How did the first covid-19 lockdown affect general practitioner contacts with children and young people?

AimsTo examine the impact of the covid-19 pandemic on total, face to face and remote general practitioner (GP) contacts with children and young people aged under 25 years in England before and after the first lockdown in the United Kingdom (March to June 2020).MethodsLongitudinal trends analysis using electronic health records from the nationally representative Clinical Practice Research Datalink Aurum database. We included all children and young people aged <25 years registered with a GP anytime during the study period (January 2015 to October 2020). We assigned their GP contacts according to their age (years) on the date of the contact: <1, 1-4, 5-9, 10-14, 15-19, 20-24.Our main outcomes were total, face-to-face and remote weekly contacts with a GP. Secondary outcomes were weekly contacts with GPs for respiratory illnesses (upper respiratory tract infections, lower respiratory tract infections and asthma) and common non-transmissible conditions (urinary tract infections, diabetes, epilepsy and appendicitis). For all outcomes, we compared the number of contacts during the first UK lockdown (March to June 2020) with the mean number of contacts for comparable weeks from 2015 to 2019.ResultsOur study population included 4 307 120 million children and young people who had 47 607 765 GP contacts. Total GP contacts fell by 40.7% (95% CI: 40.7, 40.8) during the first lockdown compared with previous years. Children aged 1-14 years had greater falls in total contacts (>50%) compared with infants and those aged 15-24 years. Face-to-face contacts fell by 88.3% (95% CI: 88.2, 88.4) for all ages. The greatest falls in face-to-face contacts occurred among children aged 1-14 (> 90%), whereas face-to-face contacts with infants fell by 76.8% (95% CI: 76.6, 77.0). Remote contacts more than doubled, increasing most in infants (over 2.5 fold). Total contacts for respiratory illnesses fell by 74% whereas contacts for common non-transmissible conditions shifted largely to remote and fell by 31%.ConclusionChildren and young people’s contact with GPs fell, particularly for face-to-face assessment during the first pandemic lockdown, with notably fewer contacts for respiratory illnesses. This change reflects a combination of altered healthcare seeking behaviour, lower prevalence of some conditions (notably fewer respiratory illnesses due to fewer social contacts), and changes in service provision. A major shift from face-to-face to remote contacts for common non-transmissible conditions mitigated overall falls.

Impact of COVID-19 on outpatient appointments in children and young people in England: an observational study.

OBJECTIVES: To describe the impact of the COVID-19 pandemic on outpatient appointments for children and young people. SETTING: All National Health Service (public) hospitals in England. PARTICIPANTS: All people in England aged <25 years. OUTCOME MEASURES: Outpatient department attendance numbers, rates and modes (face to face vs telephone) by age group, sex and socioeconomic deprivation. RESULTS: Compared with the average for January 2017 to December 2019, there was a 3.8 million appointment shortfall (23.5%) for the under-25 population in England between March 2020 and February 2021, despite a total rise in phone appointments of 2.6 million during that time. This was true for each age group, sex and deprivation fifth, but there were smaller decreases in face to face and total appointments for babies under 1 year. For all ages combined, around one in six first and one in four follow-up appointments were by phone in the most recent period. The proportion of appointments attended was high, at over 95% for telephone and over 90% for face-to-face appointments for all ages. CONCLUSIONS: COVID-19 led to a dramatic fall in total outpatient appointments and a large rise in the proportion of those appointments conducted by telephone. The impact that this has had on patient outcomes is still unknown. The differential impact of COVID-19 on outpatient activity in different sociodemographic groups may also inform design of paediatric outpatient services in the post-COVID period.

Factors associated with, and variations in, COVID-19 hospital death rates in England's first two waves: observational study.

