UK Doctors united

No description supplie

Teaching and training for general practice: a Dutch academic success story

No description supplie

Understanding barriers to women seeking and receiving help for perinatal mental health problems in UK general practice: development of a questionnaire

Aim To develop a questionnaire to measure quantitatively barriers and facilitators to women’s disclosure of perinatal mental health problems in UK primary care. To pilot and evaluate the questionnaire for content validity and internal consistency. Background Around 15% of women develop a mental illness in the perinatal period, such as depression, anxiety or PTSD. In the United Kingdom, 90% of these women will be cared for in primary care, yet currently in as many as 50% of cases, no discussion of this issue takes place. One reason for this is that women experience barriers to disclosing symptoms of perinatal mental illness in primary care. These have previously been explored qualitatively, but no tool currently exists with which to measure these barriers quantitatively. Methods Questionnaire items, drawn from qualitative literature and accounts of women’s experiences, were identified, refined iteratively, and arranged in themes. The questionnaire was piloted using cognitive debriefing interviews to establish content validity. Women completed a refined version online. Responses were analysed using descriptive statistics. Internal consistency of subscales was calculated using Cronbach’s alpha. Findings Cognitive debriefing interviews with five women showed the majority of questionnaire items were relevant, appropriate and easy to understand. The final questionnaire was completed by 71 women, and the majority of subscales had good internal consistency. The barrier scoring most highly was fear and stigma, followed by willingness to seek help and logistics of attending an appointment. Family/partner support and GPs’ reaction were the lowest scoring barriers. Factors facilitating disclosure were GPs being empathetic and non-judgemental, and listening during discussions. In the future this questionnaire can be used to examine which barriers are most important for particular groups of women. This may enable development of strategies to improve acknowledgement and discussion, and prevent under-recognition and under-treatment, of perinatal mental health problems in primary care

Low-dose naltrexone as a treatment for chronic fatigue syndrome

Naltrexone is used as an off-label treatment in low doses for several chronic immune-modulated disorders in many countries. Although only small-scale clinical trials have been performed, these suggest efficacy in several diseases including Crohn’s disease, fibromyalgia and Gulf War Illness. Despite numerous internet reports of response to low-dose naltrexone (LDN), no clinical trials exist in people with chronic fatigue syndrome. This condition is characterised by chronic profound fatigue, postexertional malaise, pain and autonomic and neurocognitive disturbances. This series of three case reports compiled by people with long-term ill-health due to chronic fatigue syndrome shows the range of responses they observed when taking LDN, from life changing to a reduction in some symptoms only. Treatment doses ranged from 4 to 12 mg. Clinical trials may be warranted to explore the potential use of naltrexone in people with these debilitating illnesses which currently have no licensed treatments available

Identification and management of frail patients in English primary care: an analysis of the General Medical Services 2018/2019 contract dataset

Objectives - The aim of this study was to explore the extent of implementation of the General Medical Services 2018/2019 ‘frailty identification and management’ contract in general practitioner (GP) practices in England, and link implementation outcomes to a range of practice and Clinical Commissioning Group (CCG) factors. Design - A cross-sectional study design using publicly available datasets relating to the year 2018 for all GP practices in England. Settings - English general practices. Data - The analysis was conducted across 6632 practices in 193 CCGs with 9 995 558 patients aged 65 years or older. Outcomes - Frailty assessment rates, frailty coding rates and frailty prevalence rates, plus rates of medication reviews, falls assessments and enriched Summary Care Records (SCRs). Analysis - Summary statistics were calculated and multilevel negative binomial regression analysis was used to investigate relationships of the six outcomes with explanatory factors. Results - 14.3% of people aged 65 years or older were assessed for frailty, with 35.4% of these—totalling 5% of the eligible population—coded moderately or severely frail. 59.2% received a medications review, but rates of falls assessments (3.7%) and enriched SCRs (21%) were low. However, percentages varied widely across practices and CCGs. Practice differences in contract implementation were most strongly accounted for by their grouping within CCGs, with weaker but still important associations with some practice and CCG factors, particularly healthcare demand-related factors of chronic caseload and (negatively) % of patients aged 65 years or older. Conclusion - CCG appears the strongest determinant of practice engagement with the frailty contract, and fuller implementation may depend on greater engagement of CCGs themselves, particularly in commissioning suitable interventions. Practices understandably targeted frailty assessments at patients more likely to be found severely frail, resulting in probable underidentification of moderately frail individuals who might benefit most from early interventions. Frailty prevalence estimates based on the contract data may not reflect actual rates

Identification and management of frailty in english primary care: a qualitative study of national policy

Background: Policymakers are directing attention to addressing the needs of an ageing population. Since 2017, general practices in England have been contractually required to identify and code ‘frailty’ as a new clinical concept and, in doing so, support targeted management for this population with the aim of improving outcomes. However, embedding frailty policies into routine practice is not without challenges and little is currently known about the success of the programme. Aim: To explore the implementation of a national policy on frailty identification and management in English primary care. Design & setting; Qualitative study entailing interviews with primary care professionals in the North of England. Method: Semi-structured interviews were conducted with GPs (n = 10), nurses (n = 6), practice managers (n = 3), and health advisors (n = 3). Normalisation process theory (NPT) and ‘system thinking’ provided sensitising frameworks to support data collection and analysis. Results: Primary care professionals were starting to use the concept of frailty to structure care within practices and across organisations; however, there was widespread concern about the challenge of providing expanded care for the identified needs with existing resources. Concerns were also expressed around how best to identify the frail subpopulation and the limitations of current tools for this, and there was a professional reticence to use the term ‘frailty’ with patients. Conclusion: Findings suggests that additional, focused resources and the development of a stronger evidence base are essential to facilitate professional engagement in policies to improve the targeted coding and management of frailty in primary care

The challenge of ageing populations and patient frailty: can primary care adapt?

