National Health Service (NHS) 111 helpline was set up to improve access to urgent care in England, efficiency and cost-effectiveness of first-contact health services. Following trusted, authoritative advice is crucial for improved clinical outcomes. We examine patient and call-related characteristics associated with compliance with advice given in NHS 111 calls. The importance of health interactions that are not face-to-face has recently been highlighted by COVID-19 pandemic. In this retrospective cohort study, NHS 111 call records were linked to urgent and emergency care services data. We analysed data of 3,864,362 calls made between October 2013 and September 2017 relating to 1,964,726 callers across London. A multiple logistic regression was used to investigate associations between compliance with advice given and patient and call characteristics. Caller’s action is ‘compliant with advice given if first subsequent service interaction following contact with NHS 111 is consistent with advice given. We found that most calls were made by women (58%), adults aged 30–59 years (33%) and people in the white ethnic category (36%). The most common advice was for caller to contact their General Practitioner (GP) or other local services (18.2%) with varying times scales. Overall, callers followed advice given in 49% of calls. Compliance with triage advice was more likely in calls for children aged <16 years, women, those from Asian/Asian British ethnicity, and calls made out of hours. The highest compliance was among callers advised to self-care without the need to contact any other healthcare service. This is one of the largest studies to describe pathway adherence following telephone advice and associated clinical and demographic features. These results could inform attempts to improve caller compliance with advice given by NHS 111, and as the NHS moves to more hybrid way of working, the lessons from this study are key to the development of remote healthcare services going forward.

The neural bases of altered consciousness in patients with epilepsy during seizures and at rest have raised significant interest in the last decade. This exponential growth has been supported by the parallel development of techniques and methods to investigate brain function noninvasively with unprecedented spatial and temporal resolution. In this article, we review the contribution of magnetoencephalography to deconvolve the bioelectrical changes associated with impaired consciousness during seizures. We use data collected from a patient with refractory absence seizures to discuss how spike-wave discharges are associated with perturbations in optimal connectivity within and between brain regions and discuss indirect evidence to suggest that this phenomenon might explain the cognitive deficits experienced during prolonged 3/s spike-wave discharges.

IntroductionHaving a baby that requires neonatal care is stressful and traumatic. Parents often report dissatisfaction with communication of clinical information. In the UK neonatal care data are recorded daily using electronic patient record systems (EPR), from which deidentified data form the National Neonatal Research Database (NNRD). We aim to evaluate the impact of sharing neonatal EPR data with parents, on parent-reported satisfaction, parent–staff interactions, staff workload and data completeness.MethodsA prospective, before-and-after, mixed-method study. Participants are parents of inpatient babies (maximum 90) and staff in a tertiary neonatal intensive care unit, London, UK. The intervention was developed by former neonatal parents, neonatologists and neonatal nurses: a communication tool for parents comprising individualised, written, daily infant updates for parents, derived from EPR data. The intervention will be provided to parents over 6 weeks. Plan-Do-Study-Act cycles will inform the tool’s iterative development and improvement. The tool’s impact will be measured using a validated parent survey, staff survey, data completeness measures and interviews.AnalysisPrimary outcome: parent satisfaction ‘with communication of clinical information and involvement in care’. Secondary outcomes: parent–staff interactions, staff workload, data completeness. Baseline survey data will be obtained from clinical service evaluation preceding the intervention. Baseline data completeness will be derived from the NNRD. During the intervention, surveys will be administered biweekly and data completeness assessed daily. We will analyse outcomes using run charts and partially paired statistical tests. Parent and staff interviews will explore information exchange and the communication tool’s impact.DiscussionThis study will evaluate the impact of a parent co-designed intervention on communication with parents in neonatal care and the completeness of routinely recorded electronic clinical data. Better use of routinely recorded clinical data provides the opportunity to improve parent satisfaction and increase the research utility of such data, benefiting clinical care.Ethics and disseminationReviewed and approved by the West Midlands—South Birmingham REC (18/WM/0175).Registration numberISRCTN62718241.

Background An ageing population and limited resources have put strain on state provision of adult social care (ASC) in England. With social care needs predicted to double over the next 20 years, there is a need for new approaches to inform service planning and development, including through predictive models of demand. Objective Describe risk factors for long-term ASC in two inner London boroughs and develop a risk prediction model for long-term ASC. Methods Pseudonymised person-level data from an integrated care dataset were analysed. We used multivariable logistic regression to model associations of demographic factors, and baseline aspects of health status and health service use, with accessing long-term ASC over 12 months. Results The cohort comprised 13,394 residents, aged ≥75 years with no prior history of ASC at baseline. Of these, 1.7% became ASC clients over 12 months. Residents were more likely to access ASC if they were older or living in areas with high socioeconomic deprivation. Those with preexisting mental health or neurological conditions, or more intense prior health service use during the baseline period, were also more likely to access ASC. A prognostic model derived from risk factors had limited predictive power. Conclusions Our findings reinforce evidence on known risk factors for residents aged 75 or over, yet even with linked routinely collected health and social care data, it was not possible to make accurate predictions of long-term ASC use for individuals. We propose that a paradigm shift towards more relational, personalised approaches, is needed.