Chris Roebuck from @NHSDigital kicked us off with an introduction to and summary of NHS Digitalβs role generally and specifically in relation to the COVID situation.
Don't worry, the session is being recorded and is running with a streamed transcript for accessibility.
Sharon Thandi begins with a discussion about a follow-up survey about #mentalhealth that started in 2017
As per usual, it takes a team to make things work. The #MentalHealth Survey of Children and Young People (CYP) involved a large collaboration
The main survey tool used was the Strengths and Difficulties Questionnaire (SDQ), which classifies respondents based on the estimated likelihood of a having mental health disorder.
Results show a rise of estimated likelihood of a mental health disorder from 1-in-9 to 1-in-6.
Many of use spent a lot more time with each other during lockdowns.
Is there a link between living in a family struggling with "family functioning" and estimated likelihood of a mental health disorder?
What is the direction of the relationship between access to contemporary resources and #mentalhealth disorders?
Is there potential for an intervention through investment in IT hardware and free spaces to be?
Our second speaker were Kieran Bakerand Lucy Elliss-Brookes, talking about Risk Stratification and the @NHSDigital "Shielded Patient List"
Again, collaboration is key. @NHSDigital worked with clinical colleagues to translate clinical concepts into technical specification and rule set to identify patients.
No one is immune to data quality issues. @NHSDigital had to handle...
- Disappearing clinical codes
- Nonsensical time frame
- Mistaken clinical codes, e.g. sickle cell trait vs sickle cell disease
- Deceased status: formally or informally?
But despite the challenges, there were many benefits...
And what was learned from the dataset that was created?
Our third talk was delivered by Rupert Chaplin and Efrosini about collecting COVID-related data from primary care.
Efrosini presented on some descriptive analyses that used the COVID-augement data.
Interactive graphs are available if you follow the QR code
As an example, comparisons were made between cases of COVID based on official statistics and those derived from @NHSDigital 's augmented, primary-care dataset
Comparisons were also made across ethic groups.
Trends were similar across all ethnicities but magnitudes differed.
NB: These data only capture information about those that attended their primary care practice.