Journal article
Evaluating algorithms for identifying incident Guillain-Barré Syndrome in Medicare fee-for-service claims
Global Epidemiology, Vol.7, 100145
06/2024
DOI: 10.1016/j.gloepi.2024.100145
Abstract
Claims data can be leveraged to study rare diseases such as Guillain-Barré Syndrome (GBS), a neurological autoimmune condition. It is difficult to accurately measure and distinguish true cases of disease with claims without a validated algorithm. Our objective was to identify the best-performing algorithm for identifying incident GBS cases in Medicare fee-for-service claims data using chart reviews as the gold standard.
This was a multi-center, single institution cohort study from 2015 to 2019 that used Medicare-linked electronic health record (EHR) data. We identified 211 patients with a GBS diagnosis code in any position of an inpatient or outpatient claim in Medicare that also had a record of GBS in their electronic medical record. We reported the positive predictive value (PPV = number of true GBS cases/total number of GBS cases identified by the algorithm) for each algorithm tested. We also tested algorithms using several prevalence assumptions for false negative GBS cases and calculated a ranked sum for each algorithm's performance.
We found that 40 patients out of 211 had a true case of GBS. Algorithm 17, a GBS diagnosis in the primary position of an inpatient claim and a diagnostic procedure within 45 days of the inpatient admission date, had the highest PPV (PPV = 81.6%, 95% CI (69.3, 93.9). Across three prevalence assumptions, Algorithm 15, a GBS diagnosis in the primary position of an inpatient claim, was favored (PPV = 79.5%, 95% CI (67.6, 91.5).
Our findings demonstrate that patients with incident GBS can be accurately identified in Medicare claims with a chart-validated algorithm. Using large-scale administrative data to study GBS offers significant advantages over case reports and patient repositories with self-reported data, and may be a potential strategy for the study of other rare diseases.
•Guillain-Barré Syndrome (GBS) is rare and claims data offer larger sample sizes.•Tested algorithms for identifying GBS in claims with chart review gold standard.•Primary inpatient diagnosis + procedure had the highest positive predictive value.•Primary inpatient diagnosis was favored across three GBS prevalence assumptions.•We validated several algorithms for identifying GBS cases in Medicare claims.
Details
- Title: Subtitle
- Evaluating algorithms for identifying incident Guillain-Barré Syndrome in Medicare fee-for-service claims
- Creators
- Samantha R. Eiffert - University of North Carolina at Chapel HillBrad Wright - University of South CarolinaJoshua Nardin - University of North Carolina at Chapel HillJames F. Howard - University of North Carolina at Chapel HillRebecca Traub - University of North Carolina at Chapel Hill
- Resource Type
- Journal article
- Publication Details
- Global Epidemiology, Vol.7, 100145
- Publisher
- Elsevier Inc
- DOI
- 10.1016/j.gloepi.2024.100145
- ISSN
- 2590-1133
- eISSN
- 2590-1133
- Language
- English
- Date published
- 06/2024
- Academic Unit
- Public Policy Center (Archive)
- Record Identifier
- 9984625360102771
Metrics
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