Nonbinary and binary transgender youth: Comparison of mental health, self-harm, suicidality, substance use and victimisation experiences

Background: Little research has compared the mental health and victimisation experiences of nonbinary youth depending on their sex assigned at birth (SAAB), or compared these two groups with binary transgender youth. Aims: To compare mental health, self-harm and suicidality, substance use and victimisation experiences between nonbinary and binary transgender young adults, both male assigned at birth (MAAB) and female assigned at birth (FAAB). Methods: Online survey data from 677 participants from the ‘Youth Chances’ community study of 16 to 25 year-olds in the United Kingdom was analysed, comparing across binary participants (transgender females (n=105) and transgender males (n=210)) and nonbinary participants (MAAB (n=93) and FAAB (n=269)). Results: Female SAAB participants (binary and nonbinary) were more likely to report a current mental health condition and history of self-harm than male SAAB participants (binary and nonbinary). Similarly, female SAAB participants (binary and nonbinary) were more likely to report childhood sexual abuse than male SAAB participants (binary and nonbinary); the reverse pattern was found for lifetime physical assault relating to being LGBTQ. Nonbinary MAAB participants were less likely than the other groups to report past suicide attempts and previous help-seeking for depression / anxiety. Binary participants reported lower life satisfaction than nonbinary participants. For all four groups, mental health problems, self-harm, suicidality, alcohol use and victimisation experiences were generally higher than that of youth in general population studies. Conclusions: These findings highlight the importance of considering both nonbinary versus binary gender identity and sex assigned at birth in relation to mental health problems, self-harm, suicidality and substance use in transgender youth. The roles of sexual abuse, other abuse and discrimination in contributing to increased rates of mental illness and self-harm in nonbinary and binary transgender individuals, particularly those who were assigned female at birth, relative to those assigned male, require investigation

The costs of dementia in England

Objectives: This study measures the average per person and annual total costs of dementia in England in 2015. Methods/Design: Up-to-date data for England were drawn from multiple sources to identify prevalence of dementia by severity, patterns of health and social care service utilisation and their unit costs, levels of unpaid care and its economic impacts, and other costs of dementia. These data were used in a refined macrosimulation model to estimate annual per-person and aggregate costs of dementia. Results: There are around 690 000 people with dementia in England, of whom 565 000 receive unpaid care or community care or live in a care home. Total annual cost of dementia in England is estimated to be £24.2 billion in 2015, of which 42% (£10.1 billion) is attributable to unpaid care. Social care costs (£10.2 billion) are three times larger than health care costs (£3.8 billion). £6.2 billion of the total social care costs are met by users themselves and their families, with £4.0 billion (39.4%) funded by government. Total annual costs of mild, moderate, and severe dementia are £3.2 billion, £6.9 billion, and £14.1 billion, respectively. Average costs of mild, moderate, and severe dementia are £24 400, £27 450, and £46 050, respectively, per person per year. Conclusions: Dementia has huge economic impacts on people living with the illness, their carers, and society as a whole. Better support for people with dementia and their carers, as well as fair and efficient financing of social care services, are essential to address the current and future challenges of dementia

Impact of hepatobiliary service centralization on treatment and outcomes in patients with colorectal cancer and liver metastases

