The state of digital health adoption in Nevada: A narrative review of infrastructure, policy, and health equity

Abstract

All 17 of Nevada’s counties carry a federal Health Professional Shortage Area (HPSA) designation, straining the state’s capacity to deliver care remotely. This narrative review examines four dimensions of that capacity. It asks how telehealth is regulated and used, how far health information exchange and electronic health records have spread, whether broadband can support remote care, and what role artificial intelligence (AI) and remote patient monitoring (RPM) now play. Throughout, it considers how the state’s workforce shortages, geography, and demographic diversity shape both demand for digital health and the barriers to it, with attention to equity. Four databases (PubMed/MEDLINE, CINAHL, Scopus, Google Scholar) were searched alongside federal, state, and policy grey literature for English-language sources from January 2015 to March 2026, yielding 88 sources, 40 peer-reviewed. Nevada has enacted comparatively expansive telehealth legislation, including conditional payment parity made permanent under Senate Bill 119 (2023); however, the limited utilization evidence shows uptake varying by race, ethnicity, and language. The sole statewide HIE operates under an opt-in consent model that constrains data availability, and roughly 100,000 Nevadans lack wireline broadband at the federal benchmark speed, concentrated in rural areas. AI and RPM are being deployed in rural settings without published evaluation, and nearly all peer-reviewed evidence on Nevada’s digital health derives from a single study. Nevada’s policy framework has outpaced its infrastructure and equity conditions; closing that gap requires coordinated action across HIE consent reform, broadband–telehealth alignment, Medicaid RPM reimbursement, and community-level investment in digital literacy and language access.

1. Introduction

The COVID-19 pandemic prompted a rapid national expansion of digital health. Telehealth rose from a fraction of a percent of outpatient encounters to a double-digit share of ambulatory care within weeks, ¹ health information exchanges processed record data volumes, and remote monitoring tools moved abruptly into routine use. As the emergency receded, the central question became how much of this expansion would persist, and for which populations.

The answer varies by setting. Nationally, telehealth has stabilized at roughly 10% of outpatient visits, above pre-pandemic levels ² ; hospital EHR adoption has reached 96% ³ ; federal broadband investment through the $42.5 billion BEAD program is beginning to reach states ⁴ ; and the 21st Century Cures Act’s information-blocking provisions and the Trusted Exchange Framework and Common Agreement (TEFCA) are reshaping health-data-sharing rules. ⁵

Whether this national momentum reaches the states and populations with the greatest need is less clear. Most published literature on digital health adoption in the United States operates at the national level, using Centers for Medicare & Medicaid Services (CMS) claims or large surveys, or at the institutional level, reporting a single health system’s experience. State-level analyses that integrate policy, infrastructure, utilization, and equity within one jurisdiction remain uncommon,^6,7 even though many decisions that determine whether digital health reaches a given population, including Medicaid reimbursement, telehealth licensure, HIE consent frameworks, and broadband priorities, are made at the state level.

Nevada is an instructive case for examining how these state-level components fit together. The state has among the most severe provider shortages in the country, a population divided between two fast-growing metropolitan areas and extensive rural territory, and a demographic mix that includes large Hispanic/Latino, tribal, and immigrant communities.^8,9 It also has a recent record of telehealth legislation, a statewide health information exchange, federal broadband investment, and early deployments of AI and remote monitoring in rural clinics.^10,11

This narrative review synthesizes the available evidence on digital health adoption in Nevada across four domains. It examines how telehealth policy translates into use, how health data moves through the state’s exchange infrastructure, where broadband does and does not reach, and what role emerging technologies such as AI and remote monitoring are beginning to play. It gives particular attention to how Nevada’s provider shortages, population concentration, demographic diversity, and growth shape the equity implications of digital health adoption, and identifies where the published evidence runs out.

