To the best of our knowledge, this is the first study of its kind evaluating the prevalence, healthcare utilization, and medication dispensation records of patients with AI in Canada. Several noteworthy findings were obtained from this study. First, the period prevalence of AI in Alberta was found to be relatively high at 839 cases per million people between 2014 and 2018 when compared to other studies. Second, patients with AI made more outpatient and emergency room visits than the average Albertan and the number of outpatient visit rates appear to be rising, but notably the majority of visits were not identified as related to AI. Last, the majority of patients appear to be prescribed a glucocorticoid only during this time frame. Our findings provide a framework for using healthcare administrative data to analyze clinical trends for an uncommon condition in a population.
In keeping with previous literature, our findings reiterate the uncommonness of AI—an aspect that often makes it difficult to determine general population-level trends and clinical effects of treatment. On a global level, the reported prevalence in European and Western countries is estimated at around 100 per million and 39 to 144 per million, respectively, while the highest reported has been Norway with 144 per million.[6,15,16] In comparison, the period prevalence of AI found by our analysis in Alberta is relatively high and raises questions as to the origin of this disproportionate burden. There are various factors that should be considered when analyzing the cause of increased burden. For primary AI, it is clear that the rates of autoimmune adrenalitis in developing countries have been rising and other risk factors such as sex (female predominance), ethnicity (white/Caucasian), and age (most often 30–50 years of age) impart an increased risk. Overall it is unclear what has resulted in this high prevalence in Alberta's population as demographic data were not available for analysis. Future analyses will investigate these considerations. Furthermore, several caveats to our obtained data likely render the period prevalence an underestimation, which further raise concern about the true burden of AI on healthcare utilization. These include variable mandatory coding requirements by health system payers, inconsistent outpatient data submission and reporting to administrative databases, and the need for manual reconciliation of databases.[17,18] The period prevalence may be underestimated because it is possible that not every patient with AI in Alberta will have visited an ED or outpatient clinic during the time period studied. It is also important to consider that patients may have not had a visit coded for AI during the time period or none of their outpatient visits were submitted to NACRS or Physician Claims. Although reconciliation was required to identify duplicate visits between databases, it is unlikely that this played a role in overestimating the period prevalence as this was completed by identifying unique instances of personal health care numbers across the visits. If there were duplicate visits from the same patient, their personal healthcare number would only be counted once. Thus, it is more likely the period prevalence was influenced by coding requirements, which would overall contribute to underestimation.
Our most concerning finding is that 94.3% of visits were not labeled with AI, even though many of the top presenting complaints (eg, abdominal pain, unspecified site; volume depletion disorder, etc.) were consistent with adrenal crisis. Given that AI is typically a lifelong condition that requires stress dosing of glucocorticoids for physical stressors such as fever, surgery, and pregnancy, it is virtually impossible that 94.3% of clinic and hospital visits were not influenced by the presence of AI. Unfortunately, we could not use chart review to audit these cases, but this low rate of AI coding begs the question of whether the treating clinicians were aware of the AI diagnosis and properly managed it. This is substantiated by the fact that healthcare utilization for AI patients was higher in ED and outpatient settings. Comparing data from Alberta Health Services in 2015–2016, our findings show overall that patients with AI had 3 times as many outpatient visits (17.82 vs. 5.34) and 4 times as many ED visits (2.26 vs 0.52) per person per year when compared to the average Albertan, providing even more evidence that AI was underreported as an associated diagnosis. This is in agreement with Gunnarsson et al, who showed similar substantially increased annual healthcare burdens for patients with AI in the United States.
Primary AI results in impairment of all adrenal axes whereas in secondary AI, the mineralocorticoid axis is still usually intact. It is expected that primary AI patients be prescribed a combination of glucocorticoid and mineralocorticoid replacement whereas secondary AI patients would require glucocorticoid replacement only.[3,6,19,20] Although the majority of patients in our study were prescribed only glucocorticoid medication (71.6%) or combination glucocorticoid and mineralocorticoid (27.4%), we do not have enough definitive data to draw conclusions about the etiology of AI. Of note, the ICD-10 code E27.3 (drug-induced adrenocortical insufficiency) included various agents such as antibiotics/antifungals, opioids and other analgesics, and other systemic therapies. Unfortunately, we did not have subcategorized "cause codes" to detail specific drugs and frequency of occurrence to supplement these data. Björnsdottir et al had previously shown via a population-based cohort study in Sweden how prescription patterns can be used to analyze AI and associated comorbidities. Beyond epidemiological measures, studies like Eyal et al's assessment in a pediatric population brings to light how determining the underlying etiology may help anticipate the percentage of patients at highest risk for adrenal crises as well. Ideally, future studies of medication dispensation records linked to detailed medical records will enable better understanding of a patient's risk for future crises and complications and enable preventive approaches.
Several limitations to this methodology and study must be addressed. First, as mentioned previously, results are contingent upon the claims and NACRS data submitted, as well as coding practices. It is not mandatory in Alberta for all outpatient visits to be submitted and entered into an administrative database; therefore, some visits may be missed using this method. Furthermore, it is not mandatory to submit outpatient visits to NACRS, and physicians on alternative payment plans are not mandated to submit to Physician Claims. Minimal coding requirements in Alberta, in which only a single code per visit must be submitted, with the use of nonspecific codes, such as "follow-up" without other medical diagnosis, may underrepresent capture of AI presentations and diagnoses. Second, this method can provide population-level estimates but is not able to rationalize findings to the individual patient care level without supplemented information through chart review. Third, as studies on the epidemiology of AI in Canada are limited, a comparator group could not be established. Overall it is clear that using this methodology requires a strong understanding of local coding and data submission processes. Future efforts in building more specific case definitions and integrating information with electronic medical records data may also help provide clarity.
In conclusion, our results show that although AI is an uncommon diagnosis, it appears to have a higher prevalence in Alberta than reported in other studies. It is unclear what etiological factors may be responsible for this relatively higher prevalence. Furthermore, patients with AI access care much more frequently than the average Albertan. With rising outpatient visits, the care demands are expected to increase in the coming years. While there appear to be various reasons for patients presenting to medical attention that are not coded specifically for AI, we do suspect that if these visits were to be closely examined, a number likely include adrenal crisis given AI's broad range of clinical presentations as well the use of nonspecific ICD codes and minimal coding requirements. This is the first study of its kind to evaluate AI in Canada specifically using administrative data. Future studies could add further light to these findings by broadening the scope of administrative data obtained, supplementing data with chart review and hospital records, and utilizing this methodology in other provinces to generate comparative data.
We would like to acknowledge members of the Division of Endocrinology and Metabolism at the University of Alberta for their input, review, and support throughout this project. We would also like to acknowledge Charlene Feuffel, Alberta Health Services Data Analyst, for her substantial contributions to the acquisition of this data.
This work was supported by the Physician Learning Program. The Physician Learning Program is funded by the Government of Alberta. The views expressed herein do not necessarily represent the official policy of the Government of Alberta.
Restrictions apply to the availability of some or all data generated or analyzed during this study to preserve patient confidentiality or because they were under license. The corresponding author will on request detail the restrictions and any conditions under which access to some data may be provided.
J Endo Soc. 2022;6(4) © 2022 Endocrine Society