Efficacy of a digitally supported regional systems intervention for suicide prevention (SUPREMOCOL) in Noord-Brabant, the Netherlands.

OBJECTIVE: We evaluated the effect of a digitally supported systems intervention for suicide prevention (SUPREMOCOL) in Noord-Brabant, the Netherlands. METHOD: Non-randomized stepped wedge trial design (SWTD). Stepwise implementation in the five subregions of the systems intervention. Pre-post analysis for the whole province (Exact Rate Ratio Test, Poisson count). SWTD Hazard Ratios of suicides per person-years for subregional analysis of control versus intervention conditions over five times three months. Sensitivity analysis. RESULTS: Suicide rates dropped 17.8% (p = .013) from 14.4 suicides per 100,000 before the start of implementation of the systems intervention (2017), to 11.9 (2018) and 11.8 (2019) per 100, during implementation; a significant reduction (p = .043) compared to no changes in the rest of the Netherlands. Suicide rates dropped further by 21.5% (p = .002) to 11.3 suicides per 100,000 during sustained implementation in 2021. Sensitivity analysis confirmed the reduction (p = .02). The SWTD analysis over 15 months in 2018-2019 did not show a significant association of this reduction with implementation per subregional level, probably due to insufficient power given the short SWTD timeframe for implementation and low suicide rates per subregion. CONCLUSIONS: During the SUPREMOCOL systems intervention, over four years, there was a sustained and significant reduction of suicides in Noord-Brabant.

Measuring recovery in participants with a schizophrenia spectrum disorder: validation of the Individual Recovery Outcomes Counter (I.ROC).

BACKGROUND: To improve recovery in mental health, validated instruments are needed. AIMS: This study evaluates psychometric properties of the Individual Recovery Outcomes Counter (I.ROC) in a Dutch population of participants with a schizophrenia spectrum disorder (SSD). METHODS: 326 participants completed the I.ROC at baseline (n = 326), six months (n = 155) and twelve months (n = 84) as part of a routine outcome assessment. Reliability, validity, sensitivity to change, and internal factor structure were examined. RESULTS: Participants evaluated the I.ROC as comprehensive. Internal consistency of the I.ROC (α = 0.88) and test-retest reliability (r = .85, p < .001) are good. Negative moderate correlations with the total score of the PANSS (r=-.50, p < .001) and the HoNOS (r=-.52, p < .001) were found, and a small negative correlation with the FR tool (r=-.36, p < .001). Moderate positive correlation with the MANSA (r = .55, p < .001) and the RAS (r = .60, p < .001) were found. The mean total I.ROC scores increased significantly between time points (F(2,166) = 6.351, p < .005), although differences were small. Confirmatory factor analysis showed that fit indices for the one-, two-, and four-factor model are comparable. CONCLUSIONS: The I.ROC is a valid and reliable instrument, with sensitivity to change, to map recovery in participants with SSD.

The use of PROMs and shared decision-making in medical encounters with patients: An opportunity to deliver value-based health care to patients.

BACKGROUND: The recent emphasis on value-based health care (VBHC) is thought to provide new opportunities for shared decision-making (SDM) in the Netherlands, especially when using patient-reported outcome measures (PROMs) in routine medical encounters. It is still largely unclear about how PROMs could be linked to SDM and what we expect from clinicians in this respect. AIM: To describe approaches and lessons learned in the fields of SDM and VBHC implementation that converge in using PROMs in medical encounters. APPROACH: Based on input from three Dutch forerunner case examples and available evidence about SDM and VBHC, we describe barriers and facilitators regarding the use of PROMs and SDM in the medical encounter. Barriers and facilitators were structured according to a conversational model that included monitoring and managing, team talk, option talk, choice talk, and decision talk. Key lessons learned and recommendations were synthesized. RESULTS: The use of individual, N = 1 PROMs scores in the medical encounter has been largely achieved in the forerunner projects. Conversation on monitoring and managing is relatively well implemented, and option talk to some extent, unlike team talk, and decision talk. Aggregated PROMs information describing outcomes of treatment options seemed to be scarcely used. Experienced barriers largely corresponded to what is known from the literature, eg, perceived lack of time and lack of tools summarizing the options. Some concerns were identified about increasing health care consumption as a result of using PROMs and SDM in the medical encounter. CONCLUSION: Successful implementation of SDM within VBHC initiatives may not be self-evident, even though individual, N = 1 PROMs scores are being used in the medical encounter. Education and staff resources on meso and macro levels may facilitate the more time-consuming SDM aspects. It seems fruitful to especially target team talk and choice talk in redesigning clinical pathways.

