Validation of Algorithms to Detect Acute and Disseminated Lyme Disease in U.S. Administrative Claims Data

This study found that claims-based algorithms requiring diagnosis codes for LD or for related symptoms, in addition to other criteria, can identify cohorts of true LD cases. These algorithms, adjusted for PPV, can be used to estimate LD incidence in the United States.

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Publication Details

Journal
Open Forum Infectious Diseases
Published
2025-02-27
DOI
https://doi.org/10.1093/ofid/ofaf109
Citations
1
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
1.35
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Validation of Algorithms to Detect Acute and Disseminated Lyme Disease in U.S. Administrative Claims Data

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1 citations
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Data-Driven Disease Surveillance
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article

Validation of Algorithms to Detect Acute and Disseminated Lyme Disease in U.S. Administrative Claims Data

Sheryl A. Kluberg, Robert T. Greenlee, Anna M. Schotthoefer, Jennifer C. Moïsi, Maria E. Sundaram, James H. Stark, Sarah J Willis, Cheryl N. McMahill‐Walraven, Thomas G. Boyce, Noelle M. Cocoros, Luis Jódar, John N. Aucott, Djeneba Audrey Djibo, H. J. O’Neill
article en
1 citations

Abstract

This study found that claims-based algorithms requiring diagnosis codes for LD or for related symptoms, in addition to other criteria, can identify cohorts of true LD cases. These algorithms, adjusted for PPV, can be used to estimate LD incidence in the United States.

Open Forum Infectious DiseasesVol. 12(4)
Marshfield Clinic (US), Harvard University (US), Johns Hopkins University (US), Pfizer (United States) (US), Johns Hopkins Medicine (US), Marshfield Clinic (US), Harvard Pilgrim Health Care (US), CVS Health (United States) (US), Health Solutions (Sweden) (SE), Pfizer (France) (FR), Marshfield Clinic (US)
Openalex Percentile: Top 22%
Data-Driven Disease Surveillance
1.35
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