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The American Journal of Managed Care December 2015
Interest in Mental Health Care Among Patients Making eVisits
Steven M. Albert, PhD; Yll Agimi, PhD; and G. Daniel Martich, MD
The Impact of Electronic Health Records and Teamwork on Diabetes Care Quality
Ilana Graetz, PhD; Jie Huang, PhD; Richard Brand, PhD; Stephen M. Shortell, PhD, MPH, MBA; Thomas G. Rundall, PhD; Jim Bellows, PhD; John Hsu, MD, MBA, MSCE; Marc Jaffe, MD; and Mary E. Reed, DrPH
Health IT-Assisted Population-Based Preventive Cancer Screening: A Cost Analysis
Douglas E. Levy, PhD; Vidit N. Munshi, MA; Jeffrey M. Ashburner, PhD, MPH; Adrian H. Zai, MD, PhD, MPH; Richard W. Grant, MD, MPH; and Steven J. Atlas, MD, MPH
A Health Systems Improvement Research Agenda for AJMC's Next Decade
Dennis P. Scanlon, PhD, Associate Editor, The American Journal of Managed Care
An Introduction to the Health IT Issue
Jeffrey S. McCullough, PhD, Assistant Professor, University of Minnesota School of Public Health; Guest Editor-in-Chief for the health IT issue of The American Journal of Managed Care
Preventing Patient Absenteeism: Validation of a Predictive Overbooking Model
Mark Reid, PhD; Samuel Cohen, MD; Hank Wang, MD, MSHS; Aung Kaung, MD; Anish Patel, MD; Vartan Tashjian, BS; Demetrius L. Williams, Jr, MPA; Bibiana Martinez, MPH; and Brennan M.R. Spiegel, MD, MSHS
EHR Adoption Among Ambulatory Care Teams
Philip Wesley Barker, MS; and Dawn Marie Heisey-Grove, MPH
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Impact of a National Specialty E-Consultation Implementation Project on Access
Susan Kirsh, MD, MPH; Evan Carey, MS; David C. Aron, MD, MS; Omar Cardenas, BS; Glenn Graham, MD, PhD; Rajiv Jain, MD; David H. Au, MD; Chin-Lin Tseng, DrPH; Heather Franklin, MPH; and P. Michael Ho, MD, PhD
Patient-Initiated E-mails to Providers: Associations With Out-of-Pocket Visit Costs, and Impact on Care-Seeking and Health
Mary Reed, DrPH; Ilana Graetz, PhD; Nancy Gordon, ScD; and Vicki Fung, PhD
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Yiye Zhang, MS; and Rema Padman, PhD
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Katherine K. Kim, PhD, MPH, MBA; Robert S. Rudin, PhD; and Machelle D. Wilson, PhD
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Eunice Park-Lee, PhD; Vincent Rome, MPH; and Christine Caffrey, PhD
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Dominique Comer, PharmD, MS; Joseph Couto, PharmD, MBA; Ruth Aguiar, BA; Pan Wu, PhD; and Daniel Elliott, MD, MSCE
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Michael F. Furukawa, PhD; Jennifer King, PhD; and Vaishali Patel, PhD, MPH

Impact of a National Specialty E-Consultation Implementation Project on Access

Susan Kirsh, MD, MPH; Evan Carey, MS; David C. Aron, MD, MS; Omar Cardenas, BS; Glenn Graham, MD, PhD; Rajiv Jain, MD; David H. Au, MD; Chin-Lin Tseng, DrPH; Heather Franklin, MPH; and P. Michael Ho, MD, PhD
E-consult implementation grew from 12 to 122 VHA sites with multiple specialties. The adjusted e-consult rate of 1.93/100 consults saved significant patient travel miles and costs.
In the 3 months following a specialty care consult, patients who had received e-consults were less likely to have subsequent face-to-face visits with the same specialty compared with patients with a face-to-face consult (18.6% vs 43.2%; P <.001). In contrast, e-consult patients were more likely to have a subsequent primary care visit compared with patients with a face-to-face consult (78.8% vs 67.4%; P <.001), suggesting that patients receiving an e-consult have a higher probability of follow-up with their PCP for subsequent care compared with patients with a face-to-face specialty care visit.