OBJECTIVES: To assess patient-level and hospital-level predictors of death and variation in death rates following admission for COVID-19 in England's first two waves after accounting for random variation. To quantify the correlation between hospitals' first and second wave death rates. DESIGN: Observational study using administrative data. SETTING: Acute non-specialist hospitals in England. PARTICIPANTS: All patients admitted with a primary diagnosis of COVID-19. PRIMARY AND SECONDARY OUTCOMES: In-hospital death. RESULTS: Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. In wave 1 (March to July 2020), there were 74 484 admissions and 21 883 deaths (crude rate 29.4%); in wave 2 (August 2020 to March 2021), there were 165 642 admissions and 36 040 deaths (21.8%). Wave 2 patients were younger, with more hypertension and obesity but lower rates of other comorbidities. Mortality improved for all ages; in wave 2, it peaked in December 2020 at 24.2% (lower than wave 1's peak) but halved by March 2021. In multiple multilevel modelling combining HES with hospital-level data from Situational Reports, wave 2 and wave 1 variables significantly associated with death were mostly the same. The median odds ratio for wave 1 was just 1.05 and for wave 2 was 1.07. At 99.8% control limits, 3% of hospitals were high and 7% were low funnel plot outliers in wave 1; these figures were 9% and 12% for wave 2. Four hospitals were (low) outliers in both waves. The correlation between hospitals' adjusted mortality rates between waves was 0.45 (p<0.0001). Length of stay was similar in each wave. CONCLUSIONS: England's first two COVID-19 waves were similar regarding predictors and moderate interhospital variation. Despite the challenges, variation in death rates and length of stay between hospitals was modest and might be accounted for by unobserved patient factors.

Impact of COVID-19 on primary care contacts with children and young people in England: longitudinal trends study 2015-2020.

BACKGROUND: The NHS response to COVID-19 altered provision and access to primary care. AIM: To examine the impact of COVID-19 on GP contacts with children and young people (CYP) in England. DESIGN AND SETTING: A longitudinal trends analysis was undertaken using electronic health records from the Clinical Practice Research Datalink (CPRD) Aurum database. METHOD: All CYP aged <25 years registered with a GP in the CPRD Aurum database were included. The number of total, remote, and face-to-face contacts during the first UK lockdown (March to June 2020) were compared with the mean contacts for comparable weeks from 2015 to 2019. RESULTS: In total, 47 607 765 GP contacts with 4 307 120 CYP were included. GP contacts fell 41% during the first lockdown compared with previous years. Children aged 1-14 years had greater falls in total contacts (≥50%) compared with infants and those aged 15-24 years. Face-to-face contacts fell by 88%, with the greatest falls occurring among children aged 1-14 years (>90%). Remote contacts more than doubled, increasing most in infants (over 2.5-fold). Total contacts for respiratory illnesses fell by 74% whereas contacts for common non-transmissible conditions shifted largely to remote contacts, mitigating the total fall (31%). CONCLUSION: During the COVID-19 pandemic, CYP's contact with GPs fell, particularly for face-to-face assessments. This may be explained by a lower incidence of respiratory illnesses because of fewer social contacts and changing health-seeking behaviour. The large shift to remote contacts mitigated total falls in contacts for some age groups and for common non-transmissible conditions.

The use of, and outcomes for, inflammatory bowel disease services during the Covid-19 pandemic: a nationwide observational study.

BACKGROUND: Inflammatory bowel disease (IBD) services have been particularly affected by the Covid-19 pandemic. Delays in referral to secondary care and access to investigations and surgery have been exacerbated. AIMS: To investigate the use of and outcomes for emergency IBD care during the Covid-19 pandemic. METHODS: Nationwide observational study using administrative data for England (2015-2020) comparing cohorts admitted from 1 January 2015, to 31 January 2020 (pre-pandemic) and from 1 February 2020, to 31 January 2021 (pandemic). Autoregressive integrated moving average forecast models were run to estimate the counterfactual IBD admissions and procedures for February 2020 to January 2021. RESULTS: Large decreases in attendances to hospital for emergency treatment were observed for both acute ulcerative colitis (UC, 16.4%) and acute Crohn's disease (CD, 8.7%). The prevalence of concomitant Covid-19 during the same episode was low [391/16 494 (2.4%) and 349/15 613 (2.2%), respectively]. No significant difference in 30-day mortality was observed. A shorter median length of stay by 1 day for acute IBD admissions was observed (P < 0.0001). A higher rate of emergency readmission within 28 days for acute UC was observed (14.1% vs 13.4%, P = 0.012). All IBD procedures and investigations showed decreases in volume from February 2020 to January 2021 compared with counterfactual estimates. The largest absolute deficit was in endoscopy (17 544 fewer procedures, 35.2% reduction). CONCLUSION: There is likely a significant burden of untreated IBD in the community. Patients with IBD may experience clinical harm or protracted decreases in quality of life if care is not prioritised.

