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Published on: September 15, 2017
Health Care Burden in Patients With Adrenal Insufficiency
Candace Gunnarsson1, Michael P Ryan1, Claudio Marelli2
1CTI Clinical Trial and Consulting Services Inc., Covington, Kentucky 41011.
Insights
Patients with adrenal insufficiency (AI) face a significant healthcare cost burden, with higher expenditures and hospitalizations compared to controls. Adherence to glucocorticoid therapy can reduce these costs.
Area of Science:
- Endocrinology
- Health Economics
- Real-World Evidence
Background:
- Adrenal insufficiency (AI) encompasses primary (PAI), pituitary (PIT), and congenital adrenal hyperplasia (CAH) forms.
- Understanding the economic impact of AI is crucial for healthcare resource allocation.
Purpose of the Study:
- To estimate the annual healthcare burden associated with AI using real-world data.
- To compare healthcare expenditures across different AI subtypes and treatment regimens.
Main Methods:
- Utilized a US payer database (>108 million members) to identify 10,383 AI patients.
- Matched AI patients 1:1 with controls based on demographics and insurance.
- Employed multivariable expenditure models, analyzing subsets by glucocorticoid therapy and adherence.
Main Results:
- AI patients incurred significantly higher annual healthcare costs (PAI: $18,624, PIT: $32,218, CAH: $7677) vs. controls.
- AI patients experienced 8-10 times more inpatient hospital days annually.
- Multiple steroid therapies increased expenditures; higher adherence to hydrocortisone correlated with lower costs in PAI and PIT.
Conclusions:
- AI imposes a substantial annual healthcare burden, varying by cause and treatment.
- Optimizing glucocorticoid replacement adherence can mitigate healthcare expenditures in AI patients.
Objective:
This study aimed to estimate the annual health care burden for patients with adrenal insufficiency [AI; primary (PAI), secondary to pituitary disorder (PIT), and congenital adrenal hyperplasia (CAH)] using real-world data.
Methods:
Using a US-based payer database comprising >108 million members, strict inclusion criteria with diagnostic codes and pharmacy records were used to identify 10,383 patients with AI. This included 1014 patients with PAI, 8818 with PIT, and 551 with CAH, followed for >12 months. Patients were matched 1:1 to controls, based on age (±5 years), sex, insurance, and region. Multivariable expenditure models were estimated for each AI cohort vs controls as well as subsets by glucocorticoid therapy (hydrocortisone, dexamethasone, prednisone, or multiple therapies). A separate multivariable model was estimated to assess the association between adherence and expenditures.
Results:
Total annual health care expenditure estimates were significantly higher (P < 0.0001) in all AI cohorts compared with matched controls (PAI $18,624 vs $4320, PIT $32,218 vs $6956, CAH $7677 vs $4203). Patients with AI have more frequent inpatient hospital stays with up to eight to 10 times more days in the hospital per year than their matched controls. In each AI cohort, patients on multiple steroid therapies had higher expenditures in comparison with patients using hydrocortisone therapy alone. In PAI and PIT cohorts taking hydrocortisone only, fewer expenditures were found in higher adherence subsets.
Conclusion:
Patients with AI demonstrate a substantial annual health care burden. Expenditures vary by underlying cause and treatment and are reduced in patients with higher adherence to glucocorticoid replacement.
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