Abstract
Introduction:
Interprofessional consultations (“eConsults”), which facilitate asynchronous specialist consultations, remain understudied in neurological disorders. We aimed to describe the patient population receiving eConsult services for neurological disorders nationwide and to conduct a comparative analysis between rural and urban patients within this eConsult cohort.
Methods:
We analyzed a dataset of U.S. outpatient claims from employer-sponsored commercial and Medicare plans. Using standardized mean differences, we compared clinical and sociodemographic patient characteristics between urban and rural patients within the eConsult group.
Results:
We identified 1,374 patients who had an eConsult order for a neurological disorder. Overall eConsult volume increased by 548.5% between 2019 and 2021. A majority of the cohort were aged 65 years or older (23.7%), had an eConsult order in 2021 (52.4%), and live in an urban area (90.4%). The primary diagnosis for our cohort was likely to be a sleep-wake disorder (21.9%), cerebrovascular disease (14.3%), neurological sign or symptom (14.2%), or headache (13.7%). In the secondary analysis, rural eConsult patients exhibited higher rates of primary diagnoses for traumatic brain injury, neuroophthalmic disorders, or neuropathy than their urban counterparts.
Discussion:
In this national sample of commercially insured patients, the utilization of eConsults for neurological conditions increased nationwide since 2019, especially for patients living in rural areas.
Introduction
Despite the growing global demand for neurological care, 1 the world continues to face an increasing shortage of neurologists. 2 Typical wait times for ambulatory neurological care in the United States (U.S.) can reach 3 months or more in the United States, 3 with rural areas suffering from significant access challenges. 4,5 Electronic interprofessional consultations (“eConsults”) have emerged as a potential solution to the problem of limited specialty care access by allowing providers to request an asynchronous, electronic consultation from specialists without waiting for a face-to-face appointment. eConsult services are associated with reduced wait times, 6 avoidance of unnecessary specialist referrals, 7,8 and reduced health care costs. 9,10
Since 2014, the American Medical Association released six Current Procedural Terminology (CPT®) codes for interprofessional consultations (99446–99449, 99451, and 99452), allowing for providers to bill U.S. insurance carriers for these services. 11 Despite the potential of eConsults, a lack of information exists on the clinical and sociodemographic characteristics of patients that have been referred for eConsults, as well as the neurological conditions for which eConsults are requested. We therefore aimed to characterize the patient population receiving eConsults for neurological disorders across the United States. As a point of comparison, we also characterized patients who had in-person and outpatient consultations for neurological disorders. Due to care access challenges that disproportionately affect rural areas, we also compared characteristics between rural and urban eConsult patient populations.
Methods
STUDY DESIGN AND DATA SOURCES
This was a retrospective cohort study describing the patient clinical and sociodemographic characteristics of an outpatient eConsult cohort, as well as comparing between rural and urban patients within this cohort. We used patient data from commercial and Medicare employer-sponsored administrative claims in the Merative MarketScan® (Ann Arbor, MI) databases between January 1, 2019 and December 31, 2021. Due to being based on de-identified data, this research was considered exempt from review by the Mount Sinai Institutional Review Board.
STUDY COHORT
We characterized the eConsult cohort as any patients for whom CPT codes 99446–99449 and 99451 were billed at least once in the outpatient setting during the study period. We next identified all patients with a primary neurological diagnosis associated with their qualifying CPT codes. Neurological disorders were defined using the Agency for Healthcare Research and Quality Clinical Category Software (CCS) code groupings (Supplementary Table S1), which are comprised of International Classification of Diseases, Tenth Revision, and Clinical Modification (ICD-10-CM) codes. 12 Since we looked to study eConsult usage in the outpatient population, we excluded patients whose eConsult code were billed exclusively in the inpatient setting.
OUTCOMES
Our primary outcome was the provision of an eConsult, which we defined by the presence of qualifying CPT codes.
MEASUREMENTS
Using information from the patient's first claim, we collected patient's age, sex, year of service, medical comorbidities, Charlson comorbidity indices, and primary CPT-associated diagnosis codes from each patient's claims, which were categorized according to CCS category. We determined patient's urbanicity using the home address of the primary claim beneficiary, which was mapped to U.S. Census Bureau defined Metropolitan Statistical Area (MSA) codes. 13 Patients with “0000” (or “nonurban”) MSA codes were categorized as rural, whereas patients with non-0000 MSA codes were categorized as urban. Using these designations for urbanicity, we then compared rural and urban eConsult groups according to sociodemographic characteristics and diagnosis.
STATISTICAL ANALYSIS
We used frequencies and percentages to describe categorical variables and summary statistics for continuous variables. Due to asymmetries in group size, we measured differences using standardized mean differences (SMD), which are unaffected by sample size. 14,15 SMDs >10% in absolute value were considered significant. Statistical Analysis Software version 9.4 (SAS Institute, Inc., Cary, NC) was used to conduct all analyses.
Results
Over the study period, we identified 1,374 patients who had an outpatient eConsult for a neurological disorder. Most of the patients in the eConsult cohort were aged 65 years or older (23.7%), had an eConsult order in 2021 (52.4%), and lived in an urban area during the study period (90.4%). The most frequently recorded neurological diagnosis categories included sleep-wake disorders (21.9%), cerebrovascular disease (14.3%), neurological signs or symptoms (14.2%), or headache (13.7%). eConsult volume grew by 548.5% over the study period (Table 1).
Characteristics of Patients Receiving Outpatient eConsults for Neurological Disorders
Cells with fewer than 10 observations were marked as “NR” to preserve de-identification of the dataset as required by the Merative MarketScan data use agreement. Patients missing MSA data (15%) were excluded from the urbanicity analysis. Qualifying eConsult codes are CPT® codes.
