The impact of neurological disorders on healthcare for children and young people

Introduction Neurological conditions are a major and increasing cause of hospitalisation among children and young people, but little is known about the impact of neurological conditions on hospital services in England, nor the factors that influence length of stay and bed days per year. Objectives To quantify the hospital usage in children and young people related to neurological conditions, trends over time and variation by ethnicity and deprivation status. Methods An ICD10 coding framework identified a cohort of individuals aged 0-19 years with neurological conditions from linked routinely collected healthcare data from England (The Hospital Episode Statistics Admitted Patient Care dataset), from 1 April 2003 to 31 March 2015. Linked outpatient and accident and emergency data were used to supplement missing demographic data. Length of stay and bed days per year per person were calculated. These were separately modelled using random intercept multivariable negative binomial regressions with gender, age, ethnic group, diagnostic group, region of residence and deprivation category as predictors. Results 524,442 individuals were identified over the study period, increasing from 49,928 in 2003/04 to 102,840 in 2014/15. Neurological conditions account for 8.8% of inpatient bed days in the 0-14 year old age group. Length of stay and bed days per year vary primarily by age group – e.g. Under 1 year olds had 1.85 times (95%CI 1.83-1.86%) longer stays and over double (2.36 times, 95%CI 2.34-2.37 times) the number of bed days per person per year compared to 5 to 9 year olds – and main diagnostic group, with smaller variations by ethnic group, deprivation and region. Conclusions Neurological conditions in children and young people have a significant and increasing impact on the NHS in England. Falls in length of stay and bed days per person are more than offset by increasing numbers of children and young people with neurological diagnoses. Variations in length of stay and bed days per year by diagnostic group, ethnic group, age group, deprivation category and region should be taken into account in resource planning

Understanding the medical complexity of children and young people with life-limiting conditions in Wales using linked, routinely collected healthcare data

Objectives To better understand the complexity and healthcare needs of children and young people in Wales with life-limiting or life threatening conditions to better plan and target healthcare services. Previous attempts to quantify complexity have required primary data collection; this is not feasible at scale, use of existing data is preferred. Methods Routinely collected healthcare and administrative data were linked: primary care data, hospital care data sets, cancer and congenital anomaly registries, paediatric intensive care audit data and death records. Children and young people with life-limiting conditions were identified using a previously developed diagnostic framework. Previous work on conceptualising medical complexity across eight domains was operationalised for the first time using the wide range of available data, with scores across five domains and a total complexity score. The relationship between the complexity score, healthcare use, stage of condition and category of condition was explored. Results Children and young people with life-limiting conditions showed the full range of medical complexity scores, from zero to five, with distributions varying across age groups with increasing complexity at greater ages. Distributions also varied across categories of condition, with congenital and oncology conditions, although among the most prevalent, exhibiting lower medical complexity. Nonetheless, all conditions showed a range of complexities – there were no conditions for which all individuals were either high or low complexity. Complexity scores were correlated with stage of condition and healthcare use and may be used to identify groups likely to have higher healthcare demand or greater risk of clinical instability. While life-limiting conditions were more prevalent in areas of higher deprivation, there was no association between deprivation and medical complexity. Conclusion Assessment of medical complexity from routinely-collected data can be useful in better understanding a population and in targeting and planning care, without requiring additional data collection. This can help to design resilient services that prepare for changing needs and aid targeting of limited resources

Inequalities in emergency care use across transition from paediatric to adult care : a retrospective cohort study of young people with chronic kidney disease in England

Transition of young people with chronic kidney disease (CKD) from paediatric to adult healthcare has been associated with poor outcomes, but few population-level studies examine trends in subgroups. We aimed to assess sociodemographic inequalities in changes in unplanned secondary care utilisation occurring across transfer to adult care for people with CKD in England. A cohort was constructed from routine healthcare administrative data in England of young people with childhooddiagnosed CKD who transitioned to adult care. The primary outcome was the number of emergency inpatient admissions and accident and emergency department (A&E) attendances per person year, compared before and after transfer. Injury-related and maternity admissions were excluded. Outcomes were compared via sociodemographic data using negative binomial regression with random effects. The cohort included 4505 individuals. Controlling for age, birth year, age at transfer, region and sociodemographic factors, transfer was associated with a significant decrease in emergency admissions (IRR 0.75, 95% CI 0.64–0.88) and no significant change in A&E attendances (IRR 1.10, 95% CI 0.95–1.27). Female sex was associated with static admissions and increased A&E attendances with transfer, with higher admissions and A&E attendances compared to males pre-transfer. Non-white ethnicities and higher deprivation were associated with higher unplanned secondary care use. Conclusion: Sociodemographic inequalities in emergency secondary care usage were evident in this cohort across the transition period, independent of age, with some variation between admissions and A&E use, and evidence of effect modification by transfer. Such inequalities likely have multifactorial origin, but importantly, could represent differential meetings of care needs

