Ambiguity Uncertainty and Risk: Reframing the task of suicide risk assessment and prevention in acute in-patient mental health

The work of the National Confidential Inquiry into Suicide by People with Mental Illness has served to draw attention to the issue of suicide amongst users of mental health services including inpatient and provided the basis for a series of recommendations aimed at improving practice (Appleby et al., 2001, NIMHE 2003). Such recommendations include further training on risk assessment for practitioners. However, representing the problem of suicide as one which can be 'managed' by risk assessment particularly quantitative actuarial approaches implicitly misrepresents the phenomena of suicidality as something which can predicted and therefore managed may be inherently unpredictable at the level of the individual over the short term. We need instead to acknowledge that our work with service users who may be contemplating suicide embraces and acknowledges both uncertainty and ambiguity and seeks to assess risk phenomenologically at the level of the individual such that by understanding their reasons for living and dying we can work in partnership with them to find hope

How, for Whom, and in Which Contexts or Conditions Augmented and Virtual Reality Training Works in Upskilling Health Care Workers: Realist Synthesis

BACKGROUND: Using traditional simulators (eg, cadavers, animals, or actors) to upskill health workers is becoming less common because of ethical issues, commitment to patient safety, and cost and resource restrictions. Virtual reality (VR) and augmented reality (AR) may help to overcome these barriers. However, their effectiveness is often contested and poorly understood and warrants further investigation. OBJECTIVE: The aim of this review is to develop, test, and refine an evidence-informed program theory on how, for whom, and to what extent training using AR or VR works for upskilling health care workers and to understand what facilitates or constrains their implementation and maintenance. METHODS: We conducted a realist synthesis using the following 3-step process: theory elicitation, theory testing, and theory refinement. We first searched 7 databases and 11 practitioner journals for literature on AR or VR used to train health care staff. In total, 80 papers were identified, and information regarding context-mechanism-outcome (CMO) was extracted. We conducted a narrative synthesis to form an initial program theory comprising of CMO configurations. To refine and test this theory, we identified empirical studies through a second search of the same databases used in the first search. We used the Mixed Methods Appraisal Tool to assess the quality of the studies and to determine our confidence in each CMO configuration. RESULTS: Of the 41 CMO configurations identified, we had moderate to high confidence in 9 (22%) based on 46 empirical studies reporting on VR, AR, or mixed simulation training programs. These stated that realistic (high-fidelity) simulations trigger perceptions of realism, easier visualization of patient anatomy, and an interactive experience, which result in increased learner satisfaction and more effective learning. Immersive VR or AR engages learners in deep immersion and improves learning and skill performance. When transferable skills and knowledge are taught using VR or AR, skills are enhanced and practiced in a safe environment, leading to knowledge and skill transfer to clinical practice. Finally, for novices, VR or AR enables repeated practice, resulting in technical proficiency, skill acquisition, and improved performance. The most common barriers to implementation were up-front costs, negative attitudes and experiences (ie, cybersickness), developmental and logistical considerations, and the complexity of creating a curriculum. Facilitating factors included decreasing costs through commercialization, increasing the cost-effectiveness of training, a cultural shift toward acceptance, access to training, and leadership and collaboration. CONCLUSIONS: Technical and nontechnical skills training programs using AR or VR for health care staff may trigger perceptions of realism and deep immersion and enable easier visualization, interactivity, enhanced skills, and repeated practice in a safe environment. This may improve skills and increase learning, knowledge, and learner satisfaction. The future testing of these mechanisms using hypothesis-driven approaches is required. Research is also required to explore implementation considerations

Upskilling health and care workers with augmented and virtual reality: protocol for a realist review to develop an evidence-informed programme theory.