2. Methods

2.1. Review design and rationale

This study was conducted as a narrative review. A narrative approach was selected over a systematic review for two reasons specific to the evidence base. First, the relevant evidence on digital health in Nevada is distributed across heterogeneous source types — peer-reviewed studies, federal datasets, state Medicaid policy documents, legislative and regulatory text, organizational reports, and infrastructure data — that cannot be pooled under the uniform inclusion criteria and quantitative synthesis that define a systematic review or meta-analysis. ¹² Second, the objective was to integrate and interpret a broad, cross-domain body of evidence rather than to answer a single, narrowly bounded clinical question. The review was reported with reference to the Scale for the Assessment of Narrative Review Articles (SANRA), which addresses reporting quality rather than risk of bias. ¹³ Consistent with SANRA and with the narrative design, no formal risk-of-bias assessment or quantitative quality scoring of individual sources was performed; the appraisal approach applied instead is described in Section 2.6.

2.2. Data sources and search strategy

Four bibliographic databases were searched: PubMed/MEDLINE, CINAHL, Scopus, and Google Scholar. Searches combined the place term “Nevada” with digital health concept terms (telehealth, telemedicine, digital health, mobile health/mHealth, remote patient monitoring, health information exchange, electronic health records, artificial intelligence, broadband, and digital divide) and context terms (health professional shortage, rural health, and health equity or disparities), using Boolean operators, truncation, and phrase searching adapted to each database’s syntax and controlled vocabulary. Full search strings are provided in Supplemental Table S1. Searches were limited to English-language sources published between January 2015 and March 2026; the January 2015 start date corresponds to the period immediately preceding Assembly Bill 292, Nevada’s first major telehealth statute, and the end date reflects the most recent searches. Reference lists of included articles and relevant reviews were hand-searched (backward citation chaining) to identify sources not captured by database searching. Foundational methodological references were exempt from the date restriction.

2.3. Eligibility criteria

Sources were eligible if they (i) were published in English between January 2015 and March 2026; (ii) addressed at least one of the review’s four domains — telehealth policy or utilization, health information exchange or EHR adoption, broadband infrastructure, or emerging technologies (AI, RPM, mHealth); and (iii) either reported Nevada-specific information or provided national or comparative context relevant to interpreting Nevada’s situation. Eligible source types comprised peer-reviewed journal articles; federal and state government datasets and reports; legislative and regulatory primary sources; and reports from professional associations, nonprofit organizations, and where peer-reviewed or governmental evidence was unavailable, reputable news and trade media. Sources were excluded if they were unavailable in English, fell outside the search window (with the methodological exception noted above), or reported data superseded by a more recent authoritative source on the same measure.

2.4. Source selection

Records identified through database searching and citation chaining were screened for relevance against the eligibility criteria at the title and abstract level, followed by full-text assessment of potentially relevant sources. Because this is a narrative rather than a systematic review, screening was iterative and interpretive rather than protocol-driven: sources were selected to represent the strongest available evidence for each domain and to capture the range of Nevada-relevant policy, infrastructure, utilization, and equity considerations. Where peer-reviewed and grey-literature sources addressed the same point, the peer-reviewed source was prioritized. A record-level screening log of the type used to populate a PRISMA flow diagram was not maintained, consistent with the narrative design; the composition of the final included sources is reported in Section 2.5 in place of a record-count flow.

2.5. Composition of the included sources

Table 1 categorizes the 88 included sources. Forty (45.5%) are peer-reviewed journal articles; the remainder comprise federal and state datasets, legislative and regulatory primary sources, and organizational and news reports. The relative weight of non-peer-reviewed material, particularly for Nevada-specific claims, reflects the scarcity of primary research on digital health within the state, which this review treats as a finding in its own right (Sections 9 and 10).

Table 1.

Composition of the included sources by source type.

