Assessing Telemedicine Utilization by Using Medicaid Claims Data

The results of this descriptive analysis raise a number of important issues warranting further discussion and research. Most significant, the current findings show that in 2008–2009, telemedicine was predominantly used in the Medicaid population to treat mental health conditions, specifically bipolar disorder and ADD or ADHD. According to the media, professional organizations, and the scientific literature, telemedicine is used for a number of primary care, emergency, and specialty conditions, yet these findings show otherwise (13–15). Neufeld and Doarn’s (16) analysis of 2012 Medicare claims found a similar—yet less extreme—proportion, with mental health professional fees accounting for 70% of total expenditures for telemedicine.

The disproportionate use of telemedicine for behavioral health services in the Medicaid program may have a number of explanations. First, the overall prevalence of mental health conditions is considerably higher in the Medicaid population than in the general population, in large part because of the social determinants of mental health and also because prior to enactment of the Affordable Care Act, most adult Medicaid enrollees were required to meet categorical eligibility criteria based on a disability (17). Second, the level of sophistication of the technology needed to provide mental health treatment via telemedicine is minimal compared with other telemedicine applications. In many cases, a mental health encounter can be conducted with a Webcam and a secure Internet connection, whereas treatment of general medical ailments, such as otitis media or heart disease, requires specialized equipment that is more costly and less widely available. Third, reimbursement policies in some states may incentivize the use of telemedicine for mental health services. For example, telemedicine mental health services are almost universally covered by Medicaid programs, whereas many other services are explicitly excluded for delivery via telemedicine (18). Conversely, some state-level policies disincentivize the use of telemedicine for mental health. In some states, only psychiatrists and psychologists are eligible for reimbursement, whereas licensed therapists, social workers, and counselors, who are often reimbursed for providing these services in person, are not paid for services delivered via telemedicine (18).

A striking profile emerged of the patient who was most likely to receive telemedicine services: a white male, age 45 to 64, who lives in a rural area with a managed care plan and who is eligible for Medicaid in the category of aged, blind, and disabled. This profile warrants further research because of some of the limitations of this study, including the overrepresentation of claims from a small number of states and the likely impact of confounding variables. The rural-urban disparity was likely due to a characterization of telemedicine as a solution to rural provider shortages, even though Medicaid enrollees living in urban areas face similar access issues, especially those in need of mental health providers.

Underutilization in urban areas may also align with Medicare reimbursement policies—whereas Medicare restricts reimbursement for telemedicine to nonmetropolitan statistical areas and health professional shortage areas, most state Medicaid policies do not make this distinction and reimburse for services provided in both urban and rural areas (18). A recent study by Neufeld and colleagues (19) found a substantial increase in Medicare utilization of telemedicine in Illinois following the expansion of the state’s Medicaid telemedicine reimbursement policy. Thus this relationship may go both ways—Medicare policies may also drive Medicaid utilization patterns. Further research is needed to test this hypothesis.

As was observed in this study, racial and ethnic disparities have been found in the use of new lifesaving innovations (20). However, the racial and ethnic variation found here was likely confounded by the urban-rural disparity. In contrast, telemedicine utilization was high for people with disabilities compared with the overall study population, which may indicate benefits of this technology for people with mobility impairments. Further research is needed to better understand the diffusion of telemedicine across diverse racial and ethnic populations and people with disabilities.

The results of this study highlight the chasm between the robust public discourse surrounding telemedicine policies and actual utilization of the services. When Medicare reimbursement of telemedicine became effective in 1999, expectations were high. Congress expected expenditures for telemedicine to reach at least $60 million in the first year, but only 301 encounters occurred and actual expenditures reached only $20,000 (16). Since then, Medicare reimbursement policies for telemedicine have been in flux, with some loosening of the geographic, provider, and CPT code limitations. Despite nearly 15 years of reimbursement, the low utilization rates for telemedicine persist even in the Medicare population. Neufeld and Doarn’s (16) analysis found only $5 million in total Medicare telemedicine expenditures in 2012, and the authors characterized the current state of nationwide utilization as merely “a pilot study.” Furthermore, as demonstrated by the lack of telemedicine claims in Arkansas despite a Medicaid reimbursement policy, state reimbursement practices may lag behind policy adoption for a number of reasons, including the possibility that no claims for telemedicine were submitted, claims were submitted but issues with third-party payers prevented payment, or the billing codes were not open or active despite the state policy. It is also possible that the state developed unique telemedicine modifier codes that were not picked up in this analysis, which only flagged the GT modifier and the Q3014 HCPCS code. On a more promising note, Adler-Milstein and colleagues (21) found that 42% of U.S. hospitals surveyed in 2012 by the American Hospital Association reported telehealth adoption. However, self-reported adoption may not directly correlate with utilization.

The low utilization of telemedicine by Medicaid providers and high level of variability among states in use of telemedicine demonstrate that reimbursement alone is insufficient to advance clinical practice. There are many obstacles (for example, legal, financial, cultural, and professional obstacles) to implementation of telemedicine services. Payment for services is a major step, but governments cannot simply reimburse their way to clinical practice changes. Best practices, clinical guidelines, education and training, and established practice networks may help bridge the gap between policy and practice. Ultimately, expansion of telemedicine requires further research into the impact of state-specific reimbursement and licensure policies on telemedicine utilization (22,23). Examination of how financial incentives affect the development of telemedicine services is needed, particularly the use of different fee structures for aspects of telemedicine. For example, the facility fees paid to presenting sites where the patient is located are typically much lower than the professional or service fees paid to distant sites where the provider is located. Nominal facility fees fail to cover the costs incurred by presenting sites, such as appointment scheduling and providing staff to serve as “presenters” of the patient to the distant provider during the telemedicine encounter. Without appropriate payment, potential presenting sites may decline to enter the telemedicine market, resulting in a limited patient supply. In addition, further research is needed to evaluate return on investment and to distinguish between short-term policy impacts versus long-term cost savings and improved health outcomes.

This study had all of the known limitations of claims-based health services research. There was also the potential that use of telemedicine was underestimated because of the use of the GT and Q3014 modifier codes to identify telemedicine services. Some states may have established state-specific procedure codes or modifiers that were not picked up in our analysis. In addition, issues with third-party intermediaries may require providers to submit claims without the telemedicine-specific modifiers in order to receive reimbursement, which may also have resulted in underestimation. The high level of state variation potentially skewed the results by overrepresentation of states with more telemedicine claims. For example, nearly one-third of the cases analyzed were accounted for by Arizona alone, and nearly two-thirds were accounted for by the addition of North Carolina, Texas, and Tennessee. Therefore, the patient profile that emerged from the data may have been confounded by geographic and state-level characteristics associated with this imbalance of claims. Finally, there is some indication that providers may be utilizing telemedicine without reimbursement, especially for facility fees and for patients in HMOs or other capitated-payment plans (24).

Telemedicine has tremendous potential to decrease access barriers for underserved communities and is the subject of much policy and practice debate, yet actual utilization of telemedicine in Medicaid programs in this study was low. The overwhelming majority of Medicaid telemedicine claims were for behavioral health treatments, a pattern similar to one seen in the Medicare program. Public policies that support the expansion of telemedicine services are needed, and further research is needed to determine how specific policies affect utilization. However, public policies alone are insufficient to maximize the potential of telemedicine. Best practices, clinical guidelines, education and training, and established practice networks will all be needed to support the clinical implementation of telemedicine services.