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.

Early intervention in psychosis (EIP) services improve outcomes for young people, but approximately 30% disengage.

To test whether a new motivational engagement intervention would prolong engagement and whether it was cost-effective.

We conducted a multicentre, single-blind, parallel-group, cluster randomised controlled trial involving 20 EIP teams at five UK National Health Service (NHS) sites. Teams were randomised using permuted blocks stratified by NHS trust. Participants were all young people (aged 14–35 years) presenting with a first episode of psychosis between May 2019 and July 2020 (N = 1027). We compared the novel Early Youth Engagement (EYE-2) intervention plus standardised EIP (sEIP) with sEIP alone. The primary outcome was time to disengagement over 12–26 months. Economic outcomes were mental health costs, societal costs and socio-occupational outcomes over 12 months. Assessors were masked to treatment allocation for primary disengagement and cost-effectiveness outcomes. Analysis followed intention-to-treat principles. The trial was registered at ISRCTN51629746.

Disengagement was low at 15.9% overall in standardised stand-alone services. The adjusted hazard ratio for EYE-2 + sEIP (n = 652) versus sEIP alone (n = 375) was 1.07 (95% CI 0.76–1.49; P = 0.713). The health economic evaluation indicated lower mental healthcare costs linked to reductions in unplanned mental healthcare with no compromise of clinical outcomes, as well as some evidence for lower societal costs and more days in education, training, employment and stable accommodation in the EYE-2 group.

We found no evidence that EYE-2 increased time to disengagement, but there was some evidence for its cost-effectiveness. This is the largest study to date reporting positive engagement, health and cost outcomes in a total EIP population sample. Limitations included high loss to follow-up for secondary outcomes and low completion of societal and socio-occupational data. COVID-19 affected fidelity and implementation. Future engagement research should target engagement to those in greatest need, including in-patients and those with socio-occupational goals.