Source type	n	%
Peer-reviewed journal articles	40	45.5
Federal and institutional datasets/reports (ONC, HRSA, FCC/NTIA, CRS, AHRQ, SAMHSA, US Census, Federal Reserve)	11	12.5
State government sources (Nevada agencies; Legislative Research Division)	11	12.5
Legislative and regulatory primary sources (statutes, regulations)	4	4.5
Policy trackers, professional associations, and nonprofit/organizational reports	11	12.5
News media, trade press, commentary, and press releases	11	12.5
Total	88	100

2.6. Appraisal of grey literature

Because peer-reviewed evidence specific to Nevada is limited, grey literature was necessary but was appraised before use against four criteria: authority (the credibility and mandate of the issuing body, with government and official statistical sources weighted above organizational or commercial sources, and those above news media); currency (recency relative to a fast-moving policy and infrastructure landscape); corroboration (agreement with independent sources where available); and proximity (directness of relevance to Nevada). Government and agency sources were treated as the primary basis for infrastructure, shortage, and policy data. News, trade, and organizational communications were used chiefly to document developments — such as individual technology deployments — for which no peer-reviewed or governmental record yet exists, and were not used as the sole basis for effect-size, outcome, or comparative claims.

2.7. Evidence hierarchy and synthesis

To let the reader gauge the strength of evidence behind each claim, the synthesis applies a three-tier framework throughout. Tier 1 is direct Nevada-specific empirical evidence (peer-reviewed studies conducted in Nevada and quantitative data from Nevada agencies). Tier 2 is comparative and national evidence (peer-reviewed studies and national datasets from other states or the United States) applied to Nevada by extrapolation. Tier 3 is policy interpretation — the authors’ synthesis, inference, and recommendations. Within each thematic section, claims are attributed to the appropriate tier, and Tier 2 extrapolations are identified as such rather than presented as Nevada-specific findings. The review is organized into thematic sections covering Nevada’s healthcare context, telehealth policy and utilization, health information exchange and EHR adoption, broadband infrastructure, emerging technologies, and health equity, followed by discussion of cross-cutting themes and recommendations.

3. Nevada’s healthcare landscape: Context for digital health adoption

Digital health adoption in Nevada is shaped by the healthcare environment into which these tools are introduced. That environment is defined by a persistent shortage of providers, a population concentrated almost entirely in two metropolitan areas, continued rapid population growth, and marked socioeconomic variation across communities. Together these conditions heighten the potential value of digital health in Nevada relative to states with greater in-person capacity, while also complicating its implementation. The evidence reviewed in this section is predominantly Nevada-specific, drawn from state workforce reports, federal shortage-area designations, and census data.

3.1. Health workforce shortages

Nevada ranks among the lowest states for physician supply. Data from the Association of American Medical Colleges (AAMC) indicate approximately 218 active physicians per 100,000 residents in 2021, against a national average of 272 per 100,000, placing the state 45th of 50. ⁸ Nevada ranked 48th for primary care physicians and 49th for general surgeons per capita. ¹⁴ A workforce report from the University of Nevada, Reno School of Medicine estimated that the state would require approximately 2,631 additional active physicians to reach the national average across specialties. ¹⁵

These shortages extend to every county in the state. All 17 Nevada counties carry some form of Health Professional Shortage Area (HPSA) designation, reflecting persistently high population-to-provider ratios. ⁹ Drawing on HRSA data and state population estimates, the Nevada Health Workforce Research Center reports that approximately 64.9% of Nevadans reside in a federally designated primary care HPSA and 91.3% reside in a mental health HPSA, the latter encompassing all 14 rural and frontier counties as single-county designations. ¹⁵ Rural residents appear disproportionately affected. State reporting indicates that roughly 89% fall within a primary care HPSA, while for dental care an estimated 58% of Nevadans, and 82.5% of rural residents, lack adequate access. ¹⁶ These designations are summarized in Table 2.

Table 2.

Health Professional Shortage Area (HPSA) designations in Nevada.

