Identification of Maintenance Dialysis Recipients From an Electronic Clinical Information System and Effects on...

Clinical information systems (CISs) can support case finding. However, standardized methods for identifying maintenance dialysis recipients and assessing how CIS transitions influence disease burden estimates are lacking. We aimed to develop and evaluate methods for identifying maintenance dialysis recipients across CIS transitions and examine trends in incidence and prevalence across the implementation timeline.

Population-based retrospective cohort study.

Alberta residents aged ≥20 years, who initiated (incident) or received (prevalent) maintenance dialysis from January 2012 to March 2024, were identified using clinical data (historical kidney care program data and a new Epic-based CIS) versus administrative claims. Study periods included preimplementation (January 2012 to November 2019; use of historical program data), transition (November 2019 to November 2022; combination of data sources), and full implementation of the CIS (November 2022 to March 2024). Claims data were available throughout. Maintenance dialysis was defined as in-center hemodialysis for >90 days or initiation of peritoneal/home hemodialysis, regardless of duration.

The algorithms identified 7,766 incident cases from clinical data and 7,556 from claims, with 7,391 (93.2%) overlapping. Incidence rates increased slightly over time and were comparable between data sources. Prevalence estimates were higher in claims than historical program data preimplementation but converged during the full CIS implementation period. In 2023, CIS-based incidence was 218.5/million population versus 199.9/million population from claims, and CIS-based prevalence was 1,018.3 versus 1,006.8 from claims. Dialysis initiation dates aligned within 28 days for 84.6% of patients, and period prevalence agreed well between data sources.

Exclusion of patients with kidney failure receiving dialysis for <90 days.

Standardized methods for identifying incident maintenance dialysis recipients showed agreement between CIS and claims-based data, whereas the use of historical kidney care program data underidentified prevalent patients in Alberta. These approaches can optimize the identification of maintenance dialysis recipients from routinely collected health information.