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The American Journal of Managed Care December 2015
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Interest in Mental Health Care Among Patients Making eVisits
Steven M. Albert, PhD; Yll Agimi, PhD; and G. Daniel Martich, MD
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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
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Interest in Mental Health Care Among Patients Making eVisits

Steven M. Albert, PhD; Yll Agimi, PhD; and G. Daniel Martich, MD
Some patients using a patient portal for eVisits seek mental health care even when it is not designated for such use.
Table 1 shows single-level CCS diagnoses for patients making use of the “other” option for their eVisits. “Mental illness” was the second most common diagnosis for these eVisits, accounting for 12.6% (108/858) of “other” eVisits; 13.4% (92/685) of all patients using the “other” category had a mental health eVisit. All told, patients receiving mental health diagnoses represented 4% (92/2292) of eVisit patients. Level 2 CCS diagnoses for people receiving “mental illness” diagnoses are shown in Table 2. Of the 108 diagnoses, 62 (57.4%) involved anxiety disorders and 36 (33.3%) mood disorders.

Differences Between Patients Making eVisits for Mental Health and Other eVisit Patients

Patients who made an eVisit and received a mental health diagnosis were younger (41.1 ± 12.4 years) than patients making standard eVisits (46.1 ± 13 years) and patients with “other” eVisits that did not involve a mental health diagnosis (46.4 ± 13.6 years; P  = .001). They were also more likely to be female (82.6% vs 71.5% and 70.2%, respectively; P = .047).

Physician Response to Mental Health eVisits

The length of time between initiation of eVisits by patients and response by physicians differed by type of eVisit and mental health diagnosis. Physicians responded to patients and made the diagnosis on the same day for 80.3% of standard eVisits, 74.2% of “other” eVisits that did not involve a mental health diagnosis, and 71.0% of “other” eVisits that involved a mental health diagnosis (P <.001). More generally, physicians responded on the same day in 79% of eVisits not involving mental health diagnoses and in 71% for eVisits with a mental health diagnosis (P = .054).

DISCUSSION
In the first 3 years of our experience with eVisits, 4% of patients received mental health diagnoses despite lack of an explicit mental health eVisit option. These patients were diagnosed after choosing the “other” option and describing symptoms in free-text format. In the absence of structured eVisits to address mental health conditions, individuals seeking mental health care appear to self-select through use of the “other” eVisit option. These patients were younger than patients making use of structured eVisits. If the list of eVisit conditions explicitly included anxiety or depression, it is possible that the prevalence of mental health diagnoses among eVisit patients would be similar to the 10% prevalence seen in primary care.11 Although we were unable to establish the severity of depression or anxiety diagnosed in the eVisit, results from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) cohort suggest that patients with nonpsychotic major depressive disorders followed in primary care and specialty care are similar in symptom severity.12 Thus, the eVisit diagnosis may capture significant symptomatology and may be an important entry route for mental health care.

Limitations

This study is limited by the lack of data outside those related to a specific eVisit. Thus, we were unable to determine outcomes for patients receiving mental health diagnoses following the eVisit, such as how many completed in-person assessments or received referrals to psychiatric services. In the future, it will be valuable to track patient outcomes following receipt of mental health diagnoses in an eVisit and to compare the clinical care provided in eVisits to care resulting from visits with a primary care provider.

However, even the limited data available for this research suggest important differences in the ways clinicians currently handle eVisits resulting in mental health diagnoses. It took longer for physicians to reply to patients reporting mental health symptoms than patients reporting other kinds of symptoms. Some of this difference may be related to the free-text format of the nonstructured eVisit, but it is also possible that review of mental health symptoms reported in eVisits requires greater attention and messaging contact with patients. 

Additional limitations of this research include its focus on a particular health system patient portal and only 1 eVisit technology. For example, we were unable to assess the effect of a greater or lesser number of condition pathways in the content of the eVisit “other” category. Yet, we note that most of the “other visit” diagnoses were actually appropriate for available condition pathways (for example, nearly 20% involved respiratory conditions despite a number of potentially appropriate eVisit symptom and condition pathways [eg, cold, cough, flu, sinusitis, bronchitis, pneumonia, sore throat, strep throat]). This is not the case for mental health conditions, which are not addressed by any of the other condition or symptom pathways. Thus, we would argue that the relatively high use of the “other” category for mental health conditions (13.4% among patients choosing the “other” option) and the 4% prevalence for mental health eVisits overall is not likely to differ unless mental health eVisits are added as a condition-specific option. We note, as well, that although eHealth portals continue to change, the UPMC portal has not changed its eVisit options or underlying questionnaires and branching logic since its expansion to 22 conditions.

CONCLUSIONS
If patients seek eVisits for mental health conditions even when the option is not explicitly offered, what can we conclude? One key conclusion is the need to develop a mental health eVisit and, more broadly, Web-based tools to address mental health symptoms. Research suggests that Internet-based tools are effective for screening and delivery of mental health services.9 For example, Internet-based screening questions for diagnosing major depressive disorder yield a sensitivity of 0.95 and specificity of 0.87 with as few as 4 items,13 and similar results have been shown for Internet-based screening for anxiety disorders.14 Beyond diagnostic tools, Internet-based delivery of psychotherapy appears to be as effective as traditional in-person therapy15 and may be a reasonable firstline treatment for many patients making eVisits. Internet-based therapy for mental health conditions can be effective even without in-person personal contact.16 As the evidence base for eVisits grows, it will be important to ensure full consideration of eVisits for mental health care.

Still, mental health may offer particular challenges for eVisits. One set of criteria proposed for effective Internet-based medical care includes the following: 1) the medical problem should have a clear “diagnostic data set” accessible to a patient and easily articulated in an online encounter; 2) patients should understand that the online interaction is problem-specific and may carry risks; and 3) treatment decisions should be algorithmic and not require a personal relationship with a physician because of emotional valence or medical history.17 Mental health eVisits may satisfy the first 2 criteria, given the availability of reliable self-report instruments and use of cautions appropriate for all online clinical encounters. The third may be more challenging because of the nature of mental and behavioral health and the importance of personal physician relationships as part of the therapy for these conditions. Assessment of the efficacy of mental health eVisits for diagnosis and entry to care remains an important area for future research. The current research helps set the stage for these investigations by showing that patients seek online care for mental health conditions in the setting of an eHealth portal even when such care is not explicitly available.

Acknowledgments

The authors thank James Tomaino and Michael Kistler for data extraction.

 Author Affiliations: Department of Behavioral and Community Health Sciences, University of Pittsburgh (SMA), Pittsburgh, PA; Altarum Institute (YA), Rockville, MD; Department of Critical Care Medicine, University of Pittsburgh Medical Center (GDM), Pittsburgh, PA.

Source of Funding: Physician Services Division, University of Pittsburgh Medical Center.

Author Disclosures: The authors are involved with the design, monitoring, and evaluation of the University of Pittsburgh Medical Center patient portal.

Authorship Information: Concept and design (SMA, GDM); acquisition of data (SMA, GDM); analysis and interpretation of data (SMA, YA); drafting of the manuscript (SMA); critical revision of the manuscript for important intellectual content (SMA, GDM); statistical analysis (SMA, YA); provision of patients or study materials (GDM); obtaining funding (GDM); administrative, technical, or logistic support (YA); and supervision (SA).

Address correspondence to: Steven M. Albert, PhD, Department of Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, 208 Parran Hall,130 DeSoto St, Pittsburgh, PA 15261. E-mail: smalbert@pitt.edu.
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