Project Summary Over the past decade, there has been a growing epidemic of physician burnout, driven most notably, by Electronic Health Records (EHR), and the increasing amount of time providers spend on them. A number of solutions have been developed to untether the provider from the EHR. Prior to the COVID-19 pandemic, the two most widely adopted solutions were Speech Recognition (SR) and Medical Scribes (MS). The pandemic has worsened many of these preexisting issues with EHR, and with the broad adoption of telemedicine, creating new sociotechnical concerns. Fueled in part by this, 2 additional solutions, Virtual Scribes (VS) and Digital Scribes (DS) have begun to be employed for both in-person and telemedicine visits. We have previously performed a mixed methods evaluation of MS documenting significant barriers to successful adoption with significant variance in practice and outcomes. In spite of this rapid expansion of options, there is little information available directly to compare and contrast the ways they are co-opting provider work in the EHR, or their impact on provider activity in the EHR, medical record completion/accuracy, and safety issues. At OHSU, providers who adopt MS have baseline longer times to chart completion and significant greater amount of after-hours record completion, and use of a MS or SR had no impact on these metrics, with many, higher performing providers, worsening with MS adoption. These trends persisted and even widened with the use of telemedicine. The goal of this project is to expand upon these initial findings and use a mixed methods approach to determine the impact of EHR documentation assistance solutions on EHR use and provider workflow in ambulatory care. In Aim #1, we will adapt the Rapid Assessment Protocol (RAP) for in-person and virtual evaluation to expand on our prior work with MS to evaluate the impact of MS, VS, SR, and DS on provider workflow in the context of in-person and telemedicine visits. We will then convene a multidisciplinary stakeholder group to review these findings to come up with a series of metrics, both quantitative and simulation based, to allow for assessment of the 4 modalities. In Aim #2, we will use EHR audit logs to determine the impact of adoption of each of these 4 modalities, including data from OHSU and Medstar Health to improve generalizability, control for various EHR systems and allow for anchoring back to the qualitative data in Aim #1. In Aim #3, we will use the data from the first 2 aims, to create a high-fidelity simulation to all for direct head-to-head comparison of the 4 modalities on measures not reliably extracted from EHR audit logs including note accuracy, time-on-task, EHR navigation and patient-provider communication. In Aim #4, we will define and create a success matrix for selection of DA modalities to guide decision making on the use of appropriate DA resources for a given specialty type and location. We will also create a Documentation Assistance ...