Finally, we calculated the potential miles needed to travel to receive a face-to-face consult in lieu of an e-consult. Among the 217,014 e-consults, 93% (201,735) had acceptable distance calculations. Among those patients, 52.7% (n = 106,310) received primary care from the same facility; thus there were no potential mileage-traveled differences between an in-person consult and an e-consult. For the 47.3% (n = 95,425) of e-consults for patients from CBOCs, the average potential miles needed to travel was 72.1 miles per patient (SD = 72.6; median = 54.6; IQR = 17.1-108) (see Figure 4). This distance translates into 6,875,631 total potential miles needed to travel. During the time period, the VHA reimbursed patient mileage at a rate of 41.5 cents per mile; thus, the total potential miles needed to travel would translate into potential direct costs of $2,853,387. These mileage estimates are conservative because they are based on “as the crow flies” rather than true distance necessary to be driven.

Our study describes the implementation, spread, and impact of the VHA national e-consult program. Since VHA implementation in 2011, nearly 2% of all consults were e-consults without evidence for a plateau in their use. In addition, receipt of e-consults for patients with primary care at CBOCs was associated with reductions in the total potential miles traveled and travel costs. These findings have important implications for the VHA for addressing both spatial and nonspatial barriers to access for specialty care services, especially for veterans who live in rural communities. Furthermore, our results provide potential approaches to specialty care access for ACOs and other integrated healthcare delivery systems.6 Like other healthcare institutions, VHA has adopted the “triple aim” framework for optimizing healthcare delivery to improve the patient healthcare experience and the health of the patient population while balancing per capita cost.7 The implementation of e-consults is a potential mechanism by which VHA can strive to achieve these aims.8-24

E-consults may improve the overall patient experience of care by reducing inconvenience and waiting times for specialist consultation/input. In addition, patients have the opportunity to avoid long travel distances to see specialists and to obtain specialty advice in a timely manner compared with an in-person visit. For patients who either prefer or require an in-person specialist visit, the initial e-consult may also provide an opportunity to be more prepared for the visit. For example, by arranging for diagnostic or laboratory tests in advance, some visits to the specialist could be avoided and time to needed services potentially decreased. We found that for the majority of consults, an in-person visit did not occur following the e-consult. This finding reinforces the study of Keely et al, who found that specialists were able to answer the e-consult without needing further information 89% of the time.23

E-consults have the potential to improve quality of care for both individuals and the general patient population. First, e-consults improve patient access to specialist expertise, especially for the large number of veterans who live in rural communities. We found higher utilization of e-consults for those in CBOCs and more follow-up appointments with primary care after e-consults than for those patients not receiving e-consults. Second, e-consults promote the use of a standardized referral process with iterative communication that can lead to increased effectiveness of care delivered. In fact, preliminary results of interviews with clinicians have found that both PCPs and specialists value the benefits e-consults have for patients. In addition, e-consults provide an opportunity to improve care coordination for patients as a consequence of better PCP-specialist communication. Third, when combined with the capabilities of an EHR, it is possible to identify populations who would benefit from additional specialty care expertise. “Consultation” may be pre-emptive, thereby avoiding preventable morbidity.25,26 This population management approach will need to be evaluated prospectively.

E-consults may reduce the per capita cost of healthcare from the healthcare system perspective. Reductions may be accomplished by improved efficiency of use of high-cost specialists. On the other hand, increased access to specialists may result in increased testing and consequent expense; healthcare value may improve, albeit without reducing costs.27,28 However, we believe that the overall costs will be less with use of e-consults over time due to primary care coordination. VHA cost structure also has some unique aspects. The VHA outsources specialty care—particularly for rural veterans—because of difficulties for these veterans to access specialists. This so-called “fee-basis” care consumes funds that are used for outside care and do not return to the system. In addition, specific populations of veterans are reimbursed for their travel to clinic visits; generally, this reimbursement is provided to veterans with at least a 30% service-connected disability. The elimination of unnecessary visits subsequently reduces travel reimbursement costs. Finally, efficiency may be improved by better coordination of care and less fragmentation of care.29,30 We are not suggesting that e-consults will obviate the need for face-to-face visits, but this technology-supported platform can optimize efficient use of specialist expertise, which may be limited in differing geographic locations and health systems.

