Claims-Based Diagnostic Patterns of Patients Evaluated for Lyme Disease and Given Extended Antibiotic Therapy

Healthcare claims-based Lyme disease case-finding algorithms in the United States: A systematic literature review

BACKGROUND AND OBJECTIVE

Lyme disease (LD) is the fifth most commonly reported notifiable infectious disease in the United States (US) with approximately 35,000 cases reported in 2019 via public health surveillance. However, healthcare claims-based studies estimate that the number of LD cases is >10 times larger than reported through surveillance. To assess the burden of LD using healthcare claims data and the effectiveness of interventions for LD prevention and treatment, it is important to use validated well-performing LD case-finding algorithms ("LD algorithms"). We conducted a systematic literature review to identify LD algorithms used with US healthcare claims data and their validation status.

METHODS

We searched PubMed and Embase for articles published in English since January 1, 2000 (search date: February 20, 2021), using the following search terms: (1) "Lyme disease"; and (2) "claim*" or "administrative* data"; and (3) "United States" or "the US*". We then reviewed the titles, abstracts, full texts, and bibliographies of the articles to select eligible articles, i.e., those describing LD algorithms used with US healthcare claims data.

RESULTS

We identified 15 eligible articles. Of these, seven studies used LD algorithms with LD diagnosis codes only, four studies used LD diagnosis codes and antibiotic dispensing records, and the remaining four studies used serologic test order codes in combination with LD diagnosis codes and antibiotics records. Only one of the studies that provided data on algorithm performance: sensitivity 50% and positive predictive value 5%, and this was based on Lyme disease diagnosis code only.

CONCLUSIONS

US claims-based LD case-finding algorithms have used diverse strategies. Only one algorithm was validated, and its performance was poor. Further studies are warranted to assess performance for different algorithm designs and inform efforts to better assess the true burden of LD.

dxpr: an R package for generating analysis-ready data from electronic health records-diagnoses and procedures

BACKGROUND

Enriched electronic health records (EHRs) contain crucial information related to disease progression, and this information can help with decision-making in the health care field. Data analytics in health care is deemed as one of the essential processes that help accelerate the progress of clinical research. However, processing and analyzing EHR data are common bottlenecks in health care data analytics.

METHODS

The dxpr R package provides mechanisms for integration, wrangling, and visualization of clinical data, including diagnosis and procedure records. First, the dxpr package helps users transform International Classification of Diseases (ICD) codes to a uniform format. After code format transformation, the dxpr package supports four strategies for grouping clinical diagnostic data. For clinical procedure data, two grouping methods can be chosen. After EHRs are integrated, users can employ a set of flexible built-in querying functions for dividing data into case and control groups by using specified criteria and splitting the data into before and after an event based on the record date. Subsequently, the structure of integrated long data can be converted into wide, analysis-ready data that are suitable for statistical analysis and visualization.

RESULTS

We conducted comorbidity data processes based on a cohort of newborns from Medical Information Mart for Intensive Care-III (n = 7,833) by using the dxpr package. We first defined patent ductus arteriosus (PDA) cases as patients who had at least one PDA diagnosis (ICD, Ninth Revision, Clinical Modification [ICD-9-CM] 7470*). Controls were defined as patients who never had PDA diagnosis. In total, 381 and 7,452 patients with and without PDA, respectively, were included in our study population. Then, we grouped the diagnoses into defined comorbidities. Finally, we observed a statistically significant difference in 8 of the 16 comorbidities among patients with and without PDA, including fluid and electrolyte disorders, valvular disease, and others.

CONCLUSIONS

This dxpr package helps clinical data analysts address the common bottleneck caused by clinical data characteristics such as heterogeneity and sparseness.

Challenges in the Diagnosis and Treatment of Lyme Disease

PURPOSE OF REVIEW

Since recognition in 1975, Lyme disease has become the most common vector-borne illness in North America and Europe. The clinical features are well-characterized and treatment is usually curative, but misperceptions about morbidity persist. The purpose of this review is to examine advances in the diagnosis and treatment of Lyme disease, as well as ongoing management challenges.

RECENT FINDINGS

It is useful to recognize that Lyme disease occurs in stages, with early- and late-stage disease. Clinical expression is in part determined by Borrelial variability. For example, some strains of Borrelia burgdorferi, the causative organism in North America, are particularly arthritogenic. Most patients with early Lyme disease can be cured with a single course of oral antibiotic therapy, in contrast to some patients with Lyme arthritis, a late-stage manifestation, who are more antibiotic refractory and require other treatment strategies. Successful treatment of Lyme disease begins with successful diagnosis and with an understanding of the emergence, clinical features, and impact of Lyme disease over the past half century.