Implementing a digital decision support tool for side effects of antipsychotics: A qualitative focus group study

Background. In medicine, algorithms can inform treatment decisions by combining the most up-to-date evidence about side effect profiles of medications, which are comparable in efficacy. Their use provides opportunities for improved shared clinician–patient decision-making when initiating therapy. We designed a decision support tool (DST) that incorporated the latest evidence regarding antipsychotic side effects. The tool allowed patients to select one side effect commonly associated with antipsychotics that they wished to avoid; the tool then provided a list of suggested medications and ones to avoid. Objective. To explore qualitatively the acceptability and usefulness of the DST from the perspectives of patients and psychiatrists. Methods. This qualitative study took place at a mental health and community hospital in Oxford, UK, in 2018. Four patients/carers and four psychiatrists were recruited to two focus groups to explore their perceptions of the tool. Data were thematically analysed. Findings. Findings demonstrated a high degree of acceptability and potential usability of the DST for patients and psychiatrists. The main themes to emerge relating to the DST were ‘prescribing preferences and practices’, ‘consideration and awareness of side effects’, ‘app content, layout and accessibility’, ‘influence on clinical practice’ and ‘role in decision-making’. Conclusions. A proof-of-concept clinical study will incorporate the recommendations produced from the findings into the tool’s design. Clinical implications. Digital DSTs provide opportunities for the most up-to-date information on medication side effects to be used as the basis for shared clinician–patient decision-making. This tool has the potential to improve adherence to psychiatric medication, with benefits to clinical outcomes and healthcare resourcing

Rethinking data and rebalancing digital power

This report highlights and contextualises four cross-cutting interventions with a strong potential to reshape the digital ecosystem: 1. Transforming infrastructure into open and interoperable ecosystems. 2. Reclaiming control of data from dominant companies. 3. Rebalancing the centres of power with new (non-commercial) institutions. 4. Ensuring public participation as an essential component of technology policymaking. The interventions are multidisciplinary and they integrate legal, technological, market and governance solutions. They offer a path towards addressing present digital challenges and the possibility for a new, healthy digital ecosystem to emerge. What do we mean by a healthy digital ecosystem? One that privileges people over profit, communities over corporations, society over shareholders. And, most importantly, one where power is not held by a few large corporations, but is distributed among different and diverse models, alongside people who are represented in, and affected by the data used by those new models. The digital ecosystem we propose is balanced, accountable and sustainable, and imagines new types of infrastructure, new institutions and new governance models that can make data work for people and society. Some of these interventions can be located within (or built from) emerging and recently adopted policy initiatives, while others require the wholesale overhaul of regulatory regimes and markets. They are designed to spark ideas that political thinkers, forward-looking policymakers, researchers, civil society organisations, funders and ethical innovators in the private sector consider and respond to when designing future regulations, policies or initiatives around data use and governance. This report also acknowledges the need to prepare the ground for the more ambitious transformation of power relations in the digital ecosystem. Even a well-targeted intervention won't change the system unless it is supported by relevant institutions and behavioural change

Circulating 250HD, dietary vitamin D, PTH, and calcium associations with incident cardiovascular disease and mortality: The MIDSPAN Family Study

<p>Context: Observational studies relating circulating 25-hydroxyvitamin D (25OHD) and dietary vitamin D intake to cardiovascular disease (CVD) have reported conflicting results.</p> <p>Objective: Our objective was to investigate the association of 25OHD, dietary vitamin D, PTH, and adjusted calcium with CVD and mortality in a Scottish cohort.</p> <p>Design and Setting: TheMIDSPAN Family Study is a prospective study of 1040 men and 1298 women from the West of Scotland recruited in 1996 and followed up for a median 14.4 yr. Participants: Locally resident adult offspring of a general population cohort were recruited from 1972–1976.</p> <p>Main Outcome Measures: CVD events (n = 416) and all-cause mortality (n=100) were evaluated.</p> <p>Results: 25OHD was measured using liquid chromatography-tandem mass spectrometry in available plasma (n=2081). Median plasma 25OHD was 18.6 ng/ml, and median vitamin D intake was 3.2 µ g/d (128 IU/d). Vitamin D deficiency (25OHD<15 ng/ml) was present in 689 participants (33.1%). There was no evidence that dietary vitamin D intake, PTH, or adjusted calcium were associated with CVD events or with mortality. Vitamin D deficiency was not associated with CVD (fully adjusted hazard ratio=1.00; 95% confidence interval=0.77–1.31). Results were similar after excluding patients who reported an activity-limiting longstanding illness at baseline (18.8%) and those taking any vitamin supplements (21.7%). However, there was some evidence vitamin D deficiency was associated with all-cause mortality (fully adjusted hazard ratio=2.02; 95% confidence interval=1.17–3.51).</p> <p>Conclusion: Vitamin D deficiency was not associated with risk of CVD in this cohort with very low 25OHD. Future trials of vitamin D supplementation in middle-aged cohorts should be powered to detect differences inmortality outcomes as well as CVD.(J Clin EndocrinolMetab97: 0000 –0000, 2012)</p&gt

