Background: In Ontario, Canada’s largest province, population-based health administrative data represents an accessible and useful tool for population surveillance of people with chronic diseases. While hemoglobinopathies can be identified using data from universal hemoglobinopathy screening, which was implemented in November 2006, these data would not contain information on affected immigrants (21https://cheoresearch.wpengine.com/research/projects/researching-covid-19-community-markers-in-wastewater/.9% of the population). We validated algorithms using provincial health administrative data and newborn screening data to identify children with hemoglobinopathies whether or not they were born in Ontario, thereby creating a population-based surveillance cohort.
Objectives: (1) Validate algorithms to identify children with sickle cell disease, thalassemia and other hemoglobinopathies from within health administrative data; and (2) Determine incidence and prevalence of hemoglobinopathies in Ontario children.
Methods: For the validation study, a positive reference cohort was established using lists of known hemoglobinopathy patients who were followed at five pediatric hemoglobinopathy treatment sites in Ontario and born between November 24, 2006 and March 31, 2013. Health card numbers of these patients were linked deterministically to unique identification numbers in administrative data, which included data on hospitalizations, physician claims, sociodemographic characteristics, immigration records and cause of death. The negative reference cohort included all children residing in Ontario cities who had never been seen at a hemoglobinopathy centre, and therefore assumed not to have disease. Various combinations of administrative data codes were tested for their ability to identify children <18 years of age with hemoglobinopathies from within the databases, and we selected the algorithms with the highest positive predictive value, while maintaining sensitivity >80%. Using two validated algorithms, we identified all children with hemoglobinopathies born between April 1, 1991 and March 31, 2013. We described the crude incidence and prevalence per 100,000 patient-years (PYs).
Results: Two algorithms functioned best to identify incident and prevalent hemoglobinopathy cases (see Table). Among children born between April 1, 1991 to March 31, 2013, 1526 incident hemoglobinopathy patients were identified using Algorithm 1 (crude incidence of 4.85 per 100,000 PYs) and 1660 new hemoglobinopathy patients were identified using Algorithm 2 (crude incidence 5.28 per 100,000 PYs, 95% CI 3.51 to 3.92). In 2013, the overall prevalence of children <18 years living with hemoglobinopathies was 1215-1325 cases.
Conclusion: Through an innovative approach using provincial health administrative, immigration and demographic data, this study identified a rising incidence and prevalence of hemoglobinopathies among Ontario children <18 years of age between April 1, 1991 and March 31, 2013, potentially due to increased immigration rates. These findings could be used to inform health services distribution. This surveillance cohort will be used to understand the impact of immigration status on health care inequality for hemoglobinopathy-related health services delivery, as well as to assess outcomes in this important group of chronic diseases.