Is the burden of diabetes in Australia underestimated? Comparison of diabetes ascertainment using linked administrative health data and an Australian diabetes registry
Authors' conclusion
This study demonstrates the value in using linked administrative data for diabetes monitoring and surveillance. National estimates using the NDSS alone may underestimate the diabetes burden by up to 35%.
Study context
- Population
- Individuals aged ≥45 years from the 45 and Up Study, Australia
- Participants
- 266,414 individuals
- Comparison
- Administrative-data diabetes algorithm vs NDSS registrations
- NDSSn = 35,900reference
- Outcome
- Diabetes ascertainment by algorithm vs NDSS
Methodological detailsprospective cohort, linked administrative health data
- Prospective cohort
- Linked administrative health data
Performance
As reported in the abstract
| Test or model | Sensitivity | Specificity | PPV |
|---|---|---|---|
| Algorithm | 96.9% (95%CI 96.7-97.1) | 91.8% (95%CI 91.7-91.9) | 64.9%, 95%CI: 64.6-65.2 |
Algorithm
Sensitivity96.9% (95%CI 96.7-97.1)
Specificity91.8% (95%CI 91.7-91.9)
PPV64.9%, 95%CI: 64.6-65.2
- Certain diabetes identified by the algorithm
- 53,669
- Of 53,699 identified by the algorithm, registered to the NDSS
- 34,864
Original publication
Is the burden of diabetes in Australia underestimated? Comparison of diabetes ascertainment using linked administrative health data and an Australian diabetes registry. Diabetes Res Clin Pract. Published 18 March 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →