UCSF’s TACo Approach to e-Consults

July 6, 2019
EHR identifies patients who meet defined criteria for automatic consultation and presents a customized view of pertinent information to a specialist

Making it easy for clinicians to share data about patients is still a work in progress, but one area where there has been between improvement is in the realm of “e-consultations” within a shared electronic health record.  They allow specialists to address non-urgent questions and make recommendations about treatment of individual patients. Now health systems are starting to automate the consult requests.

A June 2019 story in the Harvard Gazette highlighted how Massachusetts General Hospital (MGH) has grown its e-consult program. MGH began offering e-consults in cardiology and dermatology in late 2013 and extended the program to allergy and immunology in August 2016. As of January 2019, the MGH e-consult program involves 47 specialty areas, and in 2018 it provided almost 10,000 e-consults. A study of their use in allergy and immunology at MGH found that it can simplify the process of providing the most appropriate care, often reducing the need for in-person specialist visits. A paper, which has been published online in the Journal of Allergy and Clinical Immunology: In Practice, reports on the first two years of the MGH program and finds a significant reduction in the time needed to access specialist guidance. Whereas wait times for an in-person patient visit with an allergist often exceed three weeks, e-consults can provide allergist guidance to referring physicians within 72 business hours, the researchers found. For many patients, e-consults avert the need for an in-person visit entirely.

 Even more impressive is some research published recently about process changes made at the University of California San Francisco (UCSF) to automate e-consults based on EHR data.

The research published in JAMA by Robert Wachter, M.D., Timothy Judson, M.D., M.P.H., and Michelle Mourad, M.D., notes that traditionally e-consults “are based on the specialists’ ability to respond to simple diagnostic or management questions by reviewing the patient’s chart electronically and offering recommendations without performing a full history and examination. Some health systems now conduct a significant fraction of their outpatient consults as e-consults, resulting in improved patient access to specialty care.” They point to a Veterans Affairs study of 554 e-consults and 938 traditional consults, which found that e-consults reduced response time by 92% to 95% (i.e., from an average of 34.4 to 2.4 days) across several specialties. But the UCSF researchers note that  because e-consults must usually be initiated by the primary care physician, they may fall short of consistently providing timely specialty expertise for cases in which the need for consultation may not be apparent.

The UCSF Diabetes Service has developed and is using what they call the targeted automatic e-consultation (TACo). In this model, the EHR identifies patients who meet defined criteria for automatic consultation and presents a customized view of the pertinent information to a designated specialist, who then reviews the case virtually. “The consultant can choose to provide targeted advice, suggest formal consultation, or neither,” the researchers note. “Like e-consults, this model allows the specialist to review pertinent information in the EHR and offer a rapid response. Unlike regular e-consults, these targeted automatic consults are triggered by patients’ EHR data rather than a consultation request.”

Here is how it works: Each day, the EHR screens the entire inpatient population for any patient meeting certain criteria and then an experienced diabetologist reviews each case. “If the specialist has a management suggestion, he or she writes a brief consult note with the recommendations. The process takes 2 to 5 minutes per case. Published evidence on the 1,132 admissions that included such virtual consults (representing 4.8% of all hospitalizations during a 12-month period) showed a significant improvement in diabetes management, with a 39 percent decrease in the proportion of patients with hyperglycemia (from 6.6 to 4.0 episodes per 100 patient-days) and a 36 percent decrease in hypoglycemic events during the study period vs rates before the study period (from 0.78 to 0.49 per 100 patient-days).

Based on these outcomes, the model has received sustained financial support for consultant time by the health system, and UCSF plans to expand the number of services offering this type of e-consultation, and study and refine this process. The researchers said they recognize that each use case is likely to present its own opportunities and challenges. 

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