Identifying Patterns of Clinical Interest in Clinicians' Treatment Preferences: Hypothesis-free Data Science Approach to Prioritizing Prescribing Outliers for Clinical Review.

BACKGROUND: Data analysis is used to identify signals suggestive of variation in treatment choice or clinical outcome. Analyses to date have generally focused on a hypothesis-driven approach. OBJECTIVE: This study aimed to develop a hypothesis-free approach to identify unusual prescribing behavior in primary care data. We aimed to apply this methodology to a national data set in a cross-sectional study to identify chemicals with significant variation in use across Clinical Commissioning Groups (CCGs) for further clinical review, thereby demonstrating proof of concept for prioritization approaches. METHODS: Here we report a new data-driven approach to identify unusual prescribing behaviour in primary care data. This approach first applies a set of filtering steps to identify chemicals with prescribing rate distributions likely to contain outliers, then applies two ranking approaches to identify the most extreme outliers amongst those candidates. This methodology has been applied to three months of national prescribing data (June-August 2017). RESULTS: Our methodology provides rankings for all chemicals by administrative region. We provide illustrative results for 2 antipsychotic drugs of particular clinical interest: promazine hydrochloride and pericyazine, which rank highly by outlier metrics. Specifically, our method identifies that, while promazine hydrochloride and pericyazine are barely used by most clinicians (with national prescribing rates of 11.1 and 6.2 per 1000 antipsychotic prescriptions, respectively), they make up a substantial proportion of antipsychotic prescribing in 2 small geographic regions in England during the study period (with maximum regional prescribing rates of 298.7 and 241.1 per 1000 antipsychotic prescriptions, respectively). CONCLUSIONS: Our hypothesis-free approach is able to identify candidates for audit and review in clinical practice. To illustrate this, we provide 2 examples of 2 very unusual antipsychotics used disproportionately in 2 small geographic areas of England

Data-Driven Identification of Unusual Prescribing Behavior: Analysis and Use of an Interactive Data Tool Using 6 Months of Primary Care Data From 6500 Practices in England.

BACKGROUND: Approaches to addressing unwarranted variation in health care service delivery have traditionally relied on the prospective identification of activities and outcomes, based on a hypothesis, with subsequent reporting against defined measures. Practice-level prescribing data in England are made publicly available by the National Health Service (NHS) Business Services Authority for all general practices. There is an opportunity to adopt a more data-driven approach to capture variability and identify outliers by applying hypothesis-free, data-driven algorithms to national data sets. OBJECTIVE: This study aimed to develop and apply a hypothesis-free algorithm to identify unusual prescribing behavior in primary care data at multiple administrative levels in the NHS in England and to visualize these results using organization-specific interactive dashboards, thereby demonstrating proof of concept for prioritization approaches. METHODS: Here we report a new data-driven approach to quantify how "unusual" the prescribing rates of a particular chemical within an organization are as compared to peer organizations, over a period of 6 months (June-December 2021). This is followed by a ranking to identify which chemicals are the most notable outliers in each organization. These outlying chemicals are calculated for all practices, primary care networks, clinical commissioning groups, and sustainability and transformation partnerships in England. Our results are presented via organization-specific interactive dashboards, the iterative development of which has been informed by user feedback. RESULTS: We developed interactive dashboards for every practice (n=6476) in England, highlighting the unusual prescribing of 2369 chemicals (dashboards are also provided for 42 sustainability and transformation partnerships, 106 clinical commissioning groups, and 1257 primary care networks). User feedback and internal review of case studies demonstrate that our methodology identifies prescribing behavior that sometimes warrants further investigation or is a known issue. CONCLUSIONS: Data-driven approaches have the potential to overcome existing biases with regard to the planning and execution of audits, interventions, and policy making within NHS organizations, potentially revealing new targets for improved health care service delivery. We present our dashboards as a proof of concept for generating candidate lists to aid expert users in their interpretation of prescribing data and prioritize further investigations and qualitative research in terms of potential targets for improved performance