Socioeconomic deprivation and ethnicity inequalities in disruption to NHS hospital admissions during the COVID-19 pandemic: a national observational study.

INTRODUCTION: Hospital admissions in many countries fell dramatically at the onset of the COVID-19 pandemic. Less is known about how care patterns differed by patient groups. We sought to determine whether areas with higher levels of socioeconomic deprivation or larger ethnic minority populations saw larger falls in emergency and planned admissions in England. METHODS: We conducted a national observational study of hospital care in the English National Health Service (NHS) in 2019-2020. Weekly volumes of elective (planned) and emergency admissions in 2020 compared with 2019 were calculated for each census area. Multiple linear regression analysis was used to estimate the reductions in volumes for areas in different quintiles of socioeconomic deprivation and ethnic minority populations after controlling for national time trends and local area composition. RESULTS: Between March and December 2020, there were 35.5% (3.0 million) fewer elective admissions and 22.0% (1.2 million) fewer emergency admissions with a non-COVID-19 primary diagnosis than in 2019. Areas with the largest share of ethnic minority populations experienced a 36.7% (95% CI 24.1% to 49.3%) larger reduction in non-primary COVID-19 emergency admissions compared with those with the smallest. The most deprived areas experienced a 10.1% (95% CI 2.6% to 17.7%) smaller reduction in non-COVID-19 emergency admissions compared with the least deprived. These patterns are not explained by differential prevalence of COVID-19 cases by area. CONCLUSIONS: Even in a healthcare system founded on the principle of equal access for equal need, the impact of COVID-19 on NHS hospital care for non-COVID patients has not been spread evenly by ethnicity and deprivation in England. While we cannot conclusively determine the mechanisms behind these differences, they risk exacerbating prepandemic health inequalities.

Capacity planning for acute hospital inpatient care and adult critical care in England: a descriptive study using hospital administrative data

Background At the beginning of the COVID-19 pandemic in March and April, 2020, there was a focus on accommodating an anticipated surge of patients with COVID-19 in acute hospitals. We aimed to estimate the potential for freeing up capacity in acute hospitals in England. Methods In this descriptive study, we used admitted patient and adult critical care records from Hospital Episode Statistics (a database containing details of attendances at National Health Service acute hospitals in England) from 2018/19 to estimate historical numbers of inpatients. Each admission was grouped into emergency, maternity, and elective, with elective split by the presence or absence of cancer in the primary diagnosis. We further stratified the population by age and frailty, which we estimated with an index using International Statistical Classification of Diseases and Related Health Problems (tenth revision) codes in diagnosis fields. We used the (then current) National Institute for Health and Care Excellence (NICE) 2020 guidance on critical care pathways as a framework to examine four scenarios that limited access to beds for specific patient groups. This study was approved by the Secretary of State and the Health Research Authority under Regulation 5 of the Health Service (Control of Patient Information) Regulations 2002 to hold confidential data and analyse them for research purposes (CAG ref 15/CAG/0005). We have approval to use these data for research into the quality and safety of health care, from the London–South East Ethics Committee (REC ref 20/LO/0611). Findings Between April 1, 2018, and March 31, 2019, 8 957 521 adults were admitted (7 372 040 [82·3%] emergency, 295 598 [3·3%] elective with cancer, 850 964 [9·5%] elective without cancer, and 438 919 [4·9%] maternity admissions), and 974 038 critical care episodes were recorded. Our analysis suggested that up to 70% of all acute inpatient beds could be released if only maternity, cancer, and emergency patients younger than 65 years were admitted;if non-frail patients aged 65 years and older were also admitted, 41% of beds could be freed up. Similarly, if only maternity, cancer, and emergency patients younger than 65 years were admitted to critical care beds, that might free up to 56% of adult critical care beds;if non-frail patients aged 65 years and older were also admitted, 30% of critical care beds could be freed up. Interpretation Given a crisis in health-care capacity, it seemed appropriate to model some difficult options based on NICE guidelines. We identified scope for freeing up total acute and critical care beds by postponing elective non-cancer admissions as a short-term measure during the first wave of COVID-19 (March to June, 2020) in England. The NICE guidelines were criticised by patient groups and have since been updated (NG191). Administrative data can inform planning for future crises albeit with limitations on estimating individual patient need, and deep social and ethical considerations. Our estimates were incorporated into a modelling tool for hospital provision during the pandemic. Funding Dr Foster Intelligence.

