Traditional specialty consults are resource intensive and may be delayed or omitted if the treating physician does not recognize the need for specialty advice. Targeted automatic e-consults (TACos) address these limitations by prospectively identifying patients using the electronic health record (EHR) and presenting pertinent information on a dashboard, enabling consultants to provide a virtual consult with written recommendations. The TACo model may improve value by facilitating more expert input without a proportional increase in cost. Through our experience developing a TACo program, we have identified four key steps. First, identify appropriate conditions that have support from the health system and from frontline clinicians. Second, design the digital infrastructure, including lists and dashboards. Third, create a funding plan to support the consultant's time, either through internal grants, external grants, e-consult billing codes, or some combination of the three. Fourth, pilot on a select number of services, iterate, and scale. Funding for TACos has been a major barrier to adoption. Fortunately, new e-consult billing codes may make it possible to recoup as least part of the program's cost. Technological hurdles also exist, particularly in building real-time lists within the EHR to prospectively identify patients based on complex criteria. We look for this model to gain popularity as evidence of clinical and operational benefit mounts. We anticipate reimbursement policies may be updated to support this type of consult. Finally, we expect machine learning to play a role in identifying patients and providing recommendations in the future. Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.
Timothy J Judson, Michelle Mourad, Robert M Wachter. Building a Targeted Automatic e-Consult (TACo) Program. Joint Commission journal on quality and patient safety. 2022 Feb;48(2):114-119
PMID: 34933816
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