OpenSAFELY NHS Service Restoration Observatory 2: changes in primary care clinical activity in England during the COVID-19 pandemic

BACKGROUND: The COVID-19 pandemic has disrupted healthcare activity across a broad range of clinical services. The NHS stopped non-urgent work in March 2020, later recommending services be restored to near-normal levels before winter where possible. AIM: To describe changes in the volume and variation of coded clinical activity in general practice across six clinical areas: cardiovascular disease, diabetes, mental health, female and reproductive health, screening and related procedures, and processes related to medication. DESIGN AND SETTING: With the approval of NHS England, a cohort study was conducted of 23.8 million patient records in general practice, in situ using OpenSAFELY. METHOD: Common primary care activities were analysed using Clinical Terms Version 3 codes and keyword searches from January 2019 to December 2020, presenting median and deciles of code usage across practices per month. RESULTS: Substantial and widespread changes in clinical activity in primary care were identified since the onset of the COVID-19 pandemic, with generally good recovery by December 2020. A few exceptions showed poor recovery and warrant further investigation, such as mental health (for example, for 'Depression interim review' the median occurrences across practices in December 2020 was down by 41.6% compared with December 2019). CONCLUSION: Granular NHS general practice data at population-scale can be used to monitor disruptions to healthcare services and guide the development of mitigation strategies. The authors are now developing real-time monitoring dashboards for the key measures identified in this study, as well as further studies using primary care data to monitor and mitigate the indirect health impacts of COVID-19 on the NHS

Changes in English medication safety indicators throughout the COVID-19 pandemic: a federated analysis of 57 million patients’ primary care records in situ using OpenSAFELY

Objective: To describe the impact of the COVID-19 pandemic on safe prescribing, using the PINCER prescribing indicators; to implement complex prescribing indicators at national scale using GP data.Design: Population based cohort study, with the approval of NHS England using the OpenSAFELY platform.Setting: Electronic health record data from 56.8 million NHS patients’ general practice records.Participants: All NHS patients registered at a GP practice using TPP or EMIS computer systems and recorded as at risk of at least one potentially hazardous PINCER indicator between September 2019 and September 2021.Main outcome measure: Monthly trends and between-practice variation for compliance with 13 PINCER indicators between September 2019 and September 2021.Results: The indicators were successfully implemented across GP data in OpenSAFELY. Hazardous prescribing remained largely unchanged during the COVID-19 pandemic, with no evidence of increases in indicators of harm as captured by the PINCER indicators. There were transient delays in blood test monitoring for some medications, particularly ACE inhibitors. All indicators exhibited substantial recovery by September 2021. We identified 1,813,058 patients (3.1%) at risk of at least one potentially hazardous prescribing event.Conclusion: NHS GP data can be analysed at national scale to generate insights on service delivery. Potentially hazardous prescribing was largely unaffected by COVID-19 in a dataset of 57 million patients’ full primary care health records in England

The art of serious storytelling: using novel visual methods to engage veterinary practitioners in reducing infection risk during surgical preparation