HPSA type	Share of population in a designated HPSA	Notes
Primary care	∼64.9%	All 17 counties carry some form of designation
Mental health	∼91.3%	All 14 rural and frontier counties designated as single-county HPSAs
Dental	∼58% statewide (≈82.5% of rural residents)	Rural residents disproportionately affected

Sources: HRSA Data Warehouse; Nevada Health Workforce Research Center (2025); Nevada Division of Public and Behavioral Health.

These shortages have structural origins. Nevada has historically had limited graduate medical education (GME) capacity, with approximately 403 federally funded residency positions, compared with more than 9,000 in California and 17,000 in New York. ¹⁴ Federal GME funding was capped in 1997, when Nevada’s population was substantially smaller. ¹⁴ Four medical schools now operate in the state (the University of Nevada, Reno School of Medicine; the Kirk Kerkorian School of Medicine at UNLV; Touro University Nevada; and Roseman University College of Medicine), yet the pipeline from training to retention remains thin. Nevada retains only 39.8% of the physicians who complete undergraduate medical education there. ¹⁷ The physician workforce is also aging; approximately 32.2% of Nevada physicians were aged 60 or older in the most recent estimate, up from 24.5% a decade earlier. ¹⁸

State and federal policymakers have responded to these shortages. At the state level, the Nevada Health Equity and Loan Assistance (NHELA) program, launched in 2025 under legislation passed in the 2023 session, offers providers up to $120,000 in loan repayment in exchange for a five-year commitment to serve rural or underserved urban communities. ¹⁴ Federally, the proposed Physicians for Underserved Areas Act would redistribute unused GME positions to shortage areas, with Nevada identified as a priority state. ¹⁹

These interventions operate on a long horizon, as physician training takes roughly a decade. In the interim, technology-enabled approaches such as telehealth, remote monitoring, and AI-assisted diagnostics represent one of the few available means of extending the reach of the existing workforce.

3.2. Geographic and demographic considerations

Nevada’s population is highly concentrated. Of approximately 3.27 million residents, roughly 2.4 million live in Clark County (Las Vegas), about 73% of the total, and a further 500,000 live in Washoe County (Reno–Sparks), around 15.5%.^20,21 The two counties together account for roughly 88–89% of the state’s residents, leaving the remaining 15 counties to share 11–12% across a large and sparsely populated geographic area. ²⁰

The implications for digital health differ by region. In the Las Vegas metropolitan area, the constraint is less geographic distance than the number of underserved residents within a rapidly growing population. Clark County’s primary care HPSA designations extend across much of northern and eastern Las Vegas and the Strip corridor, where a large tourism-dependent workforce frequently lacks employer-sponsored coverage. ²² In the 14 rural and frontier counties, the constraints differ in kind. Populations are small and dispersed, broadband is limited or absent, travel times to specialist care can extend to several hours, and clinics operate with minimal staffing.^9,23

The state’s population is also demographically diverse. Clark County comprises approximately 28.1% Hispanic or Latino, 12.0% Black or African American, and 10.2% Asian residents, ranking among the more ethnically diverse counties in the western United States. ²⁴ Spanish is the primary language in approximately 22.8% of Clark County households. ²⁴ Nevada’s American Indian and Alaska Native population, about 1.7% of residents (roughly 56,000 people), spans multiple tribal nations, including the Paiute, Shoshone, and Washoe, with reservations and colonies in both urban and rural areas. ²⁵ The state’s Native Hawaiian and Pacific Islander population (0.8%) is approximately four times the national share (0.2%), reflecting longstanding migration ties to Hawaii and the Pacific. ²⁵

These demographic features carry practical implications for digital health, though the evidence linking them to Nevada outcomes is largely interpretive rather than directly measured. With nearly a quarter of Clark County households speaking Spanish at home, patient portals and platforms available only in English are unlikely to reach a substantial share of the population. Comfort with, and trust in, technology-mediated care also varies across communities. Nevada’s labor market adds a further consideration. The tourism and hospitality sector employs a large proportion of workers in shift-based, part-time, or gig arrangements that often lack stable insurance or a continuous primary care relationship, which is the very continuity around which most digital health tools are designed. ²⁶

These pressures are intensifying. Nevada has consistently ranked among the fastest-growing US states, and Clark County alone is projected to add more than 550,000 residents by 2043. ²⁰ Because workforce and infrastructure expansion have not kept pace with this growth, the gap between the demand for care and the supply of providers is widening. This is the context in which Nevada’s digital health ecosystem operates.

