Identification of the delivery of cognitive behavioural therapy for psychosis (CBTp) using a cross-sectional sample from electronic health records and open-text information in a large UK-based mental health case register

Abstract

ObjectiveOur primary objective was to identify cognitive behavioural therapy (CBT) delivery for people with psychosis (CBTp) using an automated method in a large electronic health record database. We also examined what proportion of service users with a diagnosis of psychosis were recorded as having received CBTp within their episode of care during defined time periods provided by early intervention or promoting recovery community services for people with psychosis, compared with published audits and whether demographic characteristics differentially predicted the receipt of CBTp.MethodsBoth free text using natural language processing (NLP) techniques and structured methods of identifying CBTp were combined and evaluated for positive predictive value (PPV) and sensitivity. Using inclusion criteria from two published audits, we identified anonymised cross-sectional samples of 2579 and 2308 service users respectively with a case note diagnosis of schizophrenia or psychosis for further analysis.ResultsThe method achieved PPV of 95% and sensitivity of 96%. Using the National Audit of Schizophrenia 2 criteria, 34.6% service users were identified as ever having received at least one session and 26.4% at least two sessions of CBTp; these are higher percentages than previously reported by manual audit of a sample from the same trust that returned 20.0%. In the fully adjusted analysis, CBTp receipt was significantly (p<0.05) more likely in younger patients, in white and other when compared with black ethnic groups and patients with a diagnosis of other schizophrenia spectrum and schizoaffective disorder when compared with schizophrenia.ConclusionsThe methods presented here provided a potential method for evaluating delivery of CBTp on a large scale, providing more scope for routine monitoring, cross-site comparisons and the promotion of equitable access.

Use of Natural Language Processing to identify Obsessive Compulsive Symptoms in patients with schizophrenia, schizoaffective disorder or bipolar disorder

“…However, NLP or other algorithms have been used to extract other types of information from clinical records. Examples of this are applications to find the presence of cognitive behavioural therapy (CBT) delivery 17 , adverse drug effects (ADR) 18 and antipsychotic polypharmacy data 13 .…”

How Inclusive, User-Centered Design Research Can Improve Psychological Therapies for Psychosis: Development of SlowMo

“…For example, interventions for sleep, worry, self-esteem and reasoning styles have demonstrated larger effect sizes on paranoia compared to generic CBT for psychosis [13][14][15]. However, there is continuing concern about barriers to therapy access, uptake and adherence [5,12,16] and strategies for improving implementation are urgently needed.…”

“…Effect sizes are in the small to medium range, and psychological interventions are only accessed by 15-30% of eligible service users [4][5][6][7][8]. Some people are not motivated to try therapy, and those that do may struggle to understand it and to apply new insights to everyday situations [9][10][11].…”

‘Real time’ monitoring of antipsychotic prescribing in patients with dementia: a study using the Clinical Record Interactive Search (CRIS) platform to enhance safer prescribing

“…One approach is therefore to derive data from these text fields using NLP and thus enhance the structure of the record and information available. This has been demonstrated to be achievable in the mental health record through a range of research applications, particularly using the CRIS data resource at SLaM13–19 and creates opportunities for algorithms to improve clinical quality such as enhancing prescribing practice as described here.…”