Background: Centralization of specialist surgical services can improve patient outcomes. The aim of this cohort study was to compare liver resection rates and survival in patients with primary colorectal cancer and synchronous metastases limited to the liver diagnosed at hepatobiliary surgical units (hubs) with those diagnosed at hospital Trusts without hepatobiliary services (spokes). Methods: The study included patients from the National Bowel Cancer Audit diagnosed with primary colorectal cancer between 1 April 2010 and 31 March 2014 who underwent colorectal cancer resection in the English National Health Service. Patients were linked to Hospital Episode Statistics data to identify those with liver metastases and those who underwent liver resection. Multivariable random‐effects logistic regression was used to estimate the odds ratio of liver resection by presence of specialist hepatobiliary services on site. Survival curves were estimated using the Kaplan–Meier method. Results: Of 4547 patients, 1956 (43·0 per cent) underwent liver resection. The 1081 patients diagnosed at hubs were more likely to undergo liver resection (adjusted odds ratio 1·52, 95 per cent c.i. 1·20 to 1·91). Patients diagnosed at hubs had better median survival (30·6 months compared with 25·3 months for spokes; adjusted hazard ratio 0·83, 0·75 to 0·91). There was no difference in survival between hubs and spokes when the analysis was restricted to patients who had liver resection (P = 0·620) or those who did not undergo liver resection (P = 0·749). Conclusion: Patients with colorectal cancer and synchronous metastases limited to the liver who are diagnosed at hospital Trusts with a hepatobiliary team on site are more likely to undergo liver resection and have better survival

Patient non-attendance at urgent referral appointments for suspected cancer and its links to cancer diagnosis and one year mortality : A cohort study of patients referred on the Two Week Wait pathway

BACKGROUND: The 'Two Week Wait' policy aims to ensure patients with suspected cancer are seen within two weeks of referral. However, patient non-attendance can result in this target being missed. This study aimed to identify predictors of non-attendance; and analyse the relationship between attendance and outcomes including cancer diagnosis and early mortality. METHODS: A cohort study of 109,433 adults registered at 105 general practices, referred to a cancer centre within a large NHS hospital trust (April 2009 to December 2016) on the 'Two Week Wait' pathway. RESULTS: 5673 (5.2%) patients did not attend. Non-attendance was largely predicted by patient factors (younger and older age, male gender, greater deprivation, suspected cancer site, earlier year of referral, greater distance to the hospital) over practice factors (greater deprivation, lower Quality and Outcomes Framework score, lower cancer conversion rate, lower cancer detection rate). 10,360 (9.6%) patients were diagnosed with cancer within six months of referral (9.8% attending patients, 5.6% non-attending patients). Among these patients, 2029 (19.6%) died within 12 months of diagnosis: early mortality risk was 31.3% in non-attenders and 19.2% in attending patients. CONCLUSIONS: Non-attendance at urgent referral appointments for suspected cancer involves a minority of patients but happens in predictable groups. Cancer diagnosis was less likely in non-attending patients but these patients had worse early mortality outcomes than attending patients. The study findings have implications for cancer services and policy

Clinical effectiveness and cost-effectiveness of issuing longer versus shorter duration (3-month vs. 28-day) prescriptions in patients with chronic conditions: systematic review and economic modelling.

