Virtual Sideline: Telehealth Integration to Reduce Diagnostic Misses in Rural mTBI

1. Introduction

Mild traumatic brain injury (mTBI) remains one of the most frequently encountered yet consistently misdiagnosed conditions in emergency and prehospital care. Despite decades of awareness campaigns and evolving diagnostic frameworks, mTBI continues to be underrecognized due to a confluence of factors: transient symptomatology, narrow observation windows, variability in diagnostic criteria, and the influence of cognitive biases [1,2,3,4]. In both civilian and military populations, retrospective analyses suggest that more than half of all mTBI cases are either missed or misattributed during the initial episode of care [1,4,5].

This diagnostic ambiguity has contributed to the proliferation of mTBI guidelines across professional and governmental bodies. Organizations such as the Centers for Disease Control and Prevention (CDC), Department of Veterans Affairs/Department of Defense (VA/DoD), World Health Organization (WHO), American College of Emergency Physicians (ACEP), and American Congress of Rehabilitation Medicine (ACRM) have each issued their own criteria and care algorithms. While well-intentioned, this multiplicity has generated operational inconsistencies, complicating uniform application in field and transport settings.

mTBI accounts for the majority of neurotrauma incidents in high-income countries, yet its diagnosis often hinges on fleeting signs—loss of consciousness (LOC), post-traumatic amnesia (PTA), or brief episodes of confusion. These markers may resolve before EMS personnel arrive or dissipate en route to care, particularly in rural environments. National registry analyses reveal a significant rural penalty in EMS intervals, with scene times averaging 6–8 minutes longer than in urban settings, and transport delays further compounding the disadvantage (English, 2025).

By contrast, sideline sports medicine offers a compelling model in which trained clinicians assess suspected mTBI at the point of impact, enabling real-time decisions regarding triage, observation, or referral. This study introduces the concept of a "Virtual Sideline": a telehealth-enhanced EMS framework designed to replicate this immediacy in rural settings by embedding remote clinical expertise into field operations. Tele-EMS has demonstrated effectiveness in acute stroke and cardiac care, and emerging evidence supports its capacity to reduce scene times by up to 89% while improving triage fidelity [2,3].

To explore this model, we employed simulation-based methods to examine whether telehealth-enabled EMS can meaningfully reduce the likelihood of delayed CT imaging in rural mTBI presentations. This analysis represents Stage 1 of a two-part initiative, with confirmatory analysis using national EMS data from NEMSIS planned for Stage 2. Mild traumatic brain injury (mTBI) remains one of the most frequently encountered yet consistently misdiagnosed conditions in emergency and prehospital care. Despite decades of awareness campaigns and evolving diagnostic criteria, mTBI is still underrecognized due to a combination of transient symptoms, limited observation windows, diagnostic inconsistency, and cognitive bias.1–4 In both civilian and military populations, retrospective analyses have demonstrated that more than half of all mTBI cases are either missed or misattributed during the initial episode of care [1,4,5].

2. Objectives

• Describe the current limitations in mTBI diagnosis related to EMS timing, clinical variability, and rural care disparities.
• Present a conceptual model for integrating telehealth into EMS workflows to support timely recognition of mTBI.
• Explore the theoretical benefits and potential barriers to implementing a Virtual Sideline approach in real-world settings.

Methods 1. This conceptual analysis draws from a comprehensive literature review covering mTBI diagnostic failures, EMS response limitations, and telehealth models in acute care [1,2,6,7,8]. Primary sources included peer-reviewed journals accessed via databases such as PubMed, CINAHL, and Scopus. Additional data was extracted from the National Emergency Medical Services Information System (NEMSIS) database to establish realistic EMS response intervals and symptom observation windows relevant to mTBI cases. Literature was systematically reviewed, focusing on articles published between 2000 and 2024, with inclusion criteria emphasizing systematic reviews, meta-analyses, observational studies, and consensus guideline papers. Articles were screened by title and abstract for relevance to prehospital mTBI care, diagnostic accuracy, telehealth interventions, and rural healthcare disparities. Using a translational framework, we developed a model to simulate how integrating telehealth into EMS might improve diagnostic capture.

Methods 2. Simulation Design: Two hundred synthetic cases were created, distributed evenly between urban and rural EMS response scenarios. Variables included symptom decay functions for LOC, AC, and PTA. Virtual assessment was introduced at three intervals (10, 20, 30 minutes post-injury). The proportion of accurate mTBI identifications with and without telehealth was calculated based on literature-derived probabilities [6,7,8,10].

3. Results

Simulation data revealed pronounced improvements in diagnostic accuracy when telehealth was introduced in rural EMS scenarios. Without telehealth, the baseline mTBI recognition rate in rural settings was 38%. When teleconsultation occurred at 10 minutes post-injury, diagnostic accuracy increased markedly to 70%. Delayed telehealth contact at 20 and 30 minutes post-injury resulted in lower recognition rates of 55% and 45%, respectively, underscoring the importance of early intervention.