4. Telehealth policy and utilization

Telehealth is the most developed component of Nevada’s digital health framework. Nevada established a legal basis for virtual care earlier than most states, expanded it substantially during COVID-19, and subsequently made many of those expansions permanent. Policy and utilization, however, have not moved in step. Expansive legislation does not by itself ensure that patients use telehealth, or that the populations with the greatest need benefit most. The evidence in this section combines Nevada-specific statutes, regulations, and a single state-based utilization study with national data used for comparison.

4.1. Legislative and regulatory framework

Nevada’s telehealth policy begins with Assembly Bill 292 (AB 292), passed in 2015. AB 292 declared it the public policy of the state to encourage healthcare delivery through telehealth and required both Medicaid and private insurers to cover telehealth services on the same terms as in-person care, a coverage parity mandate adopted earlier than in many states.^10,27 The bill also established baseline licensure requirements: any provider delivering telehealth to a patient in Nevada had to hold a valid Nevada license, with limited exceptions for providers employed by urban Indian organizations. ¹⁰

When COVID-19 arrived in March 2020, Nevada’s emergency response built on this foundation. Under the governor’s Declaration of Emergency, the state temporarily loosened several restrictions. Non-HIPAA-compliant platforms were permitted, audio-only telephone consultations became reimbursable (previously only video was covered), out-of-state providers gained temporary practice authority, and the pre-existing patient–provider relationship requirement was waived.^28,29 These measures paralleled national action, as CMS expanded Medicare telehealth coverage and at least 10 states implemented new payment parity mandates during 2020.^2,30

After the emergency, the central question was which expansions would be retained. In Nevada, the answer came in 2023 with Senate Bill 119 (SB 119), which passed both chambers near-unanimously. SB 119 repealed the sunset date on the expanded provisions and made key elements permanent. Insurers must now reimburse telehealth at the same rate as in-person care when services are delivered to patients in rural areas, provided by federally qualified health centers (FQHCs), or involve behavioral health counseling and treatment.^28,31 The bill specifically included audio-only services for behavioral health, a provision of particular relevance given that all 14 rural and frontier counties are designated mental health HPSAs and many rural residents lack broadband sufficient for video visits.^16,31

Nevada’s payment parity provisions place it among roughly 23 states that had implemented explicit private-payer telehealth payment parity requirements by late 2025.^32,33 National evidence indicates such mandates have measurable effects. A 2025 systematic review found that payment parity laws were associated with modest but statistically significant increases in telehealth utilization, with the strongest effects in behavioral health and chronic disease management. ³⁴ A difference-in-differences analysis of national commercial claims (2019–2021) similarly found parity associated with increased telehealth and total outpatient visits without a corresponding rise in in-person visits, indicating that parity generated new virtual utilization rather than shifting existing visits between modalities. ³⁵

Beyond parity, Nevada has continued to refine its regulatory framework. Under Regulation R101-24 (2024), codified in NAC Chapter 636, the Nevada State Board of Optometry required a licensee to review a patient’s medical and ocular health records immediately before or during any synchronous or asynchronous telemedicine encounter, and prohibited issuing a prescription for ophthalmic lenses without first performing a manifest refraction, requiring virtual diagnostics to meet the same clinical standards as in-person care. ³⁶ Nevada also expanded Medicaid audio-only coverage beyond its initial behavioral health crisis-intervention scope to a broader set of behavioral health services, though it remains restricted to behavioral health providers and has not been extended to primary care. ³⁷ These milestones are summarized in Table 3.