From Europe PMC via Jisc Publications RouterHistory: ppub 2021-07-01, epub 2021-07-05Publication status: PublishedIntroductionAugmented reality (AR) and virtual reality (VR) are increasingly used to upskill health and care providers, including in surgical, nursing and acute care settings. Many studies have used AR/VR to deliver training, providing mixed evidence on their effectiveness and limited evidence regarding contextual factors that influence effectiveness and implementation. This review will develop, test and refine an evidence-informed programme theory on what facilitates or constrains the implementation of AR or VR programmes in health and care settings and understand how, for whom and to what extent they 'work'.Methods and analysisThis realist review adheres to the Realist And Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) standards and will be conducted in three steps: theory elicitation, theory testing and theory refinement. First, a search will identify practitioner, academic and learning and technology adoption theories from databases (MEDLINE, Scopus, CINAHL, Embase, Education Resources Information Center, PsycINFO and Web of Science), practitioner journals, snowballing and grey literature. Information regarding contexts, mechanisms and outcomes will be extracted. A narrative synthesis will determine overlapping configurations and form an initial theory. Second, the theory will be tested using empirical evidence located from the above databases and identified from the first search. Quality will be assessed using the Mixed Methods Appraisal Tool (MMAT), and relevant information will be extracted into a coding sheet. Third, the extracted information will be compared with the initial programme theory, with differences helping to make refinements. Findings will be presented as a narrative summary, and the MMAT will determine our confidence in each configuration.Ethics and disseminationEthics approval is not required. This review will develop an evidence-informed programme theory. The results will inform and support AR/VR interventions from clinical educators, healthcare providers and software developers. Upskilling through AR/VR learning interventions may improve quality of care and promote evidence-based practice and continued learning. Findings will be disseminated through conference presentations and peer-reviewed journal articles

Variation in National Clinical Audit Data Capture:Is Using Routine Data the Answer?

National Clinical Audit (NCA) data are collected from all National Health Service providers in the UK, to measure the quality of care and stimulate quality improvement initatives. As part of a larger study we explored how NHS providers currently collect NCA data and the resources involved. Study results highlight a dependence on manual data entry and use of professional resources, which could be improved by exploring how routine clinical data could be captured more effectively

Exploring variation in the use of feedback from national clinical audits : a realist investigation

BACKGROUND: National Clinical Audits (NCAs) are a well-established quality improvement strategy used in healthcare settings. Significant resources, including clinicians' time, are invested in participating in NCAs, yet there is variation in the extent to which the resulting feedback stimulates quality improvement. The aim of this study was to explore the reasons behind this variation. METHODS: We used realist evaluation to interrogate how context shapes the mechanisms through which NCAs work (or not) to stimulate quality improvement. Fifty-four interviews were conducted with doctors, nurses, audit clerks and other staff working with NCAs across five healthcare providers in England. In line with realist principles we scrutinised the data to identify how and why providers responded to NCA feedback (mechanisms), the circumstances that supported or constrained provider responses (context), and what happened as a result of the interactions between mechanisms and context (outcomes). We summarised our findings as Context+Mechanism = Outcome configurations. RESULTS: We identified five mechanisms that explained provider interactions with NCA feedback: reputation, professionalism, competition, incentives, and professional development. Professionalism and incentives underpinned most frequent interaction with feedback, providing opportunities to stimulate quality improvement. Feedback was used routinely in these ways where it was generated from data stored in local databases before upload to NCA suppliers. Local databases enabled staff to access data easily, customise feedback and, importantly, the data were trusted as accurate, due to the skills and experience of staff supporting audit participation. Feedback produced by NCA suppliers, which included national comparator data, was used in a more limited capacity across providers. Challenges accessing supplier data in a timely way and concerns about the quality of data submitted across providers were reported to constrain use of this mode of feedback. CONCLUSION: The findings suggest that there are a number of mechanisms that underpin healthcare providers' interactions with NCA feedback. However, there is variation in the mode, frequency and impact of these interactions. Feedback was used most routinely, providing opportunities to stimulate quality improvement, within clinical services resourced to collect accurate data and to maintain local databases from which feedback could be customised for the needs of the service

Complex interventions in midwifery care: Reflections on the design and evaluation of an algorithm for the diagnosis of labour

Randomised controlled trials are the ‘gold standard’ for evaluating the effectiveness of interventions in health-care settings. However, in midwifery care, many interventions are ‘complex’, comprising a number of different elements which may have an effect on the impact of the intervention in health-care settings. In this paper we reflect on our experience of designing and evaluating a complex intervention (a decision tool to assist with the diagnosis of labour in midwifery care), examining some of the issues that our study raises for future research in complex interventions

