Evidence map›Paper›PMID 39906321›Full record

ArticleOpen forum infectious diseases2025

Epidemiology of Lyme Disease as Identified Through Electronic Health Records in a Large Midwestern Health System, 2016-2019.

Kiersten J Kugeler, Erica Scotty, Alison F Hinckley, Sarah A Hook, Courtney C Nawrocki, Anne M Nikolai, Alexandra M Linz, Jennifer Meece, Anna M Schotthoefer

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kiersten J KugelerCenters for Disease Control and Prevention, Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.ORCID https://orcid.org/0000-0002-5702-6688
Erica ScottyMarshfield Clinic Research Institute, Marshfield Clinic Health System, Marshfield, Wisconsin, USA.
Alison F HinckleyCenters for Disease Control and Prevention, Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.
Sarah A HookCenters for Disease Control and Prevention, Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.
Courtney C NawrockiCenters for Disease Control and Prevention, Division of Vector-Borne Diseases, Fort Collins, Colorado, USA.
Anne M NikolaiMarshfield Clinic Research Institute, Marshfield Clinic Health System, Marshfield, Wisconsin, USA.
Alexandra M LinzMarshfield Clinic Research Institute, Marshfield Clinic Health System, Marshfield, Wisconsin, USA.ORCID https://orcid.org/0000-0002-7551-4810
Jennifer MeeceMarshfield Clinic Research Institute, Marshfield Clinic Health System, Marshfield, Wisconsin, USA.
Anna M SchotthoeferMarshfield Clinic Research Institute, Marshfield Clinic Health System, Marshfield, Wisconsin, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lyme disease is the most common vector-borne disease in the United States; however, its frequency is not reliably measured through surveillance. Electronic health records (EHR) might capture the frequency and characteristics of Lyme disease cases more accurately. We queried EHR from 1 health system to describe the epidemiology of Lyme disease cases in Wisconsin during 2016-2019. Methods: Within a cohort of persons evaluated for Lyme disease, we applied a Lyme disease case definition based on first-line antibiotics within 14 days of a Lyme disease diagnosis code or test order or on the same day as a related keyword in clinical notes. We compared characteristics of cases to those of cases reported through surveillance and reviewed medical charts to assess case definition validity. Results: Among 67 289 possible Lyme disease events in the cohort, 13 494 (20.1%) met our Lyme disease case definition. Cases were more common among males, children 5-9 years, older adults, White non-Hispanic persons, and in the summer months. EHR-based Lyme disease incidence was 4-8 times that reported through surveillance. The EHR definition had moderately high sensitivity (83.4%) and specificity (71.1%) for confirmed and probable Lyme disease. Conclusions: EHR queries show promise to capture the incidence of Lyme disease more completely and provide more robust clinical information than public health surveillance. Demographic and seasonal characteristics of EHR-identified cases were comparable to those identified through surveillance. Further algorithm refinement might improve accuracy of measuring Lyme disease in EHR systems.

Indexed as

electronic health recordsepidemiologyLyme diseasesurveillancetick-borne

Identifiers

PMID39906321
PMCPMC11793028

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.