Table 3.

Key telehealth policy milestones in Nevada, 2015–2024.

Year	Instrument	Principal provisions
2015	Assembly Bill 292	Established coverage parity for telehealth; required Nevada licensure for telehealth providers
2020	Governor’s Declaration of Emergency	Temporary: audio-only reimbursable; non-HIPAA-compliant platforms permitted; out-of-state provider authority; pre-existing relationship requirement waived
2023	Senate Bill 119	Made expansions permanent; payment parity for rural areas, FQHCs, and behavioral health; audio-only parity for behavioral health
2024	Regulation R101-24 (NAC Ch. 636)	Optometric telemedicine standards; manifest refraction required before prescribing ophthalmic lenses
2024	Medicaid Services Manual Ch. 3400	Expanded audio-only coverage for a broader set of behavioral health services

Sources: Nevada Legislature (AB 292; SB 119); Nevada State Board of Optometry; Nevada DHCFP; CCHPCA; Manatt Health.

4.2. Utilization trends

The most direct evidence on telehealth use in Nevada comes from Kim et al., a retrospective cross-sectional analysis of electronic health record data from a large Nevada healthcare provider. ³⁸ Before the pandemic, telehealth was effectively absent from routine outpatient care, accounting for 16 of 237,997 outpatient encounters in the first nine months of 2019. Over the same period in 2020, it accounted for 10.8% of outpatient visits (24,159 of 222,750; Figure 1). ³⁸ As the only peer-reviewed, Nevada-specific utilization study identified in this review, it carries substantial evidentiary weight here, although its single-provider design limits generalizability to the state as a whole.

Figure 1.

Telehealth utilization in a large Nevada healthcare system before and during the COVID-19 pandemic (Kim et al. ³⁸ ). (A) Telehealth as a share of outpatient encounters, rising from 16 of 237,997 visits (January–September 2019) to 24,159 of 222,750 visits (10.8%) over the same months in 2020. (B) Adjusted odds ratios for telehealth use by race and ethnicity (reference: White), primary language (reference: English), insurance type (reference: private), and service line (reference: adult medicine). Error bars denote 95% confidence intervals; the Asian estimate is shown as a point estimate only, as a reliable confidence interval was not available from the source. Odds ratios below 1.0 indicate lower adjusted odds of telehealth use relative to the reference group.

The study also identified which groups were reached. Relative to White patients, Asian patients (OR = 0.85) and Hispanic/Latino patients (OR = 0.89; 95% CI 0.85–0.94) had significantly lower adjusted odds of telehealth use, and Spanish-speaking patients had the lowest odds of any group examined (OR = 0.68; 95% CI 0.63–0.73), indicating a language barrier compounding the ethnic disparity. ³⁸ Disparities also tracked insurance status: Medicaid (OR = 0.91; 95% CI 0.87–0.97) and Medicare (OR = 0.94; 95% CI 0.89–0.99) beneficiaries were less likely to use telehealth than privately insured patients, as were patients in specialty (OR = 0.67) and pediatric (OR = 0.76) care relative to adult medicine. ³⁸ These patterns are shown in Figure 1.

National data provide comparative context but cannot substitute for Nevada-specific evidence. A 2024 analysis of the Health Information National Trends Survey (HINTS) found that 39.3% of U.S. adults reported telehealth use in 2022; the most common reason for non-use was that a provider did not offer it (63% of non-users), and among those offered telehealth who declined, 84.4% preferred in-person care. ³⁹ Nationally, telehealth has stabilized at approximately 10% of outpatient visits, below early-pandemic peaks but well above pre-pandemic levels. ¹ Behavioral health accounts for a disproportionate share of this utilization, a pattern likely amplified in Nevada given the severity of its mental health workforce shortages.^34,40 A systematic review comparing telehealth with in-person care during the pandemic found generally small, clinically non-meaningful differences in utilization and outcomes across most specialties, suggesting earlier quality concerns may have been overstated. ⁶

