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BACKGROUND: With the rapid development of new advanced molecular detection methods, identification of new genetic mutations conferring pathogen resistance to an ever-growing variety of antimicrobial substances will generate massive genomic datasets for public health and clinical laboratories. Keeping up with specialized standard coding for these immense datasets will be extremely challenging. This challenge prompted our effort to create a common molecular resistance Logical Observation Identifiers Names and Codes (LOINC) panel that can be used to report any identified antimicrobial resistance pattern. OBJECTIVE: To develop and utilize a common molecular resistance LOINC panel for molecular drug susceptibility testing (DST) data exchange in the U.S. National Tuberculosis Surveillance System using California Department of Public Health (CDPH) and New York State Department of Health as pilot sites. METHODS: We developed an interface and mapped incoming molecular DST data to the common molecular resistance LOINC panel using Health Level Seven (HL7) v2.5.1 Electronic Laboratory Reporting (ELR) message specifications through the Orion Health™ Rhapsody Integration Engine v6.3.1. RESULTS: Both pilot sites were able to process and upload/import the standardized HL7 v2.5.1 ELR messages into their respective systems; albeit CDPH identified areas for system improvements and has focused efforts to streamline the message importation process. Specifically, CDPH is enhancing their system to better capture parent-child elements and ensure that the data collected can be accessed seamlessly by the U.S. Centers for Disease Control and Prevention. DISCUSSION: The common molecular resistance LOINC panel is designed to be generalizable across other resistance genes and ideally also applicable to other disease domains. CONCLUSION: The study demonstrates that it is possible to exchange molecular DST data across the continuum of disparate healthcare information systems in integrated public health environments using the common molecular resistance LOINC panel.
RESUMEN
BACKGROUND: Our goal was to describe the characteristics and posttreatment outcomes of pediatric patients with central nervous system (CNS) tuberculosis (TB) and to identify factors associated with poor outcome. METHODS: We included children aged 0 to 18 years with CNS TB reported to the California TB registry between 1993 and 2011. Demographics, clinical characteristics, severity of disease at presentation (Modified Medical Research Council stage I, II, or III [III is most severe]), treatment, and outcomes during the year after treatment completion were abstracted systematically from the medical and public health records. Patient outcomes were categorized as good or poor on the basis of disability in hearing, vision, language, ambulation, and development and other neurologic deficits. RESULTS: Among 151 pediatric CNS TB cases reported between 1993 and 2011 in California for which records were available, 92 (61%) cases included sufficient information to determine outcome. Overall, 55 (60%) children had a poor outcome. After we adjusted for age (0 to 4 years), children with stage III severity (vs I or II; prevalence rate ratio [PRR], 1.4 [95% confidence interval (CI), 1.1-1.9]), a protein concentration of >100 mg/dL on initial lumbar puncture (PRR, 1.2 [95% CI, 1.03-1.4]), or infarct on neuroimaging (PRR, 1.2 [95% CI, 1.04-1.3]) were at increased risk for a poor outcome. In multivariate analysis, an age of 0 to 4 years (vs >4 years; PRR, 1.4 [95% CI, 1.2-1.7]) and a stage II or III Modified Medical Research Council score (vs stage I; PRR, 1.2 [95% CI, 1.03-1.5]) remained significantly associated with poor outcome. CONCLUSIONS: Pediatric patients with CNS TB in California are left with high rates of disabling clinical sequelae after treatment. The identification of modifiable factors is critical for improving outcomes.