Exploring Possibility of Medical Device Surveillance in Patients on Peritoneal Dialysis Using a Common Data Model

Background and Objectives: Peritoneal dialysis (PD) requires well-functioning medical de-vices (MDs). PD complications can result in significant adverse events, including discon-tinuation of PD, hospitalization, and death. This study aimed to evaluate the feasibility of detecting various PD complications and data related to MDs. Materials and Methods: A retrospective study was conducted on patients who received PD catheter insertions between January 2001 and March 2021 to evaluate PD-related compli-cations. PD complications were evaluated through diagnostic, procedural, and MD codes using a common data model (CDM) and compared with those from electronic health rec-ords (EHR). The results from one CDM database were compared with those from another CDM database. Results: A total of 342 patients were enrolled. One hundred ninety-five patients experi-enced PD complications more than once. Nineteen prescription codes and 20 diagnostic codes from the EHR were identified, covering 11 procedures, 3 MDs, and 7 complications related to PD. Infectious complications were detected using the CDM, whereas mechanical complications were missed. Although data on PD catheters and adaptors were available in the EHR, they were not detected by the CDM. Some infectious and mechanical compli-cations were identified by CDM in the other database. After implementing amended matching, these data were detected. Conclusions: While some PD-related medical data recorded in EHR were misrepresented or omitted during the CDM database extract, transform, and load process, the CDM still pro-vides valuable real-world data.