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Published on: June 20, 2020
Access to child developmental assessment services in culturally and linguistically diverse metropolitan Sydney: a
Sibella E Bentley1,2, Pankaj Garg3,4, Ori Gudes5
1The Children's Hospital at Westmead, Corner Hawkesbury Road and Hainsworth Street, Westmead, NSW, 2145, Australia. Sibella.bentley@health.nsw.gov.au.
Insights
Children with neurodevelopmental disorders (NDD) in disadvantaged areas face long waits for assessment. Prioritizing vulnerable children and refining processes are crucial for improving access to child development services.
Area of Science:
- Child Development
- Neurodevelopmental Disorders
- Public Health Services
Background:
- Limited global data exists on access to child development services for neurodevelopmental disorders (NDD).
- Long wait times for developmental assessments significantly impact child care and outcomes.
- Child developmental assessment services (CDAS) in vulnerable regions face challenges in timely service delivery.
Purpose of the Study:
- To retrospectively analyze the demographic profile of patients at a child developmental assessment service (CDAS).
- To investigate patient prioritization processes and factors influencing wait times for developmental assessments.
- To explore service delivery challenges in a socioeconomically vulnerable region of Sydney.
Main Methods:
- Analysis of data from 2354 patients seen at a CDAS between 2018 and 2022.
- Collated Socio-Economic Indexes for Areas (SEIFA) data from the Australian Bureau of Statistics.
- Employed descriptive and various statistical methods to examine demographic data and factors affecting wait lists.
Main Results:
- The cohort (n=2354) had a median age of 51 months, with 73.7% males, 64% from culturally and linguistically diverse (CALD) backgrounds, and 47% from disadvantaged suburbs.
- Median wait time was 302.5 days; 70% were seen within 12 months. CALD patients and children over 5 years experienced shorter wait times.
- Children with Global Developmental Delay (GDD) from lower SEIFA deciles waited longer; prioritization for ASD/severe GDD did not significantly reduce overall wait times.
Conclusions:
- The study highlights the demographic profile and wait time challenges for children with NDD in socioeconomically disadvantaged areas.
- There is a need to discuss benchmarking targets with service providers and prioritize children in disadvantaged suburbs.
- Refining prioritization and data collection processes is essential to improve wait times and access to child development services.
Background:
Despite the increasing prevalence of neurodevelopmental disorders (NDD), data regarding access to child development services have remained limited globally. Long wait times are a major barrier to developmental assessments, impacting on care and outcomes. The aim is to retrospectively analyse the demographic profile and prioritisation of patients seen at a child developmental assessment service (CDAS) in a vulnerable region of Sydney, and explore factors affecting wait times.
Methods:
Data was collated and analysed for 2354 patients from 2018 to 2022. Socio-Economic Indexes for Areas (SEIFA) were collated from the Australian Bureau of Statistics. Descriptive statistics were used for demographic data and various statistical methods were used to analyse the relationships and impact of factors likely to affect wait lists.
Results:
The median age was 51 months (IQR41-61) and males comprised 73.7% of the cohort. 64% of children were from culturally and linguistically diverse backgrounds (CALD) and 47% lived in the most disadvantaged suburbs. The median wait time was 302.5 days (IQR175-379) and 70% of children were seen within 12 months. CALD patients and children over 5-years had shorter wait times. Most children with Global Developmental Delay (GDD) were from the lowest four SEIFA deciles and waited longer for an appointment. 42.6% were seen within the priority allocated time or sooner. Children with ASD and/or severe GDD were prioritised to be seen earlier. Overall, the study could not demonstrate any difference in the wait times according to the prioritisation groups.
Conclusion:
This study provides insights into the profile, prioritisation processes and wait lists of children seen by CDAS in South Western Sydney with high rates of social vulnerability and presents an argument to discuss benchmarking targets with service providers. It identifies the need to prioritise children living in suburbs with socioeconomic disadvantage and refine prioritisation and data collection processes to improve wait times.
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