Shared decision-making in mental health care using routine outcome monitoring: results of a cluster randomised-controlled trial.

PURPOSE: To investigate the effects of Shared Decision-Making (SDM) using Routine Outcome Monitoring (ROM) primary on patients' perception of Decisional Conflict (DC), which measures patients' engagement in and satisfaction with clinical decisions, and secondary on working alliance and treatment outcomes. METHOD: Multi-centre two-arm matched-paired cluster randomised-controlled trial in Dutch specialist mental health care. SDM using ROM (SDMR) was compared with Decision-Making As Usual (DMAU). Outcomes were measured at baseline (T0) and 6 months (T1). Multilevel regression and intention-to-treat analyses were used. Post hoc analyses were performed on influence of subgroups and application of SDMR on DC. RESULTS: Seven teams were randomised to each arm. T0 was completed by 186 patients (51% intervention; 49% control) and T1 by 158 patients (51% intervention, 49% control). DC, working alliance, and treatment outcomes reported by patients did not differ significantly between two arms. Post hoc analyses revealed that SDMR led to less DC among depressed patients (p = 0.047, d =- 0.69). If SDMR was applied well, patients reported less DC (SDM: p = 0.000, d = - 0.45; ROM: p = 0.021, d = - 0.32), which was associated with better treatment outcomes. CONCLUSION: Except for patients with mood disorders, we found no difference between the arms for patient-reported DC. This might be explained by the less than optimal uptake of this generic intervention, which did not support patients directly. Regarding the positive influence of a higher level of applying SDM and ROM on less DC and better treatment outcomes, the results are encouraging for further investments in patient-oriented development and implementation of SDMR.

Decisional conflict in mental health care: a cross-sectional study.

PURPOSE: Decisional conflict refers to the degree to which patients are engaged in and feel comfortable about important clinical decisions. Until now, the concept has received little attention in mental health care. We investigate the level of decisional conflict in mental health care and whether this is influenced by socio-demographics, treatment setting, diagnoses, and locus of control. METHODS: Cross-sectional study among 186 patients in Dutch specialist mental health care using the Decisional Conflict Scale, which measures five dimensions of decisional conflict: information, support, clarification of values, certainty, and decisional quality. Descriptive statistics and forward stepwise linear regression analyses were used. RESULTS: Patients report relatively high levels of decisional conflict, especially those with more external locus of control. Having a personality disorder and higher education also increases decisional conflict on the dimensions support and clarification of values, respectively. Less decisional conflict was experienced by patients with psychotic disorders on the dimension certainty and by women on the information domain. CONCLUSIONS: Decisional conflict is common among patients in specialist mental health care and is very useful for assessing the quality of clinical decision making. Measuring decisional conflict and knowledge about influencing factors can be used to improve patients' participation in clinical decision making, adherence to treatment and clinical outcomes.

A National Quality Improvement Collaborative for the clinical use of outcome measurement in specialised mental healthcare: results from a parallel group design and a nested cluster randomised controlled trial.

BACKGROUND: Although the importance and advantages of measurement-based care in mental healthcare are well established, implementation in daily practice is complex and far from optimal. AIMS: To accelerate the implementation of outcome measurement in routine clinical practice, a government-sponsored National Quality Improvement Collaborative was initiated in Dutch-specialised mental healthcare. METHOD: To investigate the effects of this initiative, we combined a matched-pair parallel group design (21 teams) with a cluster randomised controlled trial (RCT) (6 teams). At the beginning and end, the primary outcome 'actual use and perceived clinical utility of outcome measurement' was assessed. RESULTS: In both designs, intervention teams demonstrated a significant higher level of implementation of outcome measurement than control teams. Overall effects were large (parallel group d=0.99; RCT d=1.25). CONCLUSIONS: The National Collaborative successfully improved the use of outcome measurement in routine clinical practice. DECLARATION OF INTEREST: None. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

A digital intake approach in specialized mental health care: study protocol of a cluster randomised controlled trial.

