NDLI: Risk factors for Lyme disease stage and manifestation using electronic health records

Content Provider	Springer Nature : BioMed Central
Author	Moon, Katherine A. Pollak, Jonathan S. Poulsen, Melissa N. Heaney, Christopher D. Hirsch, Annemarie G. Schwartz, Brian S.
Abstract	Background Little is known about risk factors for early (e.g., erythema migrans) and disseminated Lyme disease manifestations, such as arthritis, neurological complications, and carditis. No study has used both diagnoses and free text to classify Lyme disease by disease stage and manifestation. Methods We identified Lyme disease cases in 2012–2016 in the electronic health record (EHR) of a large, integrated health system in Pennsylvania. We developed a rule-based text-matching algorithm using regular expressions to extract clinical data from free text. Lyme disease cases were then classified by stage and manifestation using data from both diagnoses and free text. Among cases classified by stage, we evaluated individual, community, and health care variables as predictors of disseminated stage (vs. early) disease using Poisson regression models with robust errors. Final models adjusted for sociodemographic factors, receipt of Medical Assistance (i.e., Medicaid, a proxy for low socioeconomic status), primary care contact, setting of diagnosis, season of diagnosis, and urban/rural status. Results Among 7310 cases of Lyme disease, we classified 62% by stage. Overall, 23% were classified using both diagnoses and text, 26% were classified using diagnoses only, and 13% were classified using text only. Among the staged diagnoses (n = 4530), 30% were disseminated stage (762 arthritis, 426 neurological manifestations, 76 carditis, 95 secondary erythema migrans, and 76 other manifestations). In adjusted models, we found that persons on Medical Assistance at least 50% of time under observation, compared to never users, had a higher risk (risk ratio [95% confidence interval]) of disseminated Lyme disease (1.20 [1.05, 1.37]). Primary care contact (0.59 [0.54, 0.64]) and diagnosis in the urgent care (0.22 [0.17, 0.29]), compared to the outpatient setting, were associated with lower risk of disseminated Lyme disease. Conclusions The associations between insurance payor, primary care status, and diagnostic setting with disseminated Lyme disease suggest that lower socioeconomic status and less health care access could be linked with disseminated stage Lyme disease. Intervening on these factors could reduce the individual and health care burden of disseminated Lyme disease. Our findings demonstrate the value of both diagnostic and narrative text data to identify Lyme disease manifestations in the EHR.
Related Links	https://bmcinfectdis.biomedcentral.com/counter/pdf/10.1186/s12879-021-06959-y.pdf
Ending Page	13
Page Count	13
Starting Page	1
File Format	HTM / HTML
ISSN	14712334
DOI	10.1186/s12879-021-06959-y
Journal	BMC Infectious Diseases
Issue Number	1
Volume Number	21
Language	English
Publisher	BioMed Central
Publisher Date	2021-12-20
Access Restriction	Open
Subject Keyword	Infectious Diseases Parasitology Medical Microbiology Tropical Medicine Internal Medicine Lyme disease Tick-borne disease Electronic health records Epidemiology Disease stage Disseminated Lyme disease
Content Type	Text
Resource Type	Article
Subject	Infectious Diseases
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	3.3/2023

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