Patient-level and hospital-level variation and related time trends in COVID-19 case fatality rates during the first pandemic wave in England: multilevel modelling analysis of routine data.

BACKGROUND: A report suggesting large between-hospital variations in mortality after admission for COVID-19 in England attracted much media attention but used crude rates. We aimed to quantify these variations between hospitals and over time during England's first wave (March to July 2020) and assess available patient-level and hospital-level predictors to explain those variations. METHODS: We used administrative data for England, augmented by hospital-level information. Admissions were extracted with COVID-19 codes. In-hospital death was the primary outcome. Risk-adjusted mortality ratios (standardised mortality ratios) and interhospital variation were calculated using multilevel logistic regression. Early-wave (March to April) and late-wave (May to July) periods were compared. RESULTS: 74 781 admissions had a primary diagnosis of COVID-19, with 21 984 in-hospital deaths (29.4%); the 30-day total mortality rate was 28.8%. The crude in-hospital death rate fell in all ages and overall from 32.9% in March to 13.4% in July. Patient-level predictors included age, male gender, non-white ethnic group (early period only) and several comorbidities (obesity early period only). The only significant hospital-level predictor was daily COVID-19 admissions in the late period; we did not find a relation with staff absences for COVID-19, mechanical ventilation bed occupancies, total bed occupancies or bed occupancies for COVID-19 admissions in either period. Just 4 (3%) and 2 (2%) hospitals were high, and 5 (4%) and 0 hospitals were low funnel plot mortality outliers at 3 SD for early and late periods, respectively, after risk adjustment. We found no strong correlation between early and late hospital-level mortality (r=0.17, p=0.06). CONCLUSIONS: There was modest variation in mortality following admission for COVID-19 between English hospitals after adjustment for risk and random variation, in marked contrast to early media reports. Early-period mortality did not predict late-period mortality.

The J-IDEA Pandemic Planner: A Framework for Implementing Hospital Provision Interventions During the COVID-19 Pandemic.

BACKGROUND: Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for coronavirus disease 2019 (COVID-19), while retaining capacity for other emergency conditions, is one of the most challenging tasks faced by health care providers and policymakers during the pandemic. Health systems must be well-prepared to cope with large and sudden changes in demand by implementing interventions to ensure adequate access to care. We developed the first planning tool for the COVID-19 pandemic to account for how hospital provision interventions (such as cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affect the capacity of hospitals to provide life-saving care. METHODS: We conducted a review of interventions implemented or considered in 12 European countries in March to April 2020, an evaluation of their impact on capacity, and a review of key parameters in the care of COVID-19 patients. This information was used to develop a planner capable of estimating the impact of specific interventions on doctors, nurses, beds, and respiratory support equipment. We applied this to a scenario-based case study of 1 intervention, the set-up of field hospitals in England, under varying levels of COVID-19 patients. RESULTS: The Abdul Latif Jameel Institute for Disease and Emergency Analytics pandemic planner is a hospital planning tool that allows hospital administrators, policymakers, and other decision-makers to calculate the amount of capacity in terms of beds, staff, and crucial medical equipment obtained by implementing the interventions. Flexible assumptions on baseline capacity, the number of hospitalizations, staff-to-beds ratios, and staff absences due to COVID-19 make the planner adaptable to multiple settings. The results of the case study show that while field hospitals alleviate the burden on the number of beds available, this intervention is futile unless the deficit of critical care nurses is addressed first. DISCUSSION: The tool supports decision-makers in delivering a fast and effective response to the pandemic. The unique contribution of the planner is that it allows users to compare the impact of interventions that change some or all inputs.

CCopeY: A Mixed-Methods Coproduced Study on the Mental Health Status and Coping Strategies of Young People During COVID-19 UK Lockdown.

