A population-based, retrospective, linked administrative health data approach was used to identify patients with a diagnosis of AI and their emergency and outpatient visits in Alberta between January 1, 2014, and December 31, 2018. The province of Alberta has a single public health system that collects data within the 3 sources that provided the variables for this study: the Physician Claims Database, the National Ambulatory Care Reporting System (NACRS), and the Pharmaceutical Information Network (PIN). All Albertan residents seeking care in Alberta would be captured within this provincial reporting structure. The Physician Claims and NACRS data sets were linked to PIN records using unique lifetime identifiers. A description of these databases can be found in the Supplementary Appendix S1.
Case Definition for Adrenal Insufficiency
A case definition for AI, as illustrated in Table 1, was created by a group of endocrinologists and researchers based on International Classification of Diseases, 9th and/or 10th edition (ICD-9 and ICD-10, respectively) codes and relevant medications dispensed to estimate the prevalence of AI. The coding used was kept broad to capture all etiologies of AI.
Given the existence of the PIN database, where pharmacies in Alberta are required to register dispensed medications within 24 h, we included the dispensation of prescribed glucocorticoids and/or mineralocorticoids to the case definition. We queried the 3 databases to identify adult (aged ≥18) Alberta residents with at least 1 emergency or outpatient visit related to AI between January 1, 2014 and December 31, 2018 with the following criteria:
An ICD-9 diagnosis of 255.4, 255.2, or 255.5 in Physician Claims or an ICD-10 diagnosis of E27.1, E27.2, E27.3, E27.4, or E25.0 in NACRS and with at least 2 PIN dispensing records of glucocorticoid or mineralocorticoid after the earliest date of diagnosis (index date), or
An ICD-9 diagnosis of 253.2 in Physician Claims or an ICD-10 diagnosis of E89.3 or E23.0 in NACRS and with at least 2 PIN dispensing records of glucocorticoid after the earliest date of diagnosis (index date).
The period prevalence was calculated as the number of unique patients, identified by personal healthcare numbers, with at least 1 emergency or outpatient visit with a code for AI between January 1, 2014 and December 31, 2018, divided by the mid-interval population size of Alberta [defined as the adult (≥18 years) population of Alberta in 2016, which was 3.143995 million].
Estimating Rates of Emergency and Outpatient Healthcare Utilization
The unique lifetime identifiers of the patients were used to query the Physician Claims and NACRS databases for all emergency and outpatient visits from a patient's index date to December 31, 2018. A visit was defined to be related to AI if the visit had at least 1 diagnostic code for AI associated with it.
There are 2 sources of emergency and outpatient data in Alberta: the Physician Claims database and the NACRS database. All emergency room visits are captured in the NACRS database, and most are captured in the Physician Claims database. For outpatient visits, some visits are captured in Physician Claims only, some in NACRS only, some in both, and some in neither. To count the number of unique visits, it was therefore necessary to attempt to identify and remove duplicate visits both within and between these databases. The Physician Claims database uses ICD-9 coding taxonomy, while NACRS uses ICD-10. To remove duplicate visits, we first removed duplicate visits from within each database (ie, visits with identical information). We then combined the data sets and, as there is no official reconciliation between these 2 databases, identified and removed duplicate visits between them using the following definition: a visit for the same patient on the same date with the same visit type (emergency or outpatient) and at the same facility was considered a duplicate.
The main reason for the visit was considered to be the first diagnostic code in both the Physician Claims and NACRS data sets as it is defined as the diagnosis or condition that is most responsible for the patient's visit.
The unique lifetime identifier of each patient was used to query the PIN database for glucocorticoid and mineralocorticoid medication dispenses between their index date (earliest date in the time period with a diagnostic code for AI) and December 31, 2018. The list of glucocorticoid and mineralocorticoid medications that were searched for can be found in the Supplementary Appendix S1. Each patient was categorized as having been dispensed glucocorticoid medications only, mineralocorticoid medications only, or both.
Descriptive statistics were presented as frequencies and percentages as well as means and SDs. Results were stratified by whether the visit was related to the treatment of AI, where applicable. For descriptive purposes only, 2 bivariate ordinary least squares regression lines of best fit were calculated to depict the overall trend in visit rates over the time period; ED or outpatient visit rates were the dependent variables (y) and year (2014–2018) was the independent variable (x) in each calculation. Additionally, for descriptive purposes, we conduct inferential tests to determine whether there are differences in visit rates across years based on emergency or outpatient settings.
J Endo Soc. 2022;6(4) © 2022 Endocrine Society