GPs’ role in caring for children and young people with life-limiting conditions: a retrospective cohort study

Background: GPs are rarely actively involved in healthcare provision for children and young people (CYP) with life-limiting conditions (LLCs). This raises problems when these children develop minor illness or require management of other chronic diseases. Aim: To investigate the association between GP attendance patterns and hospital urgent and emergency care use. Design and setting: Retrospective cohort study using a primary care data source (Clinical Practice Research Datalink) in England. The cohort numbered 19 888. Method: CYP aged 0–25 years with an LLC were identified using Read codes (primary care) or International Classification of Diseases 10 th Revision (ICD-10) codes (secondary care). Emergency inpatient admissions and accident and emergency (A&E) attendances were separately analysed using multivariable, two-level random intercept negative binomial models with key variables of consistency and regularity of GP attendances. Results: Face-to-face GP surgery consultations reduced, from a mean of 7.12 per person year in 2000 to 4.43 in 2015. Those consulting the GP less regularly had 15% (95% confidence interval [CI] = 10% to 20%) more emergency admissions and 5% more A&E visits (95% CI = 1% to 10%) than those with more regular consultations. CYP who had greater consistency of GP seen had 10% (95% CI = 6% to 14%) fewer A&E attendances but no significant difference in emergency inpatient admissions than those with lower consistency. Conclusion: There is an association between GP attendance patterns and use of urgent secondary care for CYP with LLCs, with less regular GP attendance associated with higher urgent secondary healthcare use. This is an important area for further investigation and warrants the attention of policymakers and GPs, as the number of CYP with LLCs living in the community rises

Numbers, characteristics, and medical complexity of children with life-limiting conditions reaching age of transition to adult care in England: a repeated cross-sectional study [version 1; peer review: 2 approved]

Background: The number of children with life-limiting conditions in England is known to be increasing, which has been attributed in part to increased survival times. Consequently, more of these young people will reach ages at which they start transitioning to adult healthcare (14-19 years). However, no research exists that quantifies the number of young people with life-limiting conditions in England reaching transition ages or their medical complexity, both essential data for good service planning. Methods: National hospital data in England (Hospital Episode Statistics) from NHS Digital were used to identify the number of young people aged 14-19 years from 2012/13 to 2018/19 with life-limiting conditions diagnosed in childhood. The data were assessed for indicators of medical complexity: number of conditions, number of main specialties of consultants involved, number of hospital admissions and Accident & Emergency Department visits, length of stay, bed days and technology dependence (gastrostomies, tracheostomies). Overlap between measures of complexity was assessed. Results: The number of young people with life-limiting conditions has increased rapidly over the study period, from 20363 in 2012/13 to 34307 in 2018/19. There was evidence for increased complexity regarding the number of conditions and number of distinct main specialties of consultants involved in care, but limited evidence of increases in average healthcare use per person or increased technology dependence. The increasing size of the group meant that healthcare use increased overall. There was limited overlap between measures of medical complexity. Conclusions: The number of young people with life-limiting conditions reaching ages at which transition to adult healthcare should take place is increasing rapidly. Healthcare providers will need to allocate resources to deal with increasing healthcare demands and greater complexity. The transition to adult healthcare must be managed well to limit impacts on healthcare resource use and improve experiences for young people and their families

Estimation of age of transition from children's to adult healthcare for young people with long term conditions using linked routinely collected healthcare data

INTRODUCTION: Healthcare transitions, including from paediatric to adult services, can be disruptive and cause a lack of continuity in care. Existing research on the paediatric-adult healthcare transition often uses a simple age cut-off to assign transition status. This risks misclassification bias, reducing observed changes at transition (adults are included in the paediatric group and vice versa) possibly to differing extents between groups that transition at different ages. OBJECTIVE: To develop and assess methods for estimating the transition point from paediatric to adult healthcare from routine healthcare records. METHODS: A retrospective cohort of young people (12 to 23 years) with long term conditions was constructed from linked primary and secondary care data in England. Inpatient and outpatient records were classified as paediatric or adult based on treatment and clinician specialities. Transition point was estimated using three methods based on record classification (First Adult: the date of first adult record; Last Paediatric: date of last paediatric record; Fitted: a date determined by statistical fitting). Estimated transition age was compared between methods. A simulation explored impacts of estimation approaches compared to a simple age cut-off when assessing associations between transition status and healthcare events. RESULTS: Simulations showed using an age-based cut-off at 16 or 18 years as transition point, common in research on transition, may underestimate transition-associated changes. Many health records for those aged <14 years were classified as adult, limiting utility of the First Adult approach. The Last Paediatric approach is least sensitive to this possible misclassification and may best reflect experience of the transition. CONCLUSIONS: Estimating transition point from routine healthcare data is possible and offers advantages over a simple age cut-off. These methods, adapted as necessary for data from other countries, should be used to reduce risk of misclassification bias in studies of transition in nationally representative data