Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults.

"Conflicts of Interest: Research conducted by RB is supported by grants to the University of Wisconsin by the Heffter Research Institute, Usona Institute, Revive Therapeutics, and the Etheridge Foundation. MMC is a named inventor on a patent for a risk stratification algorithm for hospitalized patients (US patent #11,410,777)."

"The authors acknowledge support from the University of Wisconsin Institute for Clinical and Translational Research, which, in turn, is supported by the Clinical and Translational Science Award program through the National Institutes of Health National Center for Advancing Translational Sciences grant (2UL1TR002373). The research was also supported by the National Institute on Drug Abuse of the National Institutes of Health (R01DA051464; CJ, DD, MA, and RB), National Library of Medicine Temporal Histories of Your Medical Event (THYME) project (R01LM010090; DD), and National Institute of Diabetes and Digestive and Kidney Diseases R01DK126933). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the other funding sources listed in this section. Our implementation framework is largely guided by a team of implementation scientists supported by the UW’s Clinical and Translational Science Award. We leveraged our Clinical and Translational Science Award’s Dissemination and Implementation Launchpad to help bridge the gap between evidence-based research and practice []. The Dissemination and Implementation Launchpad serves to accelerate the pace of disseminating research findings and increase the adoption and implementation of effective interventions, leading to sustainable practice and policy changes. It uses strategies from implementation science, design thinking, and human-centered engineering for the better integration of AI technologies into health systems. As part of the preimplementation phase, we assessed contextual factors that may impact implementation by engaging both adopters, who are the decision-makers, and end users, who are the main implementers, of the tool []. We conducted qualitative interviews with end users to evaluate the need for the tool and BPA design. We involved adopters early in the process to inform the intervention or implementation process through consultations during the design, feasibility testing, and implementation phases. An iterative process ensued to address the constraints and contextual factors that affect the adoption and implementation of the tool in our health system. Conflicts of Interest: Research conducted by RB is supported by grants to the University of Wisconsin by the Heffter Research Institute, Usona Institute, Revive Therapeutics, and the Etheridge Foundation. MMC is a named inventor on a patent for a risk stratification algorithm for hospitalized patients (US patent #11,410,777)."

"Trial Registration ClinicalTrials.gov NCT05745480; https://www.clinicaltrials.gov/ct2/show/NCT05745480"