BACKGROUND: To reduce expenditure on, and wastage of, drugs, some commissioners have encouraged general practitioners to issue shorter prescriptions, typically 28 days in length; however, the evidence base for this recommendation is uncertain. OBJECTIVE: To evaluate the evidence of the clinical effectiveness and cost-effectiveness of shorter versus longer prescriptions for people with stable chronic conditions treated in primary care. DESIGN/DATA SOURCES: The design of the study comprised three elements. First, a systematic review comparing 28-day prescriptions with longer prescriptions in patients with chronic conditions treated in primary care, evaluating any relevant clinical outcomes, adherence to treatment, costs and cost-effectiveness. Databases searched included MEDLINE (PubMed), EMBASE, Cumulative Index to Nursing and Allied Health Literature, Web of Science and Cochrane Central Register of Controlled Trials. Searches were from database inception to October 2015 (updated search to June 2016 in PubMed). Second, a cost analysis of medication wastage associated with < 60-day and ≥ 60-day prescriptions for five patient cohorts over an 11-year period from the Clinical Practice Research Datalink. Third, a decision model adapting three existing models to predict costs and effects of differing adherence levels associated with 28-day versus 3-month prescriptions in three clinical scenarios. REVIEW METHODS: In the systematic review, from 15,257 unique citations, 54 full-text papers were reviewed and 16 studies were included, five of which were abstracts and one of which was an extended conference abstract. None was a randomised controlled trial: 11 were retrospective cohort studies, three were cross-sectional surveys and two were cost studies. No information on health outcomes was available. RESULTS: An exploratory meta-analysis based on six retrospective cohort studies suggested that lower adherence was associated with 28-day prescriptions (standardised mean difference -0.45, 95% confidence interval -0.65 to -0.26). The cost analysis showed that a statistically significant increase in medication waste was associated with longer prescription lengths. However, when accounting for dispensing fees and prescriber time, longer prescriptions were found to be cost saving compared with shorter prescriptions. Prescriber time was the largest component of the calculated cost savings to the NHS. The decision modelling suggested that, in all three clinical scenarios, longer prescription lengths were associated with lower costs and higher quality-adjusted life-years. LIMITATIONS: The available evidence was found to be at a moderate to serious risk of bias. All of the studies were conducted in the USA, which was a cause for concern in terms of generalisability to the UK. No evidence of the direct impact of prescription length on health outcomes was found. The cost study could investigate prescriptions issued only; it could not assess patient adherence to those prescriptions. Additionally, the cost study was based on products issued only and did not account for underlying patient diagnoses. A lack of good-quality evidence affected our decision modelling strategy. CONCLUSIONS: Although the quality of the evidence was poor, this study found that longer prescriptions may be less costly overall, and may be associated with better adherence than 28-day prescriptions in patients with chronic conditions being treated in primary care. FUTURE WORK: There is a need to more reliably evaluate the impact of differing prescription lengths on adherence, on patient health outcomes and on total costs to the NHS. The priority should be to identify patients with particular conditions or characteristics who should receive shorter or longer prescriptions. To determine the need for any further research, an expected value of perfect information analysis should be performed. STUDY REGISTRATION: This study is registered as PROSPERO CRD42015027042. FUNDING: The National Institute for Health Research Health Technology Assessment programme

New Horizons in the use of routine data for ageing research

The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people

Developing new ways of measuring the quality and impact of ambulance service care: the PhOEBE mixed-methods research programme

