Objective:

Extract and annotate electronic health record (EHR) data accessed via Health Information Exchange for a CIDP patient cohort to assess real-world treatment patterns.

Background:

CIDP is an inflammatory neuropathy with heterogeneous presentation. EHR data were explored to describe comorbidities and disease management in real-world clinical practice.

Design/Methods:

Patients with CIDP who previously completed a quantitative survey and provided consent to participate in the Inspire CIDP Virtual Registry for collection of their medical records were included. CIDP-related data elements were extracted, processed, and analyzed. Descriptive statistics were generated. 

Results:

Among patients included (N=50), median patient age was 63 years (IQR: 54-72). Median age at CIDP diagnosis was 57 years (IQR: 48-62); median time between first/last EHR was 126 months (IQR: 96-160). Most patients (96%) had comorbidities, most commonly hypertension (42%). Most patients (74%) had ≥1 CIDP-related medication other than immunoglobulin therapy (median number/patient: 2; IQR: 2-4) listed. Of patients with CIDP-related medication (excluding immunoglobulin therapy) listed in their EHR, 70% had corticosteroid use. Among patients with CIDP who had intravenous (IVIG) or subcutaneous (SCIG) immunoglobulin infusion details listed (56%), 27 received IVIG and 5 received SCIG; median numbers of IVIG or SCIG infusions (IQR) were 5 (2-34) and 2 (2-4), respectively. Median IVIG loading dose and maintenance doses (IQR) were 1.2 g/kg (1.0-2.0) and 1.4 g/kg (1.1-2.0), respectively.

Conclusions:

We demonstrated that it is feasible to extract EHR data to describe real-world characteristics and treatment patterns, including IVIG doses, of patients with CIDP. Most patients had ≥1 CIDP-related medication other than immunoglobulin therapy in their EHR; most reported IVIG or SCIG infusions, predominantly IVIG. Variations in practice and treatment patterns were noted, resulting in varied clinical data in EHRs, potentially impacting identification of patients with CIDP. We hope to expand this analysis to include CIDP-specific data extraction for diagnostic confirmation.