Institutional use of National Clinical Audits by healthcare providers

Rationale, aims, and objectives Healthcare systems worldwide devote significant resources towards collecting data to support care quality assurance and improvement. In the United Kingdom, National Clinical Audits are intended to contribute to these objectives by providing public reports of data on healthcare treatment and outcomes, but their potential for quality improvement in particular is not realized fully among healthcare providers. Here, we aim to explore this outcome from the perspective of hospital boards and their quality committees: an under‐studied area, given the emphasis in previous research on the audits' use by clinical teams. Methods We carried out semi‐structured, qualitative interviews with 54 staff in different clinical and management settings in five English National Health Service hospitals about their use of NCA data, and the circumstances that supported or constrained such use. We used Framework Analysis to identify themes within their responses. Results We found that members and officers of hospitals' governing bodies perceived an imbalance between the benefits to their institutions from National Clinical Audits and the substantial resources consumed by participating in them. This led some to question the audits' legitimacy, which could limit scope for improvements based on audit data, proposed by clinical teams. Conclusions Measures to enhance the audits' perceived legitimacy could help address these limitations. These include audit suppliers moving from an emphasis on cumulative, retrospective reports to real‐time reporting, clearly presenting the “headline” outcomes important to institutional bodies and staff. Measures may also include further negotiation between hospitals, suppliers and their commissioners about the nature and volume of data the latter are expected to collect; wider use by hospitals of routine clinical data to populate audit data fields; and further development of interactive digital technologies to help staff explore and report audit data in meaningful ways

Predictive model-based interventions to reduce outpatient no-shows: a rapid systematic review

Objective: Outpatient no-shows have important implications for costs and the quality of care. Predictive models of no-shows could be used to target intervention delivery to reduce no-shows. We reviewed the effectiveness of predictive model-based interventions on outpatient no-shows, intervention costs, acceptability, and equity. Materials and Methods: Rapid systematic review of randomized controlled trials (RCTs) and non-RCTs. We searched Medline, Cochrane CENTRAL, Embase, IEEE Xplore, and Clinical Trial Registries on March 30, 2022 (updated on July 8, 2022). Two reviewers extracted outcome data and assessed the risk of bias using ROB 2, ROBINS-I, and confidence in the evidence using GRADE. We calculated risk ratios (RRs) for the relationship between the intervention and no-show rates (primary outcome), compared with usual appointment scheduling. Meta-analysis was not possible due to heterogeneity. Results: We included 7 RCTs and 1 non-RCT, in dermatology (n = 2), outpatient primary care (n = 2), endoscopy, oncology, mental health, pneumology, and an magnetic resonance imaging clinic. There was high certainty evidence that predictive model-based text message reminders reduced no-shows (1 RCT, median RR 0.91, interquartile range [IQR] 0.90, 0.92). There was moderate certainty evidence that predictive model-based phone call reminders (3 RCTs, median RR 0.61, IQR 0.49, 0.68) and patient navigators reduced no-shows (1 RCT, RR 0.55, 95% confidence interval 0.46, 0.67). The effect of predictive model-based overbooking was uncertain. Limited information was reported on cost-effectiveness, acceptability, and equity. Discussion and Conclusions: Predictive modeling plus text message reminders, phone call reminders, and patient navigator calls are probably effective at reducing no-shows. Further research is needed on the comparative effectiveness of predictive model-based interventions addressed to patients at high risk of no-shows versus nontargeted interventions addressed to all patients

Diagnosis and management of people with venous thromboembolism and advanced cancer: how do doctors decide? a qualitative study

Abstract Background: The treatment of cancer associated thrombosis (CAT) is well established, with level 1A evidence to support the recommendation of a low molecular weight heparin (LMWH) by daily injection for 3-6 months. However, registry data suggest compliance to clinical guidelines is poor. Clinicians face particular challenges in treating CAT in advanced cancer patients due to shorter life expectancy, increased bleeding risk and concerns that self injection may be too burdensome. For these reasons decision making around the diagnosis and management of CAT in people with advanced cancer, can be complex, and should focus on its likely net benefit for the patient. We explored factors that influence doctors' decision making in this situation and sought to gain an understanding of the barriers and facilitators to the application of best practice. Methods: Think aloud exercises using standardised case scenarios, and individual in depth interviews were conducted. All were transcribed. The think aloud exercises were analysed using Protocol Analysis and the interviews using Framework Analysis. Participants: 46 participants took part in the think aloud exercises and 45 participants were interviewed in depth. Each group included oncologists, palliative physicians and general practitioners and included both senior doctors and those in training. Setting: Two Strategic Health Authority regions, one in the north of England and one in Wales