Health care systems worldwide are having to adapt to ageing populations and increasing numbers of older people with frailty with complex health and social needs, and in the UK primary care is at the frontline of policy attempts to meet this challenge, but achieving the goal of making frailty an integral part of primary care practice is not without considerable challenge

Identifying undetected dementia in UK primary care patients: a retrospective case-control study comparing machine-learning and standard epidemiological approaches

Background Identifying dementia early in time, using real world data, is a public health challenge. As only two-thirds of people with dementia now ultimately receive a formal diagnosis in United Kingdom health systems and many receive it late in the disease process, there is ample room for improvement. The policy of the UK government and National Health Service (NHS) is to increase rates of timely dementia diagnosis. We used data from general practice (GP) patient records to create a machine-learning model to identify patients who have or who are developing dementia, but are currently undetected as having the condition by the GP. Methods We used electronic patient records from Clinical Practice Research Datalink (CPRD). Using a case-control design, we selected patients aged >65y with a diagnosis of dementia (cases) and matched them 1:1 by sex and age to patients with no evidence of dementia (controls). We developed a list of 70 clinical entities related to the onset of dementia and recorded in the 5 years before diagnosis. After creating binary features, we trialled machine learning classifiers to discriminate between cases and controls (logistic regression, naïve Bayes, support vector machines, random forest and neural networks). We examined the most important features contributing to discrimination. Results The final analysis included data on 93,120 patients, with a median age of 82.6 years; 64.8% were female. The naïve Bayes model performed least well. The logistic regression, support vector machine, neural network and random forest performed very similarly with an AUROC of 0.74. The top features retained in the logistic regression model were disorientation and wandering, behaviour change, schizophrenia, self-neglect, and difficulty managing. Conclusions Our model could aid GPs or health service planners with the early detection of dementia. Future work could improve the model by exploring the longitudinal nature of patient data and modelling decline in function over time

Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis

Background Primary care provides the foundation for most modern health-care systems, and in the interests of equity, it should be resourced according to local need. We aimed to describe spatially the burden of chronic conditions and primary medical care funding in England at a low geographical level, and to measure how much variation in funding is explained by chronic condition prevalence and other patient and regional factors. Methods We used multiple administrative data sets including chronic condition prevalence and management data (2014/15), funding for primary-care practices (2015-16), and geographical and area deprivation data (2015). Data were assigned to a low geographical level (average 1500 residents). We investigated the overall morbidity burden across 19 chronic conditions and its regional variation, spatial clustering and association with funding and area deprivation. A linear regression model was used to explain local variation in spending using patient demographics, morbidity, deprivation and regional characteristics. Results Levels of morbidity varied within and between regions, with several clusters of very high morbidity identified. At the regional level, morbidity was modestly associated with practice funding, with the North East and North West appearing underfunded. The regression model explained 39% of the variability in practice funding, but even after adjusting for covariates, a large amount of variability in funding existed across regions. High morbidity and, especially, rural location were very strongly associated with higher practice funding, while associations were more modest for high deprivation and older age. Conclusions Primary care funding in England does not adequately reflect the contemporary morbidity burden. More equitable resource allocation could be achieved by making better use of routinely available information and big data resources. Similar methods could be deployed in other countries where comparable data are collected, to identify morbidity clusters and to target funding to areas of greater need

Understanding the implementation of interventions to improve the management of frailty in primary care: a rapid realist review

OBJECTIVE: Identifying and managing the needs of frail people in the community is an increasing priority for policy makers. We sought to identify factors that enable or constrain the implementation of interventions for frail older persons in primary care. DESIGN: A rapid realist review. DATA SOURCES: Cochrane Library, SCOPUS and EMBASE, and grey literature. The search was conducted in September 2019 and rerun on 8 January 2022. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: We considered all types of empirical studies describing interventions targeting frailty in primary care. ANALYSIS: We followed the Realist and Meta-narrative Evidence Syntheses: Evolving Standards quality and publication criteria for our synthesis to systematically analyse and synthesise the existing literature and to identify (intervention-context-mechanism-outcome) configurations. We used normalisation processes theory to illuminate mechanisms surrounding implementation. RESULTS: Our primary research returned 1755 articles, narrowed down to 29 relevant frailty intervention studies conducted in primary care. Our review identified two families of interventions. They comprised: (1) interventions aimed at the comprehensive assessment and management of frailty needs; and (2) interventions targeting specific frailty needs. Key factors that facilitate or inhibit the translation of frailty interventions into practice related to the distribution of resources; patient engagement and professional skill sets to address identified need. CONCLUSION: There remain challenges to achieving successful implementation of frailty interventions in primary care. There were a key learning points under each family. First, targeted allocation of resources to address specific needs allows a greater alignment of skill sets and reduces overassessment of frail individuals. Second, earlier patient involvement may also improve intervention implementation and adherence