Environmental changes can be positive in mental illness. Systematic, planned and guided environmental change in all its aspects is called nidotherapy. It has shown some benefit but has not been extended to whole communities.

A cluster-randomised step-wedge trial is planned in six village communities in Nottinghamshire, England, covering an adult population of 400.

Adults in six villages will be offered a full personal environmental assessment followed by agreed change in different 3-month periods over the course of 1 year. All six villages have populations between 51 and 100 residents and are similar demographically. Assessments of mental health, personality status, social function, quality of life and environment satisfaction will be made. After the initial baseline period of 3 months, two villages will be randomised to nidotherapy for 3 months, a further two at 6 months and the last two at 9 months.

The primary outcome will be change in social function; secondary outcomes include health-related quality of life, anxiety and depressive symptoms, personality status, costs of nidotherapy and life satisfaction. Adverse events will also be recorded. The analysis will be carried out using a multimodal statistical approach examining (a) the change in scores of the primary outcome (social function); (b) change in scores of all secondary outcomes, including costs; and (c) changes in environmental satisfaction.

The findings of this study should help to determine whether nidotherapy has a place in the early detection and treatment of mental pathology.

Adaptive radiotherapy (ART) is commonly used to mitigate effects of anatomical change during head and neck (H&N) radiotherapy. The process of identifying patients for ART can be subjective and resource-intensive. This feasibility project aims to design and validate a pipeline to automate the process and use it to assess the current clinical pathway for H&N treatments.

The pipeline analysed patients’ on-set cone-beam CT (CBCT) scans to identify inter-fractional anatomical changes. CBCTs were converted into synthetic CTs, contours were automatically generated, and the original plan was recomputed. Each synthetic CT was evaluated against a set of dosimetric goals, with failed goals causing an ART recommendation.

To validate pipeline performance, a ‘gold standard’ was synthesised by recomputing patients’ original plans on a rescan-CT acquired during treatment and identifying failed clinical goals. The pipeline sensitivity and specificity compared to this ‘gold standard’ were calculated for 12 ART patients. The pipeline was then run on a cohort of 12 ART and 14 non-ART patients, and its sensitivity and specificity were instead calculated against the clinical decision made.

The pipeline showed good agreement with the synthesised ‘gold standard’ with an optimum sensitivity of 0·83 and specificity of 0·67. When run over a cohort containing both ART and non-ART patients and assessed against the subjective clinical decision made, the pipeline showed no predictive power (sensitivity: 0·58, specificity: 0·47).

Good agreement with the ‘gold standard’ gives confidence in pipeline performance and disagreement with clinical decisions implies implementation could help standardise the current clinical pathway.

To better understand clinicians’ rationale for ordering testing for C. difficile infection (CDI) for patients receiving laxatives and the impact of the implementation of a clinical decision support (CDS) intervention.

A mixed-methods, case series was performed from March 2, 2017 to December 31, 2018.

Yale New Haven Hospital, a 1,541 bed tertiary academic medical center.

Hospitalized patients ≥ 18 years old, and clinicians who were alerted by the CDS.

CDS was triggered in real-time when a clinician sought to order testing for CDI for a patient who received one or more doses of laxatives within the preceding 24 hours.

A total of 3,376 CDS alerts were triggered during the 21-month study period from 2,567 unique clinician interactions. Clinicians bypassed the CDS alert 74.5% of the time, more frequent among residents (48.3% bypass vs. 39.9% accept) and advanced practice providers (APPs) (34.9% bypass vs. 30.6% accept) than attendings (11.3% bypass vs. 22.5% accept). Ordering clinicians noted increased stool frequency/output (48%), current antibiotic exposure (34%), and instructions by an attending physician to test (28%) were among the most common reasons for overriding the alert and proceeding with testing for CDI.

Testing for CDI despite patient laxative use was associated with an increased clinician concern for CDI, patient risk for CDI, and attending physician instruction for testing. Attendings frequently accepted CDS guidance while residents and APPs often reinstated CDI test orders, suggesting a need for greater empowerment and discretion when ordering tests.

Data from an RCT of IAPT Norway (“Prompt Mental Health Care” [PMHC]) were linked to several administrative registers up to five years following the intervention. The aims were to (1) examine the effects of PMHC compared to treatment-as-usual (TAU) on work-related outcomes and health care use, (2) estimate the cost–benefit of PMHC, and (3) examine whether clinical outcomes at six-month follow-up explained the effects of PMHC on work−/cost–benefit-related outcomes.

