Optimizing identification of Lyme disease diagnoses in commercial insurance claims data, United States, 2016–2019
As compared to our original algorithm, a modified algorithm that limits the antimicrobials prescribed and shortens the timeframe between a diagnosis code and a qualifying prescription claim might more accurately identify Lyme disease diagnoses when utilizing insurance claims data for supplementary, routine identification and monitoring of Lyme disease diagnoses.
Authors
- Alison F. Hinckley (ORCID: https://orcid.org/0000-0003-2853-5165)
- Courtney C. Nawrocki (ORCID: https://orcid.org/0000-0001-7754-6480)
- Kiersten J. Kugeler (ORCID: https://orcid.org/0000-0002-5702-6688)
- Austin Earley (ORCID: https://orcid.org/0000-0002-1401-3350)
- Sarah A. Hook (ORCID: https://orcid.org/0000-0002-4981-1053)
Institutions
- Oak Ridge Associated Universities (US)
- Centers for Disease Control and Prevention (US)
- Oak Ridge Institute for Science and Education
Publication Details
- Journal
- BMC Infectious Diseases
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1186/s12879-024-10195-5
- Citations
- 4
- Primary Topic
- Vector-borne infectious diseases
- Type
- article
- Field-Weighted Citation Impact
- 2.06
Funders
- Centers for Disease Control and Prevention