Evaluating e-consultation implementations based on use and time-line across various specialties.

Background: Electronic Consultation (e-consults) can provide improved access, enhance patient and provider satisfaction, and reduce beneficiary travel expenses. We explored how e-consults were implemented across three specialty areas, diabetes (Diab), gastroenterology (GI), and neurosurgery (Neuro), at two Veterans Affairs hospitals in terms of strategies for use and time-lines.

Methods: We conducted observations and electronically shadowed patient e-consultations submitted to a specialty care service by primary care provider(s) at the two sites during a thirteen-month period. We divided the e-consult process in each specialty into three broad milestones; Request (from primary to specialty), Response (from specialty back to primary), and Follow up (from primary to patient), and recorded the flow and time in each category. An overall hierarchy of e-consults was developed to illustrate the many ways an e-consult was used. The Kolmogorov-Smirnov test was used to compare the distribution of time across specialties.

Results: A total of 394 consults submitted between April 14, 2012 and May 2, 2013 were reviewed (Diab=152, GI=169, Neuro=73). Of the 152 diabetes specialty clinic e-consults, 35% required some sort of direct contact with the patient by the specialty clinic before a recommendation was provided. Overall, 58% of the e-consults were completed within 20days, while 68% were completed within 30days. The Response times between Diab and GI were significantly different (median=0 vs. 3days; p<0.0001) and so were Follow up times (median=0 vs. 4days; p<0.0001). All three stages were statistically different between Diab and Neuro; however, there was not enough evidence to suggest any differences between GI and Neuro.

Conclusions: The use of an e-consult is likely to vary based on the specialty, but the often significant variations in time may continue to hinder prompt access to care. E-consult design, implementation, documentation, training, self-learning, and monitoring should be tailored to get the most benefit out of this system.