Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM
An abstract was presented at the 2020 Society for Epidemiologic Annual Meeting (virtual) as a poster.
Funding information: National Center for Advancing Translational Sciences, Grant/Award Number: KL2TR001454; U.S. Food and Drug Administration, Grant/Award Number: HHSF223201400030I
Abstract
Purpose
Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data.
Methods
We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated.
Results
We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%–84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL.
Conclusions
Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.
CONFLICT OF INTEREST
Dr. McMahill-Walraven is employed by Aetna, a CVS Health company. Aetna receives funding for public health and distributed research projects as a subcontractor from Harvard Pilgrim Health Care Institute for FDA Sentinel, Managed Care Pharmacy's (AMCP) Biologics and Biosimilars Collective Intelligence Collaborative (BBCIC), Pfizer, and GSK; and contractor from Patient Centered Outcomes Research Institute (PCORI), Reagan-Udall's Foundation Innovation in Medical Evidence Development and Surveillance (IMEDS), and Pfizer. No other authors have conflicts of interest to declare.
