Enhancing Research Data Infrastructure to Address the Opioid Epidemic: The Opioid Overdose Network (02-Net)

Objective: Opioid Overdose Network is an effort to generalize and adapt an existing research data network, the Accrual to Clinical Trials (ACT) Network, to support the design of trials for survivors of opioid overdoses presenting to emergency departments (ED). Four institutions (Medical University of South Carolina (MUSC), Dartmouth Medical School (DMS), University of Kentucky (UK), and University of California San Diego (UCSD)) worked to adapt ACT network. This paper reports their progress. Materials and Methods: The approach that was taken to enhancing ACT network focused on four activities: cloning and extending the ACT infrastructure, developing an e-phenotype and corresponding registry, developing portable natural language processing (NLP) tools to enhance data capture, and developing automated documentation templates to enhance extended data capture. Results: All four institutions were able to replicate their i2b2 and Shared Health Research Information Network (SHRINE) infrastructure. A five-category e-phenotype model based on ICD-10 coding was developed from prior published work. Ongoing work is refining this via machine learning and artificial intelligence methods. Portable NLP tools, focused on the sentence level, were also developed to identify uncoded opioid overdose-related concepts in provider notes. Optimal performance was seen in NLP tools that combined rule-based with deep learning methods (F score, 0.94). A template for ED overdose documentation was developed to improve primary data capture. Interactive prompts to physicians inside ED progress notes were effective in promoting the use of the template. The template had good system usability and net promoter scores (0.72 and 0.75, respectively, n=13). Discussion: Results suggested that tailoring of existing multipurpose research networks to a specific task is feasible: however, substantial efforts were required for coordination of the subnetwork and development of new tools for extension of available data.