Improving availability and accuracy of the junior doctors' on-call handover through digitalisation.

Clinical handovers from out-of-hours activity are essential for relaying information about events such as new admissions, outstanding or complete investigations, physical health reviews, ward jobs and risk. This information enables the day team to effectively prioritise and follow-up any necessary tasks.Junior doctors at a hospital site in the London Borough of Newham were aware that the existing handover system, constituted of a word document circulated via email, was lacking robustness and that the handover was not sent out reliably on a daily basis.Quality improvement (QI) methods including process mapping, PDSA ('Plan, Do, Study, Act') cycles, driver diagrams and run charts were used to understand the issue, create a more robust process and measure the improvements made, all supported by regular QI project meetings. The change ideas included moving from an informal Microsoft (MS) Word document, which was emailed out, to an Excel spreadsheet stored centrally on MS Teams. Column headers were added for admissions, ward jobs, seclusion reviews, matters relating to mental health law and Accident and Emergency (A&E) assessments, as well as defined columns for outstanding jobs and standard tasks that need to be completed for all admissions. Responsibility for circulating the handover list was given to the incoming day duty doctor if the night doctor was too busy, with admin support to chase the circulation of the handover. Results were studied for the following 18 months.The percentage of handovers being appropriately sent out increased from a median of 80% to 100% during the project period, and the availability of handover data where the data were visible to doctors on MS Teams but had not been sent out also increased from a median of 80% to 100%. The system was deemed safe, effective and easy to use, and has already been replicated at neighbouring hospitals.

The contribution of pain catastrophizing, depression and anxiety symptoms among patients with persistent pain and opioid misuse behaviours.

BACKGROUND: Anxiety, depression and pain catastrophizing are independently associated with risk of opioid misuse in patients with persistent pain but their relationship to current opioid misuse, when considered together, is poorly understood. This study will assess the relative contribution of these modifiable, and distinct psychological constructs to current opioid misuse in patients with persistent pain. METHODS: One hundred and twenty-seven patients referred to a specialized opioid management clinic for prescription opioid misuse within a tertiary pain service were recruited for this study. The Pain Catastrophizing Scale, Depression, Anxiety and Stress Scales and the Current Opioid Misuse Measure were administered pre-treatment. Pain severity and morphine equivalent dose based on independent registry data were also recorded. RESULTS: Higher levels of pain catastrophizing, depression, and anxiety were significantly associated with higher current opioid misuse (r = .475, 0.599, and 0.516 respectively, p < .01). Pain severity was significantly associated with pain catastrophizing (r = .301, p < .01). Catastrophizing, depression, and anxiety explained an additional 11.56% of the variance (R2 change = 0.34, p < .01) over and above age, gender, pain severity and morphine equivalent dose. Depression was the only significant variable at Step 2 (ß = 0.62, p < .01). CONCLUSION: Findings show that in a sample of people with persistent pain referred for treatment for opioid misuse, depression contributes over and above that of anxiety and pain catastrophizing. Theoretical and clinical practice implications are presented.

Improving referrals to community mental health services in the liaison setting.

The East London Foundation Trust (ELFT) psychiatric liaison team (PLT) at Newham University Hospital (NUH) is responsible for referring adult patients they have reviewed, on to community mental health services on discharge where appropriate, and also to notify their existing team for follow-up on discharge when already under the care of a community service. This should then lead to appropriate ongoing management of the patient's mental health needs in terms of continued support and assessment of risk, further assessment of mental state, titration of medications and prevention of further admissions.Following an ELFT incident review where it was noted that a patient was not referred to community services on discharge, a retrospective case note review was undertaken over an 11-month period to define the baseline efficacy of current referrals. Quality improvement (QI) methods were used to understand the issue, create a more robust process and measure the improvements made. We set up regular QI Project meetings and we used driver diagram, process mapping, PDSA cycles and run charts. The change ideas included moving from a white board based system to using Microsoft Excel, CRS millennium patient lists, Microsoft TEAMS and additional admin support. We studied the results for the following 14 months.The percentage of patients being appropriately referred in terms of timeliness and correct documentation increased from a run chart baseline of 35% to 88% during the project period, and the number of patients with some evidence of referral having been completed increased from 83% to 100%.The previous system used was ineffective in managing onward referrals for mental health patients from PLT. QI methods have allowed sustainable improvement in both the percentage of patients referred and those correctly documented, improving follow up and care for mental health patients who are admitted to NUH.

Network Analysis and Visualisation of Opioid Prescribing Data.

In many countries around the world (including Australia), the prescribing of opioid analgesic drugs is an increasing trend associated with significant increases in drug-related patient harm such as abuse, overdose, and death. In Australia, the Medicines Regulation and Quality Unit within Queensland Health maintains a database recording opioid analgesic drug prescriptions dispensed across the State (population 4.703 million). In this work, we propose the use of network visualisation and analysis as a tool for improved understanding of these data. Prescribing data for Fentanyl patches, a strong opioid with high potential for misuse and subsequent harm, across Queensland, Australia from 2011 to 2018 is analysed as an example of using network analysis, where prescribing patterns are viewed as a dynamic, bipartite graph of the interactions between patients and prescribers over time. The technique provides a global view of a large state-wide prescribing dataset, including the distribution of subgraph structures present. Local analysis is also carried out to demonstrate the clinical utility of the technique, including the dynamics of the graph structure over time. A variety of network statistics that measure network structural and dynamic properties are presented to reveal the characteristics and trends of drug seeking and prescribing behaviours. This approach has been recognised by healthcare professionals at Queensland Health as leading to new and useful insights on the relationship between patients and prescribers and supporting their advisory role to reduce patient harm from inappropriate use of prescription drugs.

Meperidine: a continuing problem.

Letter to the Editor regarding meperidine prescriptions in Queensland, Australia, 1999 to 2010.

Validation of the Drinking Refusal Self-Efficacy Questionnaire--Revised in an Adolescent Sample (DRSEQ-RA).

Adolescent drinking is a significant issue yet valid psychometric tools designed for this group are scarce. The Drinking Refusal Self-Efficacy Questionnaire--Revised Adolescent Version (DRSEQ-RA) is designed to assess an individual's belief in their ability to resist drinking alcohol. The original DRSEQ-R consists of three factors reflecting social pressure refusal self-efficacy, opportunistic refusal self-efficacy and emotional relief refusal self-efficacy. A large sample of 2020 adolescents aged between 12 and 19 years completed the DRSEQ and measures of alcohol consumption in small groups. Using confirmatory factor analysis, the three factor structure was confirmed. All three factors were negatively correlated with both frequency and volume of alcohol consumption. Drinkers reported lower drinking refusal self-efficacy than non-drinkers. Taken together, these results suggest that the adolescent version of the Drinking Refusal Self-Efficacy Questionnaire (DRSEQ-RA) is a reliable and valid measure of drinking refusal self-efficacy.