E-consult programs have been established in a variety of healthcare systems. However, in order for e-consults to be more widely adopted, changes to the payment systems are needed. The VHA’s model of salaried physicians and capitated reimbursement provides a more favorable environment for e-consult implementation. In contrast, under the fee-for-service model, specialists must physically see the patient and bill for a separate visit in order to receive payment. Thus, although the reach of technology expands and allows the extension of care delivery into areas where few specialists reside, payment models lag behind and may hinder the potential spread of such programs. It will be important to assess how the different models for reimbursement and shared savings in ACOs under the Affordable Care Act evolve; their effects on different types of specialist care delivery and coordination of care remain to be seen.31-35


Our study has several limitations. First, the rate of increase of e-consults may reflect changes in documentation; formalized coding of e-consults was part of the initiative because of its relevance to tracking patient care and the necessity to capture the work of specialty care providers. Second, the e-consult initiative was conducted within an integrated healthcare delivery system and a single EHR enabling ready access to information for both PCPs and specialists. Nevertheless, trends in use of EHRs and efforts to achieve interoperability may render implementation of e-consults in other settings less difficult in the future. The logistical issues for implementing such a system in the fee-for-service sector are likely to be different. This may include recognition that some healthcare systems may need to contract out for specialist care; contracted specialists may not be interested in supporting large-scale e-consult initiatives. However, as the country moves toward ACOs, the lessons learned in implementing this initiative in the VHA may be applicable to ACOs. Finally, although the number of e-consults has increased, we do not know if these e-consults have resulted in improved patient outcomes. Future studies must be done to address any potential unintended consequences for patients, clinicians, and healthcare systems, as well as other unanswered questions. Last, the patients’ perspectives need to be considered and to that end, we will be conducting interviews with patients in the near future to obtain their feedback and experience with e-consults.

Since the e-consult initiative rolled out in 2011, there has been a steady increase in the use of e-consults across 21 networks and for a diverse group of specialties. Specifically, the number of patients with primary care at CBOCs—which are relatively remote from sites where specialists are located—receiving an e-consult has increased. Use of e-consults has been associated with reductions in potentially unnecessary driving, as evidenced by potential miles saved. These findings have important implications for the VHA in terms of increasing access to specialty care in general and to veterans who live in rural communities in particular, and the findings may apply to other healthcare systems.


The authors thank the Evaluation Center Quantitative Analysis Group: Jackie Szarka, PhD; Jeffrey A. Todd-Stenberg, BA; Christian D. Helfrich, PhD, MPH; Anne C. Lambert-Kerzner, PhD, MSPH; Catherine T. Battaglia, PhD, MS; Thomas J. Glorioso, MS; Kent Davis; Katherine M. Fagan Williams, MPH. All authors and the Evaluation Center Quantitative Group had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Author Affiliations: Office of Specialty Care Services (SK, OC, GG), Patient Care Services (RJ), Veterans Health Administration, Washington, DC; Louis Stokes Cleveland VA Medical Center (SK, DCA), Cleveland, OH; Case Western Reserve University School of Medicine (SK, DCA), Cleveland, OH; Eastern Colorado VA Medical Center (EC, PMH), Denver, CO; Puget Sound Health Services Research & Development Center of Innovation, Department of Veterans Affairs (DHA), Seattle, WA; Department of Medicine, University of Washington (DHA), Seattle, WA; New Jersey Veterans Health Care System, East Orange Campus (C-LT, HF), East Orange, NJ

Source of Funding: This material is based upon work supported by the US Department of Veterans Affairs, the Office of Specialty Care Transformation and the Office of Research and Development Quality Enhancement Research Initiative.

Author Disclosures: The authors are employed by the VA and this work was funded, in part, by the VA Office of Specialty Care Transformation, the office overseeing the e-consult initiative. The views expressed here do not necessarily reflect the position or policy of the Department of Veterans Affairs. The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (OC, HF, DHA, DCA, GG, RJ, PMH, EC, SK); acquisition of data (DHA, GG, EC, SK); analysis and interpretation of data (OC, HF, DHA, C-LT, DCA, GG, RJ, EC, SK); drafting of the manuscript (DHA, C-LT, DCA, EC, SK); critical revision of the manuscript for important intellectual content (OC, DHA, DCA, GG, RJ, PMH, EC, SK); statistical analysis (HF, C-LT, EC, SK); provision of patients or study materials (GG, SK); obtaining funding (OC, DHA, DCA, SK); administrative, technical, or logistic support (DHA, GG, PMH, SK); and supervision (DHA, GG, RJ, SK).

Address correspondence to: Susan Kirsh, MD, MPH, Case Western Reserve University School of Medicine, 10701 East Blvd, Cleveland, OH 44106. E-mail:
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