IntroductionStroke registries are used in many settings to measure stroke treatment and outcomes, but rarely include data on health economic outcomes. We aimed to extend the Sentinel Stroke National Audit Programme registry of England, Wales and Northern Ireland to derive and report patient-level estimates of the cost of stroke care.MethodsAn individual patient simulation model was built to estimate health and social care costs at one and five years after stroke, and the cost-benefits of thrombolysis and early supported discharge. Costs were stratified according to age, sex, stroke type (ischaemic or primary intracerebral haemorrhage) and stroke severity. The results were illustrated using data on all patients with stroke included in Sentinel Stroke National Audit Programme from April 2015 to March 2016 (n = 84,184).ResultsThe total cost of health and social care for patients with acute stroke each year in England, Wales and Northern Ireland was £3.60 billion in the first five years after admission (mean per patient cost: £46,039). There was fivefold variation in the magnitude of costs between patients, ranging from £19,101 to £107,336. Costs increased with older age, increasing stroke severity and intracerebral hemorrhage stroke. Increasing the proportion of eligible patients receiving thrombolysis or early supported discharge was estimated to save health and social care costs by five years after stroke.DiscussionThe cost of stroke care is large and varies widely between patients. Increasing the proportion of eligible patients receiving thrombolysis or early supported discharge could contribute to reducing the financial burden of stroke.ConclusionExtending stroke registers to report individualised data on costs may enhance their potential to support quality improvement and research.
The coronavirus (COVID-19) pandemic has had a profound impact on people receiving social care. As of July 2020, there have been over 30,500 more deaths among care home residents in England than we would normally expect. A further 4,500 excess deaths have been reported among people receiving domiciliary social care. Briefing: Adult social care and COVID-19 2 • We found that while discharges from hospitals to residential care homes were 75% of the historical average, discharges from hospitals to nursing homes increased to 120% of the historical average. • During March and April, similar to the general population, there was a substantial reduction in hospital admissions among care home residents. Elective admissions reduced to 58% of the 5-year historical average during this period and emergency admissions to 85% of the 5-year historical average. During this time, 14% of admissions had COVID-19 as the primary cause. By reducing admissions, care home and NHS teams may have reduced the risk of transmission. There may have also been an increase in unmet health needs but the data currently available do not allow us to assess whether this was the case. • Long-standing structural issues have exacerbated the crisis in social care and hindered the response to the pandemic. But action is needed to prevent further harm, and this includes the need for data to fill the gaps highlighted in this briefing. Many of the most pressing data gaps concern domiciliary care, as it is not currently possible to track and understand the spread of infection in these settings. We also need more data on the health and care needs accumulated during the pandemic, and how well social care users are able to access essential services. • The Health Foundation is undertaking a wider programme of work to improve social care data. Our work so far has pointed to deep-rooted structural and cultural challenges that impact how data are collected, shared and used. A new data strategy is needed for social care that first and foremost enables the provision of better care. * Proportions have changed substantially since, but in May, this ranged from 26% in England and Wales to 66% in Spain, as reported in Eurosurveillance in a comparison of European/European Economic Area (EEA) countries: www.
Background The COVID-19 pandemic has had a significant impact on primary care service delivery with an increased use of remote consultations. With general practice delivering record numbers of appointments and rising concerns around access, funding, and staffing in the UK National Health Service, we assessed contemporary trends in consultation rate and modes (ie, face-to-face versus remote). Objective This paper describes trends in consultation rates in general practice in England for key demographics before and during the COVID-19 pandemic. We explore the use of remote and face-to-face consultations with regard to socioeconomic deprivation to understand the possible effect of changes in consultation modes on health inequalities. Methods We did a retrospective analysis of 9,429,919 consultations by general practitioners, nurses, or other health care professionals between March 2018 and February 2022 for patients registered at 397 general practices in England. We used routine electronic health records from Clinical Practice Research Datalink Aurum with linkage to national data sets. Negative binomial models were used to predict consultation rates and modes (ie, remote versus face-to-face) by age, sex, and socioeconomic deprivation over time. Results Overall consultation rates increased by 15% from 4.92 in 2018-2019 to 5.66 in 2021-2022 with some fluctuation during the start of the COVID-19 pandemic. The breakdown into face-to-face and remote consultations shows that the pandemic precipitated a rapid increase in remote consultations across all groups, but the extent varies by age. Consultation rates increased with increasing levels of deprivation. Socioeconomic differences in consultation rates, adjusted for sex and age, halved during the pandemic (from 0.36 to 0.18, indicating more consultations in the most deprived), effectively narrowing relative differences between deprivation quintiles. This trend remains when stratified by sex, but the difference across deprivation quintiles is smaller for men. The most deprived saw a relatively larger increase in remote and decrease in face-to-face consultation rates compared to the least deprived. Conclusions The substantial increases in consultation rates observed in this study imply an increased pressure on general practice. The narrowing of consultation rates between deprivation quintiles is cause for concern, given ample evidence that health needs are greater in more deprived areas.
Background The COVID-19 pandemic has severely impacted healthcare delivery and there are growing concerns that the pandemic will accelerate antimicrobial resistance. Objectives To evaluate the impact of the COVID-19 pandemic on antibiotic prescribing in a tertiary paediatric hospital in London, UK. Methods Data on patient characteristics and antimicrobial administration for inpatients treated between 29 April 2019 and Sunday 28 March 2021 were extracted from the electronic health record (EHR). Interrupted time series analysis was used to evaluate antibiotic days of therapy (DOT) and the proportion of prescribed antibiotics from the WHO ‘Access’ class. Results A total of 23 292 inpatient admissions were included. Prior to the pandemic there were an average 262 admissions per week compared with 212 during the pandemic period. Patient demographics were similar in the two periods but there was a shift in the specialities that patients had been admitted to. During the pandemic, there was a crude increase in antibiotic DOTs, from 801 weekly DOT before the pandemic to 846. The proportion of Access antibiotics decreased from 44% to 42%. However, after controlling for changes in patient characteristics, there was no evidence for the pandemic having an impact on antibiotic prescribing. Conclusions The patient population in a specialist children’s hospital was affected by the COVID-19 pandemic, but after adjusting for these changes there was no evidence that antibiotic prescribing was significantly affected by the pandemic. This highlights both the value of routine, high-quality EHR data and importance of appropriate statistical methods that can adjust for underlying changes to populations when evaluating impacts of the pandemic on healthcare.
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