Experimental waiting times data for autism services published for first time
Partial statistics on waiting times for people in contact with autism services have been published today by NHS Digital.
The Autism Statistics1 report includes data on the number of new patients referred for suspected autism within the reporting period and waiting times for the first appointment (in weeks)2.
These experimental statistics3 are undergoing evaluation and should be used with caution as they do not capture all patients. In addition, information is based on total submissions for England and at provider level, but not all provider organisations are submitting data4. Work is ongoing to establish the number of organisations who should be submitting autism data.
A number of other limitations, including around the complexity of recording autism diagnoses and referrals, and other data quality issues are explained within the report.
The data has been published so that users and stakeholders can feed back on their suitability and quality to assist in their development, in order to improve the dataset over time.
Today’s publication includes statistics for the first three quarters of 2018-19, with breakdowns by age, gender and ethnicity.
This information is collected from the Mental Health Services Dataset5.
Read the full report
Notes to Editors
- Autism Statistics has been developed to help achieve better outcomes for children and young people and adults with autism. It provides data that will be used to commission services in a way that improves health and reduces inequalities and supports service improvement and clinical quality. This is done by capturing detailed information submitted about the patient (age, gender, ethnicity) along with submitted data at provider level. Further detail on the information captured within the Mental Health Services Dataset (MHSDS) is available from: https://digital.nhs.uk/data-and-information/data-collections-and-data-sets/data-sets/mental-health-services-data-set
- The National Institute for Health and Care Excellence (NICE) recommends that people who are referred to a professional or team who specialise in diagnosing autism should have an assessment started within 13 weeks of their referral.
- Experimental statistics are new official statistics undergoing evaluation. They are published in order to involve users and stakeholders in their development and as a means to build in quality at an early stage.
- Currently it is not fully known which provider organisations are in scope of submitting data for autism patients. All providers of autism services should submit data if they provide this care. Work is ongoing to establish the number of organisations who should be submitting autism data.
- MHSDS is a patient level, output based, secondary uses data set which aims to deliver robust, comprehensive, nationally consistent and comparable information for children, young people and adults who are in contact with mental health services, including autism services. People who receive autism spectrum disorder services or who are thought to have an autism spectrum disorder are within the scope of the MHSDS. Changes in Version 3.0 of the MHSDS introduced on 1 April 2018 include enhanced data collection in support of timely recording of diagnosis of autism spectrum disorder. From 1 April 2018, providers of mental health, learning disabilities and autism spectrum disorder services must start submitting data related to autism patients as two new options are available for the primary reason for referral as follows:
25 Suspected Autism Spectrum Disorder
26 Diagnosed Autism Spectrum Disorder
NHS Digital is the national information and technology partner of the health and care system. Our team of information analysis, technology and project management experts create, deliver and manage the crucial digital systems, services, products and standards upon which health and care professionals depend. During the 2018/19 financial year, NHS Digital published 265 statistical reports. Our vision is to harness the power of information and technology to make health and care better.
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