BACKGROUND: Enhancing patient participation is becoming increasingly important in mental health care as patients use to have a dependent, inactive role and nonadherence to treatment is a regular problem. Research shows promising results of initiatives stimulating patient participation in partnership with their clinicians. However, few initiatives targeting both patients' and clinicians' behaviour have been evaluated in randomised trials (RCT). Therefore, in GGz Breburg, a specialized mental health institution, a digital intake approach was developed aimed at exploring treatment needs, expectations and preferences of patients intended to prepare patients for the intake consultations. Subsequently, patients and clinicians discuss this information during intake consultations and make shared decisions about options in treatment. The aim of this trial is to test the efficacy of this new digital intake approach facilitated by Routine Outcome Monitoring (ROM), peer support and training of clinicians as compared to the intake as usual. The primary outcome is decisional conflict about choices in treatment. Secondary outcomes focus on patient participation, shared decision making, working alliance, adherence to treatment and clinical outcomes. METHODS: This article presents the study protocol of a cluster-randomised controlled trial in four outpatient departments for adults with depression, anxiety and personality disorders, working in two different regions. Randomisation is done between two similar intake-teams within each department. In the four intervention teams the new intake approach is implemented. The four control teams apply the intake as usual and will implement the new approach after the completion of the study. In total 176 patients are projected to participate in the study. Data collection will be at baseline, and at two weeks and two months after the intake. DISCUSSION: This study will potentially demonstrate the efficacy of the new digital intake approach in mental health care in terms of the primary outcome the degree of decisional conflict about choices in treatment. The findings of this study may contribute to the roll out of such eHealth initiatives fostering patient involvement in decision making about their treatment. TRIAL REGISTRATION: Trial registration: Dutch Trial Register NTR5677 . Registered 17th January 2016.

Shared Decision Making in mental health care using Routine Outcome Monitoring as a source of information: a cluster randomised controlled trial.

BACKGROUND: Shared Decision Making (SDM) is a way to empower patients when decisions are made about treatment. In order to be effective agents in this process, patients need access to information of good quality. Routine Outcome Monitoring (ROM) may provide such information and therefore may be a key element in SDM. This trial tests the effectiveness of SDM using ROM, primarily aiming to diminish decisional conflict of the patient while making decisions about treatment. The degree of decisional conflict, the primary outcome of this study, encompasses personal certainty about choosing an appropriate treatment, information about options, clarification of patient values, support from others and patients experience of an effective decision making process. Secondary outcomes of the study focus on the working alliance between patient and clinician, adherence to treatment, and clinical outcome and quality of life. METHODS/DESIGN: This article presents the study protocol of a multi-centre two-arm cluster randomised controlled trial (RCT). The research is conducted in Dutch specialised mental health care teams participating in the ROM Quality Improvement Collaborative (QIC), which aims to implement ROM in daily clinical practice. In the intervention teams, ROM is used as a source of information during the SDM process between the patient and clinician. Control teams receive no specific SDM or ROM instructions and apply decision making as usual. Randomisation is conducted at the level of the participating teams within the mental health organisations. A total of 12 teams from 4 organisations and 364 patients participate in the study. Prior to data collection, the intervention teams are trained to use ROM during the SDM process. Data collection will be at baseline, and at 3 and 6 months after inclusion of the patient. Control teams will implement the SDM and ROM model after completion of the study. DISCUSSION: This study will provide useful information about the effectiveness of ROM within a SDM framework. Furthermore, with practical guidelines this study may contribute to the implementation of SDM using ROM in mental health care. Reporting of the results is expected from December 2016 onwards. TRIAL REGISTRATION: Dutch trial register: TC5262. Trial registration date: 24th of June 2015.