PURPOSE: Exploring the impact of the COVID-19 pandemic on young people's mental health is an increasing priority. Studies to date are largely surveys and lack meaningful involvement from service users in their design, planning, and delivery. The study aimed to examine the mental health status and coping strategies of young people during the first UK COVID-19 lockdown using coproduction methodology. METHODS: The mental health status of young people (aged 16-24) in April 2020 was established utilizing a sequential explanatory coproduced mixed methods design. Factors associated with poor mental health status, including coping strategies, were also examined using an online survey and semi-structured interviews. RESULTS: Since the lockdown, 30.3% had poor mental health, and 10.8% had self-harmed. Young people identifying as Black/Black-British ethnicity had the highest increased odds of experiencing poor mental health (odds ratio [OR] 3.688, 95% CI .54-25.40). Behavioral disengagement (OR 1.462, 95% CI 1.22-1.76), self-blame (OR 1.307 95% CI 1.10-1.55), and substance use (OR 1.211 95% CI 1.02-1.44) coping strategies, negative affect (OR 1.109, 95% CI 1.07-1.15), sleep problems (OR .915 95% CI .88-.95) and conscientiousness personality trait (OR .819 95% CI .69-.98) were significantly associated with poor mental health. Three qualitative themes were identified: (1) pre-existing/developed helpful coping strategies employed, (2) mental health difficulties worsened, and (3) mental health and nonmental health support needed during and after lockdown. CONCLUSION: Poor mental health is associated with dysfunctional coping strategies. Innovative coping strategies can help other young people cope during and after lockdowns, with digital and school promotion and application.

Characteristics of frequent paediatric users of emergency departments in England: an observational study using routine national data.

BACKGROUND: Frequent attendances of the same users in emergency departments (ED) can intensify workload pressures and are common among children, yet little is known about the characteristics of paediatric frequent users in EDs. AIM: To describe the volume of frequent paediatric attendance in England and the demographics of frequent paediatric ED users in English hospitals. METHOD: We analysed the Hospital Episode Statistics dataset for April 2014-March 2017. The study included 2 308 816 children under 16 years old who attended an ED at least once. Children who attended four times or more in 2015/2016 were classified as frequent users. The preceding and subsequent years were used to capture attendances bordering with the current year. We used a mixed effects logistic regression with a random intercept to predict the odds of being a frequent user in children from different sociodemographic groups. RESULTS: One in 11 children (9.1%) who attended an ED attended four times or more in a year. Infants had a greater likelihood of being a frequent attender (OR 3.24, 95% CI 3.19 to 3.30 vs 5 to 9 years old). Children from more deprived areas had a greater likelihood of being a frequent attender (OR 1.57, 95% CI 1.54 to 1.59 vs least deprived). Boys had a slightly greater likelihood than girls (OR 1.05, 95% CI 1.04 to 1.06). Children of Asian and mixed ethnic groups were more likely to be frequent users than those from white ethnic groups, while children from black and 'other' had a lower likelihood (OR 1.03, 95% CI 1.01 to 1.05; OR 1.04, 95% CI 1.01 to 1.06; OR 0.88, 95% CI 0.86 to 0.90; OR 0.90, 95% CI 0.87 to 0.92, respectively). CONCLUSION: One in 11 children was a frequent attender. Interventions for reducing paediatric frequent attendance need to target infants and families living in deprived areas.

Adapting hospital capacity to meet changing demands during the COVID-19 pandemic.

BACKGROUND: To calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients. METHODS: We analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators. RESULTS: NHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors. All elective surgery can be conducted at normal pre-pandemic levels provided the other interventions are sustained, but only if the daily number of COVID-19 patients occupying CC beds is not greater than 1550 in the whole of England. If the other interventions are not maintained, then elective surgery can only be conducted if the number of COVID-19 patients occupying CC beds is not greater than 320. However, there is greater national capacity to treat G&A patients: without interventions, it takes almost 10,000 G&A COVID-19 patients before any G&A elective patients would be unable to be accommodated. CONCLUSIONS: Unless COVID-19 hospitalisations drop to low levels, there is a continued need to enhance critical care capacity in England with field hospitals, use of private hospitals or deployment of former and newly qualified medical staff to allow some or all elective surgery to take place.