@article{ref1,
title="The burden associated with, and management of, difficult-to-treat depression in patients under specialist psychiatric care in the United Kingdom",
journal="Journal of psychopharmacology",
year="2022",
author="Roque, Gloria and Franarin, Tarso and Fell, Benjamin and McAllister-Williams, R. Hamish and Zhang, Xinyue and Wei, Yiran and Engelthaler, Tomas and Menzat, Bayar and Costa, Tiago",
volume="36",
number="5",
pages="545-556",
abstract="BACKGROUND: Major depressive disorder (MDD) is common and often has sub-optimal response to treatment. Difficult-to-treat depression (DTD) is a new concept that describes 'depression that continues to cause significant burden despite usual treatment efforts'. AIMS: To identify patients with likely DTD in UK secondary care and examine demographic, disease and treatment data as compared with 'non-DTD' MDD patients. <br><br>METHODS: Anonymised electronic health records (EHRs) of five specialist mental health National Health Service (NHS) Trusts in the United Kingdom were analysed using a natural language processing model. Data on disease characteristics, comorbidities and treatment histories were extracted from structured fields and using natural language algorithms from unstructured fields. Patients with MDD aged ⩾18 years were included in the analysis; those with presumed DTD were identified on the basis of MDD history (duration and recurrence) and number of treatments prescribed. <br><br>RESULTS: In a sample of 28,184 patients with MDD, 19% met criteria for DTD. Compared to the non-DTD group, patients with DTD were more likely to have severe depression, suicidal ideation, and comorbid psychiatric and/or physical illness, as well as higher rates of hospitalisation. They were also more likely to be in receipt of unemployment and sickness/disability benefits. More intensive treatment strategies were used in the DTD group, including higher rates of combination therapy, augmentation, psychotherapy and electroconvulsive therapy. <br><br>CONCLUSION: This study demonstrates the feasibility of identifying patients with probable DTD from EHRs and highlights the increased burden associated with MDD in these patients.<p /><p>Language: en</p>",
language="en",
issn="0269-8811",
doi="10.1177/02698811221090628",
url="http://dx.doi.org/10.1177/02698811221090628"
}