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Enhancing Diabetes Surveillance Across Alberta by Adding Laboratory and Pharmacy Data to the National Diabetes Surveillance System Methods.
- Source :
-
Canadian journal of diabetes [Can J Diabetes] 2022 Jun; Vol. 46 (4), pp. 375-380. Date of Electronic Publication: 2021 Dec 30. - Publication Year :
- 2022
-
Abstract
- Objectives: The National Diabetes Surveillance System (NDSS) case definition, which identifies a case of diabetes using administrative health records as "two physician claims or one hospital discharge abstract record, within a 2-year period for a diagnosis bearing International Classification of Disease codes for diabetes," was compared with expanded case definitions, including pharmacy (PHARM) and laboratory (LAB) data. The PHARM definition included any therapeutic antihyperglycemic agents, and the LAB definition included thresholds of ≥1 glycated hemoglobin measurement of ≥6.5%, or 2 instances of random glucose ≥11.1 mmol/L or fasting glucose ≥7.0 mmol/L.<br />Methods: In this retrospective study we used administrative data from the Diabetes Infrastructure for Surveillance, Evaluation, and Research project. Descriptive statistics were used to characterize participants by several subgroups.<br />Results: The NDSS identified 291,242 diabetes cases, indicating a provincial prevalence of 6.83%. Using LAB plus PHARM identified 52,040 additional cases, so the combination of NDSS or LAB or PHARM identified the largest number of cases (n=343,282), increasing the diabetes prevalence estimate to 8.06%. These 3 sources resulted in 7 unique subsets: NDSS only (n=42,606), PHARM only (n=16,310), LAB only (n=32,202), NDSS+LAB (n=32,582), NDSS+PHARM (n=22,503), LAB+PHARM (n=3,528) and NDSS+LAB+PHARM (n=193,551). Refinement using demographic and clinical characteristics allowed presumptive cases of polycystic ovarian syndrome to be excluded.<br />Conclusions: The widely used NDSS case definition can be enhanced by the addition of LAB and PHARM data. Including PHARM and LAB data identified subsets of the diabetes population, which can maximize the yield for detection of diabetes cases in Alberta and provide a richer understanding of this population to target interventions to improve health outcomes.<br /> (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 2352-3840
- Volume :
- 46
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Canadian journal of diabetes
- Publication Type :
- Academic Journal
- Accession number :
- 35490092
- Full Text :
- https://doi.org/10.1016/j.jcjd.2021.12.001