RCTs with parallel assignment were conducted at two PMHC sites (N = 738) during 2016/2017. Eligible participants were considered for admission due to anxiety and/or depression. We used Bayesian estimation with 90% credibility intervals (CI) and posterior probabilities (PP) of effects in favor of PMHC. Primary outcome years were 2018–2022. The cost–benefit analysis estimated the overall economic gain expressed in terms of a benefit–cost ratio and the differences in overall public sector spending.

The PMHC group was more likely than the TAU group to be in regular work without receiving welfare benefits in 2019–2022 (1.27 ≤ OR ≤ 1.43). Some evidence was found that the PMHC group spent less on health care. The benefit–cost ratio in terms of economic gain relative to intervention costs was estimated at 5.26 (90%CI $ - $1.28, 11.8). The PP of PMHC being cost-beneficial for the economy as a whole was 85.9%. The estimated difference in public sector spending was small. PMHC effects on work participation and cost–benefit were largely explained by PMHC effects on mental health.

The results support the societal economic benefit of investing in IAPT-like services.

Contemporary data relating to antipsychotic prescribing in UK primary care for patients diagnosed with severe mental illness (SMI) are lacking.

To describe contemporary patterns of antipsychotic prescribing in UK primary care for patients diagnosed with SMI.

Cohort study of patients with an SMI diagnosis (i.e. schizophrenia, bipolar disorder, other non-organic psychoses) first recorded in primary care between 2000 and 2017 derived from Clinical Practice Research Datalink. Patients were considered exposed to antipsychotics if prescribed at least one antipsychotic in primary care between 2000 and 2019. We compared characteristics of patients prescribed and not prescribed antipsychotics; calculated annual prevalence rates for antipsychotic prescribing; and computed average daily antipsychotic doses stratified by patient characteristics.

Of 309 378 patients first diagnosed with an SMI in primary care between 2000 and 2017, 212,618 (68.7%) were prescribed an antipsychotic between 2000 and 2019. Antipsychotic prescribing prevalence was 426 (95% CI, 420–433) per 1000 patients in the year 2000, reaching a peak of 550 (547–553) in 2016, decreasing to 470 (468–473) in 2019. The proportion prescribed antipsychotics was higher among patients diagnosed with schizophrenia (81.0%) than with bipolar disorder (64.6%) and other non-organic psychoses (65.7%). Olanzapine, quetiapine, risperidone and aripiprazole accounted for 78.8% of all antipsychotic prescriptions. Higher mean olanzapine equivalent total daily doses were prescribed to patients with the following characteristics: schizophrenia diagnosis, ethnic minority status, male gender, younger age and greater relative deprivation.

Antipsychotic prescribing is dominated by olanzapine, quetiapine, risperidone and aripiprazole. We identified potential disparities in both the receipt and prescribed doses of antipsychotics across subgroups. To inform efforts to optimise prescribing and ensure equity of care, further research is needed to understand why certain groups are prescribed higher doses and are more likely to be treated with long-acting injectable antipsychotics compared with others.

This project developed and validated an automated pipeline for prostate treatments to accurately determine which patients could benefit from adaptive radiotherapy (ART) using synthetic CTs (sCTs) generated from on-treatment cone-beam CT (CBCT) images.

The automated pipeline converted CBCTs to sCTs utilising deep-learning, for accurate dose recalculation. Deformable image registration mapped contours from the planning CT to the sCT, with the treatment plan recalculated. A pass/fail assessment used relevant clinical goals. A fail threshold indicated ART was required. All acquired CBCTs (230 sCTs) for 31 patients (6 who had ART) were assessed for pipeline accuracy and clinical viability, comparing clinical outcomes to pipeline outcomes.

The pipeline distinguished patients requiring ART; 74·4% of sCTs for ART patients were red (failure) results, compared to 6·4% of non-ART sCTs. The receiver operator characteristic area under curve was 0·98, demonstrating high performance. The automated pipeline was statistically significantly (p < 0·05) quicker than the current clinical assessment methods (182·5s and 556·4s, respectively), and deformed contour accuracy was acceptable, with 96·6% of deformed clinical target volumes (CTVs) clinically acceptable.

The automated pipeline identified patients who required ART with high accuracy while reducing time and resource requirements. This could reduce departmental workload and increase efficiency and personalisation of patient treatments. Further work aims to apply the pipeline to other treatment sites and investigate its potential for taking into account dose accumulation.