In urban contexts, where EMS response times are typically faster, baseline recognition rates were higher at 65%. Telehealth integration led to a more modest increase in diagnostic accuracy, rising to 75%. These findings highlight both the time-sensitive nature of mTBI symptoms and the disproportionately greater benefit of telehealth in rural environments with delayed access to care.

The logistic model was statistically significant (p < .001). Key results include:

• Telehealth reduced CT delay odds in rural patients (OR = 0.19, p < .001).
• Urban and suburban patients had lower baseline odds of delay (Urban OR = 0.14; Suburban OR = 0.23).
• GCS was not predictive (p = .70), supporting concerns about its sensitivity in early mTBI.
• Interaction effect: Telehealth benefit was greatest in rural areas, where predicted delay dropped from ~60% to ~20%.

These modeled findings are consistent with real-world tele-EMS trials reporting scene time reductions of 16–44 minutes and avoidance of up to 32% of low-acuity transports.

4. Discussion

These findings demonstrate the time-sensitive value of telehealth in reducing missed diagnoses of mTBI in rural settings. Real-time assessment before symptom resolution can recapture transient signs, improving triage accuracy and clinical validation [1,4,6,7]. Telehealth parallels the gains observed in telestroke and prehospital cardiac interventions and may serve a similar equity function in neurotrauma [11,12,15,22].

Moreover, this study highlights the utility of simulation modeling as a strategic tool in prehospital systems research. In the absence of immediate access to live patient data, virtual modeling enables controlled testing of hypothetical interventions under realistic conditions. This approach allows researchers to anticipate outcome trajectories, estimate thresholds for clinical benefit, and generate empirically grounded hypotheses for future validation. In this case, modeling provided a mechanism to quantify the impact of telehealth timing and urbanicity on diagnostic performance, yielding actionable insights before full-scale implementation.

The Virtual Sideline model offers a telehealth-enhanced EMS workflow that directly addresses the diagnostic latency of mTBI in rural settings. The simulated 60% delay rate among rural patients with normal GCS mirrors findings from national EMS registries and emphasizes how GCS-based triage alone underestimates risk in mTBI [5,6].

While Glasgow Coma Scale remains standard in EMS triage, its limited granularity misses subtle indicators of evolving intracranial pathology, such as:

• Lucid intervals in epidural hematoma,
• Contusions and diffuse axonal injury,
• Non-specific neurologic complaints (e.g., dizziness, disorientation).

These gaps are compounded in rural areas by limited neuroimaging access and longer transport times.4 Tele-EMS interventions offer a meaningful solution—embedding expert clinical oversight into the EMS workflow before arrival at definitive care. Real-world tele-EMS implementations have shown up to 89% scene time reductions and saved EMS systems millions in preventable transports.2 The economic burden of delayed diagnosis—estimated at over $13,000 per patient annually—further justifies systemic adoption.7 Moreover, retrospective interviews like the BAT-L demonstrate 72–89% sensitivity for reconstructing mTBI symptoms post hoc.8 This suggests a dual-pathway model: telehealth reduces initial miss; structured interviews recover missed diagnoses when latency is unavoidable.

5. Conclusions and Policy Implications

This simulation study supports a Virtual Sideline paradigm for mTBI care, in which telehealth-enabled EMS reduces rural diagnostic disparities and accelerates access to neuroimaging. By embedding remote clinical oversight in field operations, this model allows EMS to capture transient neurological signs before they resolve—particularly in time-limited rural settings.

Beyond clinical utility, this work illustrates the value of simulation modeling as a pragmatic bridge between conceptual innovation and empirical validation. In advance of full-scale deployment or national data analysis, virtual modeling can forecast system-level benefits and refine hypotheses, guiding policy and investment.

Policymakers and EMS leadership should pursue reimbursement strategies, grant-supported pilot programs, and technology procurement pathways that facilitate prehospital tele-neurology integration. Standardized training, interagency protocols, and broadband infrastructure are essential to ensure operational feasibility and equitable access. These recommendations align with broader national goals to reduce outcome disparities and modernize prehospital neurotrauma care systems.

Table 1. Diagnostic Yield Across EMS Scenarios With and Without Telehealth.

EMS Arrival Time (min)	Scenario	Estimated mTBI Recognition Rate	Relative Gain With Telehealth
<15	Urban – No Telehealth	65%	—
<15	Urban – Telehealth at 10 min	75%	+10%
25	Rural – No Telehealth	38%	—
25	Rural – Telehealth at 10 min	70%	+32%
25	Rural – Telehealth at 20 min	55%	+17%
25	Rural – Telehealth at 30 min	45%	+7%

Table 1. Diagnostic Yield Across EMS Scenarios With and Without Telehealth.

EMS Arrival Time (min)	Scenario	Estimated mTBI Recognition Rate	Relative Gain With Telehealth
<15	Urban – No Telehealth	65%	—
<15	Urban – Telehealth at 10 min	75%	+10%
25	Rural – No Telehealth	38%	—
25	Rural – Telehealth at 10 min	70%	+32%
25	Rural – Telehealth at 20 min	55%	+17%
25	Rural – Telehealth at 30 min	45%	+7%