Antimicrobial-resistant bacteria are a growing global healthcare threat. Uptake of appropriate infection prevention and control (IPC) measures is heavily influenced by human risk perception, consequent behaviour and the ways humans and animals interact within the environment. Effective IPC communication and teaching tools are necessary to ensure individuals’ understanding and behaviours are in line with scientific recommendations. This chapter describes a novel approach to developing an IPC training tool to raise the perception and understanding of risk of infection to animal patients during routine veterinary surgical procedures. The researchers ‘made the invisible visible’, revealing bacterial contamination sources and their spread during preparation for surgery via a dynamic 3-layer interactive virtual model of a veterinary practice based on real-world data on human, animal and bacterial interactions. They used a serious storytelling approach, visualisation, simple gamification techniques and a collaborative design approach to engage students, nurses and surgeons from the veterinary community in the co-development of the tool. Participants were invited to identify risky behaviours, direct and indirect sources of bacterial contamination, and were prompted to reflect on the potential consequences of poor or improved IPC measures on the patient outcome and residual bacterial contamination in the practice environment. The study was conducted over two phases. Phase 1 achieved proof-of-concept: at evaluation, 92% of 51 trial participants stated an intention to change their behaviour and to implement infection controls that aligned with training objectives. In Phase 2, the tool was enhanced, and software was developed to a beta-version to enable self-paced training on web-based and mobile platforms. The co-development and evaluation process, importance of end-user engagement throughout and findings are discussed

COVID-19 and substance use disorders: a review of international guidelines for frontline healthcare workers of addiction services.

BACKGROUND: People with substance use disorders may be at a greater risk of contracting COVID-19 infection and developing medical complications. Several institutional and governmental health agencies across the world developed ad hoc guidance for substance use disorder services and care of individuals misusing substances. We aimed to synthesise the best available recommendations on management and care of people with or at risk of substance use disorders during the COVID-19 pandemic from existing guidelines published in UK, USA, Australia, Canada, New Zealand, and Singapore. METHODS: We systematically searched existing guidelines and websites from 28 international institutions and governmental bodies in the context of the COVID-19 pandemic (May 4 2021). We summarized the extracted data as answers to specific clinical questions. RESULTS: We organised the available recommendations from 19 sources in three sections. First, we focused on general advice and recommendations for people who misuse alcohol or drugs during the COVID-19 pandemic, the design of contingency plans, safeguarding issues for children and families of service users and advice to the public, patients, and carers. Then, we summarised specific guidelines for people who use illicit drugs and related services, such as opioid substitution treatment and needle and syringe programmes. Finally, we provided a synthesis on specific recommendations for services supporting people who misuse alcohol and key topics in the field, such as management of alcohol detoxification and safe transition between supervised and unsupervised consumption. CONCLUSIONS: Available guidance reflected different approaches, ranging from being extremely cautious in providing recommendations other than generic statements to proposing adaptation of previously available guidelines to confront the challenges of the COVID-19 pandemic. After the early phase, guidance focused on reduction of infection transmission and service delivery. Guidance did not provide advice on infection prevention via vaccination programmes and service access strategies tailored to individuals with substance use disorders

Age discrimination in history

BACKGROUND: Lung and colorectal cancer are common and have high UK mortality rates. Early diagnosis is important in reducing cancer mortality, but the literature on lung and colorectal cancers suggests many people wait for a considerable time before presenting symptoms. OBJECTIVE: To gain in-depth understanding of patients' interpretations of symptoms of lung and colorectal cancer prior to diagnosis, and to explore processes leading to help-seeking. METHODS: Semi-structured interviews were conducted with patients diagnosed with lung (N=9) or colorectal (N=20) cancer within the previous 12 months. Patients were asked about symptoms experienced in the period preceding diagnosis, their interpretations of symptoms, and decision making for help-seeking. Thematic analysis was conducted and comparisons drawn within and across the patient groups. RESULTS: Patients were proactive and rational in addressing symptoms; many developed alternative, non-cancer explanations based on their knowledge and experience. Discussions with important others frequently provided the impetus to consult, but paradoxically others often initially reinforced alternative explanations. Fear and denial did not emerge as barriers to help-seeking, but help-seeking was triggered when patients' alternative explanations could no longer be maintained, for instance due to persistence or progression of symptoms. CONCLUSION: Patients' reasoning, decision making and interpersonal interactions prior to diagnosis were complex. Prompting patients for additional detail on symptoms within consultations could elicit critical contextual information to aid referral decisions. Findings also have implications for the design of public health campaigns