Depression, especially when complicated by severe symptoms and chronicity, puts a great burden on patients, their relatives and society. Electroconvulsive therapy (ECT) is a safe and effective treatment for depressive episodes, even whenpsychotherapeutic and psychopharmacological interventions have failed. Despite its superior efficacy, use of ECT for depressed patients is surprisingly low in the Netherlands. Although treatment guidelines for depressive episodes advise the use of ECT in case of treatment resistance, in 2014 only 1.2% of chronic depressive patients treated in the specialized mental health system received ECT. This low application rate is possibly due to (1) limited knowledge on the optimal position of ECT in the treatment algorithms, (2) a lack of knowledge on cost-effectiveness, (3) fear for (cognitive) side-effects in patients, relatives and professionals, and the outdated representation of ECT in the media and society at large.
We will address these issues by
(1) analyzing aspects of (cost-) effectiveness of ECT,
(2) determining the most optimal position of ECT in the treatment algorithms for depressive episodes, and finally
(3) facilitating more up-to-date, transparent and objective information for Dutch patients, relatives and professionals regarding ECT.
To analyze (cost-) effectiveness of ECT in the Netherlands, we will make use of both a large database of merged clinical and research cohorts of ECT-patients (N=±1500) and an observational prospective cohort study investigating comparative (cost-)effectiveness of ECT and antidepressants (n=220). The archival cohort will be used to scrutinize for clinical variables predicting (cost-) effectiveness and estimates of total treatment costs by using linear and logistic regression analyses as well as modern multivariate machine learning methods. Such potential clinical predictors include gender, age, symptom severity, psychotic features, duration of current episode, and especially level of treatment resistance and the number of earlier treatment steps.
Specific attention will be devoted to cognitive outcome after ECT and its clinical predictors. To secure generalizability, ECT-patients from mental health facilities, general hospitals and academic medical centers will be entered in our database. This will provide us with more up-to-date information about the (cost-) effectiveness and (cognitive) side-effects of ECT in Dutch patients. In our search for the most optimal position of ECT during a depressed patient’s treatment journey, investigating the comparative (cost)-effectiveness with the most optimal antidepressant treatment is essential, and for this goal a prospective designed observational cohort study will be conducted. We will not only compare immediate outcomes on depression and cognitive functioning, and treatment costs in depressed patients treated with ECT versus antidepressant medication (both N=110), but also monitor adverse events such as relapse and side-effects during a follow-up period of one year. This will allow us to investigate whether the anticipated superior effects of ECT in the short term, also translate to sustained clinical benefits for patients. Propensity scores matching will be used to limit confounding by indication and regression analyses as well as modern multivariate machine learning methods will be used to explore predictors of (cost-) effectiveness. The central clinical endpoint for the cost-effectiveness analysis will be incremental costs per treatment responder. For the cost-utility analysis, a change in quality of life will be estimated by using repeated individual measures in the first year. This will provide us information from a (cost-) effectiveness perspective about the most optimal position of ECT in treatment algorithms.
To facilitate more up-to-date, transparent and objective information on ECT, together with patients, relatives and professionals, we will build an informative, needs-based (as verified by qualitative interviews), website on ECT with a personalized decision-making tool. Therewith, we also aim to reduce the existing stigma around ECT and to increase the (common) knowledge in patients, relatives and professionals about (cost-) effectiveness and the optimal position of ECT within the treatment algorithms. Our project will position ECT in the Dutch treatment algorithm for depression based on national scientific data, including facts on cost-effectiveness and needs of the patients in the decision-making process.