Linked data analysis of learning disability health checks and emergency hospital admissions in the Kent Integrated Dataset

Hospital admissions of school-age children with an intellectual disability: A population-based survey

AIM

To describe the profiles of hospital admissions of school-age children identified with a learning disability (ICD-11 intellectual developmental disorder) and/or safeguarding needs compared to children without learning disability, in a population where proactive identification of learning disabilities in children is embedded in practice.

METHOD

Data were collected about the reasons for and duration of hospital admissions of school-age children living in the study catchment area between April 2017 and March 2019; the presence (or absence) of learning disability and/or safeguarding flags in the medical record was also noted. The impact of the presence of flags on the outcomes was explored using negative binomial regression modelling.

RESULTS

Of 46 295 children in the local population, 1171 (2.53%) had a learning disability flag. The admissions of 4057 children were analysed (1956 females; age range 5-16 years, mean 10 years 6 months, SD 3 years 8 months). Of these, 221 out of 4057 (5.5%) had a learning disability, 443 out of 4057 (10.9%) had safeguarding flags, 43 out of 4057 (1.1%) had both, and 3436 out of 4057 (84.7%) had neither. There was a significantly increased incidence of hospital admissions and length of stay in children with either or both flags, compared to children with neither.

INTERPRETATION

Children with learning disabilities and/or safeguarding needs have higher rates of hospital admissions than children without. Robust identification of learning disabilities in childhood is required to make the needs of this group visible in routinely collected data as the first step towards needs being appropriately addressed.

WHAT THIS PAPER ADDS

Children with learning disabilities must be consistently identified in populations so that their needs are made visible. Information about these needs must be collected from educational, health, and social care sources and scrutinized systematically. Children with learning disabilities and safeguarding needs have an increased incidence of hospital admissions and length of stay.

Factors that affect GP referral of a child with intellectual disability for a mild illness: A discrete choice experiment

BACKGROUND

General practitioners (GP) report multiple challenges when treating individuals with intellectual disabilities which may influence referral rates. The study aimed to establish factors that influence GP's decision-making when referring a child with intellectual disabilities to the emergency department.

METHOD

Discrete choice experiments (DCEs) are increasingly used in health research to further understand complex decision making. A DCE was designed to assess the relative importance of factors that may influence a GP's (N = 157) decision to refer.

RESULTS

A random parameters model indicated that perceived limited parental capacity to manage an illness was the most important factor in the decision to refer a child to the ED, followed by a repeat visit, a referral request from the parent, and a Friday afternoon appointment.

CONCLUSION

Understanding the factors that influence referral is important for service improvement and to strengthen primary care provision for this population and their families.

Healthcare utilisation and unmet health needs in children with intellectual disability: a propensity score matching approach using longitudinal cohort data

BACKGROUND

Health disparities for children with intellectual disabilities can be challenging to measure due to many other factors that can impact health and healthcare use. The aim of the current study was to use longitudinal cohort data to compare children with intellectual disability (ID) in Ireland between 2006 and 2014 on healthcare utilisation and unmet need, at ages 9 and 13, using a propensity score matching (PSM) approach.

METHODS

Using data from the Growing up in Ireland study, PSM was used to identify an appropriate control sample to compare with a sample of children with ID (n = 124). Participants were matched on variables that are known to influence healthcare utilisation to reduce the impact of confounding variables between groups so that differences between the groups can be estimated. Logistic regression was used to estimate effects at ages 9 and 13.

RESULTS

Children with ID were no more likely to have visited a general practitioner or emergency department in the past 12 months than children without ID. They did have a greater likelihood of visiting a doctor in a hospital in the past 12 months and of having an overnight stay in hospital by age 9. Primary caregivers of children with ID were more likely to report unmet health needs at ages 9 and 13.

CONCLUSIONS

This approach is a novel means of comparing healthcare use in this population by balancing the impact of other factors that may result in inequities, to which children with ID may be more vulnerable.