1. Ian McRae Peter Del Fante Nasser Bagheri Justin Reeves Paul Konings
Exploring unidentified diabetes cases in the LeFevre Peninsula, Adelaide
Ian McRae Peter Del Fante
Nasser Bagheri Justin Reeves
Paul Konings

3. The Task Follows Nacul et al (2010) in the UK who used:
Practice level data to measure the number of people diagnosed with diabetes
Data from a health survey which collects clinical measures to construct a model of total diabetes load

4. Applying this model of diabetes load to the clinical practice information to estimate how many patients at a practice level maybe undiagnosed diabetes patients
Applying the model to small geographic areas and comparing with numbers of identified patients from the practices
Then exploring patterns of individuals and areas with undiagnosed diabetes.

5. Model for total diabetes as function of demographic and clinical measures
North West Adelaide Health Survey
About to start
Report back to practices
Have data
Have 70% of data geo-attributed
Mapping of locations of undiagnosed – consideration of clustering
For practices/areas
Predict total diabetes
subtract already diagnosed
Giving undiagnosed diabetes patients
Data extracted from practices in LeFevre Peninsula
ABS data on SEIFA, age, gender, ethnicity
Modelling of undiagnosed by area.
Geocode to mesh blocks
Data on distance to GP, distance to hospital, GP per capita

6. This is a beginning
Assuming all goes well, this will be the basis for other studies
In other areas and bigger areas
In relation to other chronic conditions