Background Ambulance service quality measures have focused on response times and a small number of emergency conditions, such as cardiac arrest. These quality measures do not reflect the care for the wide range of problems that ambulance services respond to and the Prehospital Outcomes for Evidence Based Evaluation (PhOEBE) programme sought to address this. Objectives The aim was to develop new ways of measuring the impact of ambulance service care by reviewing and synthesising literature on prehospital ambulance outcome measures and using consensus methods to identify measures for further development; creating a data set linking routinely collected ambulance service, hospital and mortality data; and using the linked data to explore the development of case-mix adjustment models to assess differences or changes in processes and outcomes resulting from ambulance service care. Design A mixed-methods study using a systematic review and synthesis of performance and outcome measures reported in policy and research literature; qualitative interviews with ambulance service users; a three-stage consensus process to identify candidate indicators; the creation of a data set linking ambulance, hospital and mortality data; and statistical modelling of the linked data set to produce novel case-mix adjustment measures of ambulance service quality. Setting East Midlands and Yorkshire, England. Participants Ambulance services, patients, public, emergency care clinical academics, commissioners and policy-makers between 2011 and 2015. Interventions None. Main outcome measures Ambulance performance and quality measures. Data sources Ambulance call-and-dispatch and electronic patient report forms, Hospital Episode Statistics, accident and emergency and inpatient data, and Office for National Statistics mortality data. Results Seventy-two candidate measures were generated from systematic reviews in four categories: (1) ambulance service operations (n = 14), (2) clinical management of patients (n = 20), (3) impact of care on patients (n = 9) and (4) time measures (n = 29). The most common operations measures were call triage accuracy; clinical management was adherence to care protocols, and for patient outcome it was survival measures. Excluding time measures, nine measures were highly prioritised by participants taking part in the consensus event, including measures relating to pain, patient experience, accuracy of dispatch decisions and patient safety. Twenty experts participated in two Delphi rounds to refine and prioritise measures and 20 measures scored ≥ 8/9 points, which indicated good consensus. Eighteen patient and public representatives attending a consensus workshop identified six measures as important: time to definitive care, response time, reduction in pain score, calls correctly prioritised to appropriate levels of response, proportion of patients with a specific condition who are treated in accordance with established guidelines, and survival to hospital discharge for treatable emergency conditions. From this we developed six new potential indicators using the linked data set, of which five were constructed using case-mix-adjusted predictive models: (1) mean change in pain score; (2) proportion of serious emergency conditions correctly identified at the time of the 999 call; (3) response time (unadjusted); (4) proportion of decisions to leave a patient at scene that were potentially inappropriate; (5) proportion of patients transported to the emergency department by 999 emergency ambulance who did not require treatment or investigation(s); and (6) proportion of ambulance patients with a serious emergency condition who survive to admission, and to 7 days post admission. Two indicators (pain score and response times) did not need case-mix adjustment. Among the four adjusted indicators, we found that accuracy of call triage was 61%, rate of potentially inappropriate decisions to leave at home was 5–10%, unnecessary transport to hospital was 1.7–19.2% and survival to hospital admission was 89.5–96.4% depending on Clinical Commissioning Group area. We were unable to complete a fourth objective to test the indicators in use because of delays in obtaining data. An economic analysis using indicators (4) and (5) showed that incorrect decisions resulted in higher costs. Limitations Creation of a linked data set was complex and time-consuming and data quality was variable. Construction of the indicators was also complex and revealed the effects of other services on outcome, which limits comparisons between services. Conclusions We identified and prioritised, through consensus processes, a set of potential ambulance service quality measures that reflected preferences of services and users. Together, these encompass a broad range of domains relevant to the population using the emergency ambulance service. The quality measures can be used to compare ambulance services or regions or measure performance over time if there are improvements in mechanisms for linking data across services. Future work The new measures can be used to assess different dimensions of ambulance service delivery but current data challenges prohibit routine use. There are opportunities to improve data linkage processes and to further develop, validate and simplify these measures. Funding The National Institute for Health Research Programme Grants for Applied Research programme

Developing and evaluating packages to support implementation of quality indicators in general practice : the ASPIRE research programme, including two cluster RCTs

