# data[].attributes.body
What tests do we target for data?
What data is available/accessible?
e.g.
Polytesting - how easy is it to order multiple tests with low influence on management
'Monitoring' tests - how often should you check HbA1c, FBC, cholesterol in otherwise healthy person

# data[].attributes.headline
Who will support the topic at the ST end

# data[].attributes.subject
Who will support the topic at the ST end

# data[].attributes.body
Is there a local  primary care testing guru to comment on subject matter?

Who will support topic development at ST end?

# data[].attributes.body
NZ version
·         Summarise the benefits, harms and limitations of testing

·         Identify factors that influence requesting of tests and the potential risks involved

·         Identify when tests might be harmful

·         Recognise that reducing inequity in testing is important for improving health outcomes

·         Recognise the importance of shared decision making and assessment of patients’ test (health) literacy

Relevance for ST?

# data[].attributes.body
NZ version
Best-practice testing

Minimising waste in testing
Inequities - who are we missing?
Poly testing
Overdiagnosis
Incidentalomas
Disease creep - changing diagnostic thresholds
Role of testing in disease prevention

What does ST version need to cover? Where are the knowledge gaps?

# data[].attributes.body
NZ version as an idea of what might be covered

# data[].attributes.attachment_link.title
FINAL MD Slide Presentation Testing Times AugSep 2020

# data[].attributes.body
From a much older topic but concepts may be applicable

# data[].attributes.attachment_link.title
+ MASTER GP SG Powerpoint (Polytesting) FINAL

# data[].attributes.body
What would your groups be interested in discussing?

Ideas for comment
What tests could we omit without adversely impacting care?
Role for the wider team - who else orders tests - how is this info coordinated at the practice? Who manages abnormal results?
What does shared decision making look like in testing? Do you discuss next steps - if the result is positive then ...

# data[].attributes.body
Case/Scenarios Ideas
What tests do we highlight for discussion?
Role of testing in management - the worried well
Managing incidentalomas - the more tests done the more likely a result will sit outside the normal range - how do you manage this?
What tests do we highlight for discussion here?