Sekhon SS, Crick K, Myroniuk TW, Hamming KSC, Ghosh M, Campbell-Scherer D, Yeung RO. Adrenal Insufficiency: Investigating Prevalence and Healthcare Utilization Using Administrative Data.
J Endocr Soc 2022;
6:bvab184. [PMID:
35284774 PMCID:
PMC8907404 DOI:
10.1210/jendso/bvab184]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Indexed: 11/19/2022] Open
Abstract
Context
Adrenal insufficiency (AI) is an uncommon, life-threatening disorder requiring lifelong treatment with steroid therapy and special attention to prevent adrenal crisis. Little is known about the prevalence of AI in Canada or healthcare utilization rates by these patients.
Objective
We aimed to assess the prevalence and healthcare burden of AI in Alberta, Canada.
Methods
This study used a population-based, retrospective administrative health data approach to identify patients with a diagnosis of AI over a 5-year period and evaluated emergency and outpatient healthcare utilization rates, steroid dispense records, and visit reasons.
Results
The period prevalence of AI was 839 per million adults. Patients made an average of 2.3 and 17.8 visits per year in the emergency department and outpatient settings, respectively. This was 3 to 4 times as frequent as the average Albertan, and only 5% were coded as visits for AI. The majority of patients were dispensed glucocorticoid medications only.
Conclusion
The prevalence of AI in Alberta is higher than published data in other locations. The frequency of visits suggests a significant healthcare burden and emphasizes the need for a strong understanding of this condition across all clinical settings. Our most concerning finding is that 94.3% of visits were not labeled with AI, even though many of the top presenting complaints were consistent with adrenal crisis. Several data limitations were discovered that suggest improvements in the standardization of data submission and coding can expand the yield of future studies using this method.
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