Open Access Open Badges Research article

Technical evaluation of methods for identifying chemotherapy-induced febrile neutropenia in healthcare claims databases

Derek Weycker1*, Oleg Sofrygin1, Kim Seefeld1, Robert G Deeter2, Jason Legg2 and John Edelsberg1

Author Affiliations

1 Policy Analysis Inc. (PAI), Brookline, MA, USA

2 Amgen Inc, Thousand Oaks, CA, USA

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BMC Health Services Research 2013, 13:60  doi:10.1186/1472-6963-13-60

Published: 13 February 2013



Healthcare claims databases have been used in several studies to characterize the risk and burden of chemotherapy-induced febrile neutropenia (FN) and effectiveness of colony-stimulating factors against FN. The accuracy of methods previously used to identify FN in such databases has not been formally evaluated.


Data comprised linked electronic medical records from Geisinger Health System and healthcare claims data from Geisinger Health Plan. Subjects were classified into subgroups based on whether or not they were hospitalized for FN per the presumptive “gold standard” (ANC <1.0×109/L, and body temperature ≥38.3°C or receipt of antibiotics) and claims-based definition (diagnosis codes for neutropenia, fever, and/or infection). Accuracy was evaluated principally based on positive predictive value (PPV) and sensitivity.


Among 357 study subjects, 82 (23%) met the gold standard for hospitalized FN. For the claims-based definition including diagnosis codes for neutropenia plus fever in any position (n=28), PPV was 100% and sensitivity was 34% (95% CI: 24–45). For the definition including neutropenia in the primary position (n=54), PPV was 87% (78–95) and sensitivity was 57% (46–68). For the definition including neutropenia in any position (n=71), PPV was 77% (68–87) and sensitivity was 67% (56–77).


Patients hospitalized for chemotherapy-induced FN can be identified in healthcare claims databases--with an acceptable level of mis-classification--using diagnosis codes for neutropenia, or neutropenia plus fever.

Febrile neutropenia; Neutropenia; Diagnosis; Classification; Sensitivity and specificity; Predictive value of tests