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The following is a summary of “Optimizing identification of Lyme disease diagnoses in commercial insurance claims data, United States, 2016–2019,” published in the November 2024 issue of Infectious Disease by Nawrocki et al.
Commercial insurance claims data offer a dependable window into Lyme disease trends, improving the understanding of its impact and tracking its spread across the United States.
Researchers conducted a retrospective study to assess the accuracy of algorithms using diagnosis codes and antimicrobial treatment data for identifying Lyme disease in commercial insurance claims.
They developed 3 modified versions of their existing claims-based Lyme disease algorithm, refining criteria for antimicrobial prescriptions and maximum days between diagnosis code and qualifying prescription claim. These algorithms were applied to a large national commercial claims database to identify Lyme disease diagnoses during 2016-2019. The characteristics of Lyme disease diagnoses identified by each modified algorithm were compared to those identified by the original algorithm to assess differences in demographics, seasonality, and geography.
The results showed that differences in characteristics of patients diagnosed by the 3 modified algorithms and the original algorithm were minimal, with variations in age and sex being small enough to potentially be due to chance. However, 1 modified algorithm recognized a higher proportion of diagnoses in men during peak summer months and in high-incidence regions, aligning more closely with epidemiological trends observed in public health surveillance. This algorithm restricted treatment to first-line recommended antimicrobials, reducing the timeframe between the Lyme disease diagnosis code and the qualifying prescription claim.
Investigators concluded the modified algorithm determines antimicrobial prescriptions and curtails the timeframe between diagnosis codes and qualifying prescription claims, might more accurately recognize Lyme disease diagnoses in insurance claims data.
Source: bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-024-10195-5
