stratification subgroup, sample size increases to n=383. Diagnostics and therapy are carried out in approx. 50 clusters with approx. 21 participants each and an intraclass correlation (ICC) of .05 is assumed for the primary, continuous outcome. This results in a design effect of approximately 2.0 and a total sample size of 890 patients (including 30% dropout). With an estimated participation rate of 50%, 2140 patients must be addressed for participation. Statistical analysis will be supervised by the local Department of Medical Biometry and Epidemiology. The analysis of primary and secondary outcome data is performed according to the intention-to-treat (ITT) principle. Missing values for the follow-up time points will be accounted for within mixed linear and logistic regression models. For sensitivity analyses, missing values will be replaced by multiple imputation and per-protocol (PP) analyses. The analysis of therapy utilization and productivity losses is performed descriptively as well as with difference-in-difference regressions (to analyze the measured costs over time). In addition, multivariate analyses will be carried out. Remission and response data are analyzed using logistic regression, while remission (non-clinical, i.e., performance under critical cut-off) and response (i.e. reduction in symptom severity of 50%) are specifically determined for each psychiatric condition during follow-up as compared to the baseline measurement. Changes in symptoms, level of functioning and health associated quality of life are analyzed with difference-in-difference-regression. To estimate cost efficiency, incremental cost-efficiency-relation (ICER) is calculated. To estimate the ICER's uncertainty, cost-efficiency-acceptance-curves based on net-benefit-regressions are calculated. All secondary outcome parameters are descriptively investigated as well as using multivariate analyses (e.g. logistic regression, difference-in-difference-regression). To assess inhibiting and promoting factors for the RECOVER model, qualitative measures are applied. All study data are immediately entered into a database. To minimize input errors, all data are entered by two different staff members independently. During data entry, integrity checks are performed to minimize input errors. These tests are carried out on the basis of a data validation plan and are countersigned by the head of study and the study statistician. The data input system enables continuous quality control of the input process via integrated inspection functions. After completion of the data entry, the access rights to the database are cancelled and the database is exported to the data transformation system. There, final plausibility checks are carried out and the data are checked for consistency and completeness. Missing values and inconsistencies are reported back to the examiner and processed by the person responsible. As soon as all corrections have been completed, the database is closed and transferred to the study statistician. All data entries, modifications or deletions are logged. All data (i.e. completed questionnaires, database) will be protected against unauthorized access, i.e. by physical locking in steel cabinets or secured by a system of individual access authorizations. In accordance with the principles of good clinical practice, all study data and relevant correspondence are archived by the investigators. Once the study has been completed, the all archived data will be stored by the University of Hamburg in accordance with legal regulations. The lead investigator is responsible for storing and archiving the study data. Quality assurance will be achieved by evaluation and comparison of data assessed at baseline and at follow-up assessments after six month (t6) and after one year (t12). Data contains measures of disease symptoms and severity (e.g., HEALTH-49, CGI-S, PANSS, PHQ-9, GAD-7, PHQ-15, PID-5). The daily function level is measured with the GAF, and health-related quality of life is assessed with the EQ-5D-5L and the SF-12. Treatment satisfaction will also be measured. The therapeutic coherence is determined with regard to both drug and non-drug treatment. All therapeutic services will be continuously documented in terms of number, type and duration. Data collection and monitoring will be carried out by treatment-unrelated, independent researchers (Dept. of Health Economics and Healthcare Research, Dept. of Medical Psychology and the Dept. of Medical Biometry and Epidemiology, UKE). They will primarily monitor compliance with the principles of good clinical practice and the study protocol, as well as proper data collection and input. Data verification will mainly focus on key variables that are defined at the beginning of the study. Frequency and duration of monitor visits will depend on recruitment progress, protocol compliance and data quality. It will be the monitor's responsibility to regularly check data collection and input, monitor adherence to the study protocol, and check that data are complete, consistent and correct. The monitor should have access to all data sources that can be used to verify the questionnaire information. In addition, in accordance with the regulations governing the monitoring of clinical trials, it is necessary for the investigator to grant the monitor access to the proportion of all pseudonymised patient files directly associated with the trial. Study results as well as a detailed study protocol will be published in national and international peer-reviewed scientific journals. A publication agreement for the participating institutions will be achieved within a consortium agreement. All data, personal identification data and scientific data, will be stored in the UKE's Dept. of Health Economics and Healthcare Research and Dept. of Medical Psychology for 10 years. Consent declarations will be stored in the study center's paper archive until a legally compliant scan is implemented. At all other locations, data will only be stored temporarily for immediate data processing as proposed within the study framework.