20376
ASD Database Development within the Uk's National Health Service, for Service Evaluation/Research Purposes

Thursday, May 14, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
D. Wimpory1 and B. Nicholas2, (1)Penrallt Road, Bangor University & BCU Health Board, Bangor, United Kingdom, (2)Gwynedd LL57 2AS, Bangor University, Bangor, Wales, United Kingdom
Background:  

We report on the development and use of an ASD database module as an enhancement to the UK National Health Service’s (NHS) Community Child Health database (CCH). The ASD database module was established at the end of 2011 specifically for adults and children who have received NHS diagnoses in childhood in North Wales (total child population 145,000). Previous NHS analysis of data such as numbers of ASD diagnoses, age at diagnosis, diagnostic instruments employed, waiting times and types of professions contributing to diagnoses was only available via time-consuming inter-departmental audits requiring dedicated staffing. Parental consent to electronic record keeping is given as part of each child’s birth record on the CCH and the database maintains an ongoing record of children’s developmental milestones, routine vaccinations and significant conditions. The purpose of the ASD module and its supporting administrative process is to improve efficiency in reporting ASD in North Wales; the quality of data collected; and, appropriate access for ASD practitioners to derive improved delivery of assessment/care. University research ethical permission is granted for this project so that prevalence of fragile X syndrome and other ASD co-morbidities can be determined. 

Objectives:  

Evaluate and research the data to quantify changes in diagnostic practice and depth of data collection by monitoring the contents of the ASD records and their annual rate of addition to the CCH.

Methods:  

A count, cross check and collation of CCH ASD database module records were made for the years 2012 and 2013 (2014 in progress). The data was compared with standards for ASD prevalence and the prevalence of ASD genetic comorbidities.

Results:  

The original electronic database (without enhancements) recorded an ASD diagnosis rate of ~1/month. For 2012 the recorded rate rose to ~15/month and this rate was maintained in 2013. ASD prevalence increased from 0.4% immediately before the implementation of the ASD Database Module, to over 0.6% by the end of 2013. For 2012/13: The average age at diagnosis was ~8 years. ADOS was the most frequently employed instrument, and children waited 11 months, on average, between ASD referral and diagnosis. Clinical Psychologists were the most frequent contributors to the diagnoses. ASD genetic comorbidity records were lower than expected due partly to an unexpectedly low number of counts for ASD genetic comorbidities in the CCH compared to the standard prevalence for these disorders.

Conclusions:  

The ASD database module initiative has prompted an increase in the rates of diagnosis that is closing the gap between the CCH reported prevalence of ASD and the generally accepted ~1% prevalence for the disorder. The rather high average age at diagnosis  (~8 years) for 2012 and 2013 reflects a catch-up on previously undiagnosed ASD in the system. This status is anticipated to remain until the current improved rate of recording overwhelms the historical under-recording. The lower than expected number of reports of genetic disorders that carry increased risk of ASD as a comorbidity indicates there is scope for improvements in the availability of genetic testing in North Wales.