CCS, Clinical Classification Software; CPT, Current Procedural Terminology; MSA, Metropolitan Statistical Area; NR, not reported; SD, standard deviation.
Within the eConsult cohort, 113 (9.6%) patients lived in rural areas at the time of their eConsult. Compared to urban patients, rural eConsult patients were more likely to be female (52.0% vs. 49.6%, SMD = 0.05), be aged 65 years or older (39.8% vs. 16.6%, SMD = 0.72), and have a higher mean Charlson comorbidity index (0.27 vs. 0.19, SMD = 0.19). The eConsult volume grew by 612.4% among rural patients compared to 518.4% for urban patients (Table 2).
Characteristics of Patients Receiving Outpatient eConsults for Neurological Disorders, Stratified by Urbanicity
Cells with fewer than 10 observations were marked as “NR” to preserve de-identification of the dataset as specified by the Merative MarketScan data use agreement. Patients missing MSA data (15%) were excluded from the urbanicity analysis. Primary diagnosis with zero observations in both groups were omitted from the table. Qualifying eConsult codes were CPT codes.
Further, rural patients in the eConsult cohort were more likely than urban patients to have a primary diagnosis of cerebrovascular disease (22.1% vs. 12.1%, SMD = 0.27), hereditary nervous system disorders (NR vs. 1.1%, SMD = 0.11), neurological signs and symptoms (16.8% vs. 12.6%, SMD = 0.12), neurocognitive disorders (NR vs. 1.4%, SMD = 0.14), neuropathies (NR vs. 3.2%, SMD = 0.14), neuro-ophthalmic disorders (NR vs. NR, SMD = 0.10), and traumatic brain injury (NR vs. 1.1%, SMD = 0.16) (Table 2). In contrast, urban patients were more likely to have a primary diagnosis of headache (15.1% vs. NR, SMD = 0.26), injury to nerves, muscles, and tendons (NR vs. NR, SMD = 0.12), nervous system cancers (NR vs. NR, SMD = 0.12), and sleep-wake disorders (25.9% vs. NR, SMD = 0.56) (Table 2).
Discussion
In this descriptive analysis of commercially insured patients, we found that the volume of outpatient eConsults for neurological disorders increased nearly fivefold over the 3-year study period. A majority of patients in the eConsult cohort were aged 65 years or older and had a primary diagnosis of sleep-wake disorders, cerebrovascular disease, neurological signs or symptoms, or headache. In comparing rural and urban eConsult patients, we found similar results, although rural patients in the eConsult cohort were significantly more likely to have a primary diagnosis of traumatic brain injury and neuro-ophthalmic conditions than urban patients. While the majority of eConsult patients in our cohort lived in urban areas at the time of their consultation, we found higher eConsult volume growth among rural patients.
The COVID-19 pandemic, which first majorly impacted the U.S. health care system in early 2020, likely explains the growth in eConsult utilization through the course of our study period. In this context, eConsults likely served as a helpful alternative to deliver care in the face of limited in-person contact by reducing the need for face-to-face office visits. This beneficial effect was likely compounded among rural patients who historically have more limited access to the health care system—especially telehealth, in the setting of the digital divide—than patients living in urban areas. Our findings suggest that commercially insured patients in rural areas (who traditionally suffer from significant challenges in accessing neurological care) 4,5 appear to be increasing utilization of eConsult services. With the significant shortage of primary care providers in rural communities, eConsults may alleviate the burden imposed on rural patients to travel far distances for specialist visits, shorten wait times, and offer practical medical solutions in real-time for patients living in resource-limited settings. 16,17
To our knowledge, this study is the first nationwide analysis to describe a population of patients receiving eConsults for neurological disorders. The principal limitation of our study is generalizability. Our sample was comprised of mostly commercially insured patients, which exclude a large segment of the insured U.S. population. Additionally, we entirely excluded the inpatient setting from our analysis. The fact that diagnosis codes may not accurately reflect the presence of a specific diagnosis may have also reduced the precision of our findings. Another limitation with our study is the lack of an in-person referral comparison group, which would require the ability to distinguish between new and follow-up visits. The inclusion of such an in-person comparison group would require a more complex analysis that was beyond the scope of this study, although future studies should pursue this research question. Finally, we reported clinical and sociodemographic characteristics without stratifying by time period, which did not allow us to distinguish the effect of the COVID-19 pandemic on patient characteristics.
Conclusions
eConsults have the potential to address shortages in the neurology workforce. Our findings suggest that in our cohort of commercially insured patients, eConsults are increasingly used for neurological disorders, although it is important to note that our results should be replicated in larger patient cohorts that are more representative of the entire U.S. population, and further studies investigating the health utilization impacts of neurology eConsults are warranted.
Footnotes
Acknowledgments
We thank the Scientific Computing Division at the Icahn School of Medicine at Mount Sinai for helping with the provision of the data used in our analyses.
Authors' Contributions
B.K.: conceptualization, methodology, resources, writing—review and editing, supervision, data interpretation, and project administration. S.H.: investigation, writing—original draft, writing—review and editing, and visualization. P.A.: conceptualization, methodology, statistical analysis, data curation, data interpretation, and writing—review and editing.
Data Availability Statement
The data that support this study's findings originate in a claims database under a data-use agreement with the vendor of the database. Data can be made available upon reasonable request but are subject to the conditions of the data use agreement.
Disclosure Statement
B.K. has served as consultant for NeuraHealth and Syapse, holds equity ownership for serving on the advisory board of Syntrillo, and has held speaking engagements with the American Medical Association and the American Academy of Neurology. The remaining authors have no relevant conflicts of interest to disclose.
Funding Information
No funding was received for this article.
Supplementary Material
Supplementary Table S1
References
Supplementary Material
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