This is the final version. Available from the NIHR Journals Library via the DOI in this recordData-sharing statement: All data requests should be submitted to the corresponding author for consideration. Access to anonymised data may be granted following review.Background Dissemination of clinical guidelines is necessary but seldom sufficient by itself to ensure the reliable uptake of evidence-based practice. There are further challenges in implementing multiple clinical guidelines and clinical practice recommendations in the pressurised environment of general practice. Objectives We aimed to develop and evaluate an implementation package that could be adapted to support the uptake of a range of clinical guideline recommendations and be sustainably integrated within general practice systems and resources. Over five linked work packages, we developed ‘high-impact’ quality indicators to show where a measurable change in clinical practice can improve patient outcomes (work package 1), analysed adherence to selected indicators (work package 2), developed an adaptable implementation package (work package 3), evaluated the effects and cost-effectiveness of adapted implementation packages targeting four indicators (work package 4) and examined intervention fidelity and mechanisms of action (work package 5). Setting and participants Health-care professionals and patients from general practices in West Yorkshire, UK. Design We reviewed recommendations from existing National Institute for Health and Care Excellence clinical guidance and used a multistage consensus process, including 11 professionals and patients, to derive a set of ‘high-impact’ evidence-based indicators that could be measured using routinely collected data (work package 1). In 89 general practices that shared data, we found marked variations and scope for improvement in adherence to several indicators (work package 2). Interviews with 60 general practitioners, practice nurses and practice managers explored perceived determinants of adherence to selected indicators and suggested the feasibility of adapting an implementation package to target different indicators (work package 3). We worked with professional and patient panels to develop four adapted implementation packages. These targeted risky prescribing involving non-steroidal anti-inflammatory and antiplatelet drugs, type 2 diabetes control, blood pressure control and anticoagulation for atrial fibrillation. The implementation packages embedded behaviour change techniques within audit and feedback, educational outreach and (for risky prescribing) computerised prompts. We randomised 178 practices to implementation packages targeting either diabetes control or risky prescribing (trial 1), or blood pressure control or anticoagulation (trial 2), or to a further control (non-intervention) group, and undertook economic modelling (work package 4). In trials 1 and 2, practices randomised to the implementation package for one indicator acted as control practices for the other package, and vice versa. A parallel process evaluation included a further eight practices (work package 5). Main outcome measures Trial primary end points at 11 months comprised achievement of all recommended levels of glycated haemoglobin, blood pressure and cholesterol; risky prescribing levels; achievement of recommended blood pressure; and anticoagulation prescribing. Results We recruited 178 (73%) out of 243 eligible general practices. We randomised 80 practices to trial 1 (40 per arm) and 64 to trial 2 (32 per arm), with 34 non-intervention controls. The risky prescribing implementation package reduced risky prescribing (odds ratio 0.82, 97.5% confidence interval 0.67 to 0.99; p = 0.017) with an incremental cost-effectiveness ratio of £2337 per quality-adjusted life-year. The other three packages had no effect on primary end points. The process evaluation suggested that trial outcomes were influenced by losses in fidelity throughout intervention delivery and enactment, and by the nature of the targeted clinical and patient behaviours. Limitations Our programme was conducted in one geographical area; however, practice and patient population characteristics are otherwise likely to be sufficiently diverse and typical to enhance generalisability to the UK. We used an ‘opt-out’ approach to recruit general practices to the randomised trials. Subsequently, our trial practices may have engaged with the implementation package less than if they had actively volunteered. However, this approach increases confidence in the wider applicability of trial findings as it replicates guideline implementation activities under standard conditions. Conclusions This pragmatic, rigorous evaluation indicates the value of an implementation package targeting risky prescribing. In broad terms, an adapted ‘one-size-fits-all’ approach did not consistently work, with no improvement for other targeted indicators. Future work There are challenges in designing ‘one-size-fits-all’ implementation strategies that are sufficiently robust to bring about change in the face of difficult clinical contexts and fidelity losses. We recommend maximising feasibility and ‘stress testing’ prior to rolling out interventions within a definitive evaluation. Our programme has led on to other work, adapting audit and feedback for other priorities and evaluating different ways of delivering feedback to improve patient care.National Institute for Health Research (NIHR

How can we meet the support needs of LGBT cancer patients in oncology? A systematic review

Objectives Approximately 3.6 million people in the UK identify as lesbian, gay, bisexual and transgender (LGBT). Fear of discrimination and lack of sexual orientation and gender identity recording suggests LGBT people are invisible to health services. A systematic review was conducted to critically analyse primary research investigating psychosocial support needs for LGBT cancer patients during and after treatment. Key findings Twenty studies were included in the review; of which ten were qualitative, seven quantitative and three mixed methods. The main themes highlighted include health care professional knowledge and education, negative impact on mental health, lack of inclusive support groups, prevalence of discrimination within healthcare services and the disclosure or non-disclosure of sexual orientation and gender identity. Conclusion The review highlights how healthcare providers are failing LGBT cancer patients in psychosocial support resulting in unmet needs. Recommendations have been made to ensure an LGBT inclusive environment within cancer services, as well as the need to develop support services for LGBT cancer patients. Implications for practice Training should be provided for HCP staff in LGBT health and awareness. Sexual orientation and gender identity recording and monitoring is important to ensure LGBT people are not ‘invisible’ in oncology, radiotherapy and in future research. LGBT cancer support groups and resources should be created, as the review evidence suggests LGBT patients are actively looking for these resources