Evidence on tribal communities specifically is sparse and comes from outside Nevada. In a national cohort of more than 1.7 million veterans, American Indian and Alaska Native (AI/AN) veterans used video telehealth for mental health care less than their non-AI/AN counterparts during the early pandemic, and the rural–urban gap in uptake was roughly three times larger among AI/AN veterans than among others (difference-in-differences 4.99 vs 1.66 percentage points), a shortfall the authors attributed substantially to broadband and device access. ⁴¹ We identified no Nevada-specific study reporting telehealth utilization among the state’s tribal populations, whose reservations and colonies fall predominantly in the rural and frontier counties with the lowest broadband subscription (Figure 2). This is a priority evidence gap, since these communities combine high need with the infrastructure constraints most likely to limit telehealth’s reach.

Figure 2.

Nevada counties by household broadband subscription and Health Professional Shortage Area (HPSA) designation. The map shows the geographic overlap between the counties with the lowest broadband subscription and those carrying primary care and mental health HPSA designations.

These results reveal a divide between nominal access and realized use. Nevada’s parity legislation expanded coverage on paper, yet the state’s only utilization study shows uptake stratified by race, language, and insurance status over the same period. Payment parity addresses one barrier, reimbursement, but does not by itself resolve the broadband, digital-literacy, language-concordance, and device-access constraints that determine whether expanded coverage becomes equitable use. Without parallel progress on those fronts, policy expansion can leave existing disparities intact or widen them, a theme examined further in Sections 6 and 8.

4.3. Remaining policy gaps

Several policy gaps remain, beginning with audio-only reimbursement. SB 119 extended payment parity for audio-only services only to behavioral health, leaving primary care, chronic disease management, and other specialties without reimbursement for telephone-based consultations.^31,37 In a state where rural broadband coverage is still uneven (Section 6), restricting audio-only reimbursement to a single specialty limits telehealth’s reach in precisely the communities where it could have the greatest effect.

Interstate licensure remains a friction point. Nevada participates in the Interstate Medical Licensure Compact for physicians but has been slower to adopt other professional compacts. As of mid-2025, the state had only 478 licensed clinical professional counselors, or 14.6 per 100,000 residents, below the national average, and multiple rural counties reported no licensed counselors. ⁴² Joining the Counseling Compact, which would allow out-of-state licensed counselors to provide telehealth to Nevada residents, has been proposed as a low-cost mechanism to expand behavioral health capacity without waiting for local workforce development. ⁴²

Remote patient monitoring (RPM) reimbursement is another area where Nevada lags. While 41 state Medicaid programs offer some form of RPM reimbursement, Nevada’s Medicaid RPM coverage remains limited, with restrictions on eligible conditions, provider types, and monitoring devices. ³³ Given that chronic disease management is among the use cases where telehealth shows the clearest benefit in the peer-reviewed literature,^6,34 limited RPM reimbursement is a notable shortcoming, particularly for rural Nevadans managing diabetes, hypertension, and COPD far from the nearest specialist.

Finally, Nevada has no state-level framework for asynchronous (store-and-forward) telemedicine, in which clinical information is collected and transmitted for later specialist review. Store-and-forward has proven effective for dermatology, ophthalmology, and pathology in other states, yet Nevada’s Medicaid program does not explicitly reimburse it.^33,37 Expanding reimbursement to cover asynchronous modalities and RPM would align Nevada’s policy framework more closely with the range of care-delivery options its workforce shortages require.

5. Health information exchange and electronic health records

Health information exchange (HIE) determines whether a patient’s records are available across care settings, from an emergency department in Las Vegas to a rural clinic in Elko, or whether a primary care provider can see a specialist’s recent prescribing. It is a less visible component of digital health infrastructure than telehealth, but a foundational one. Nevada’s HIE infrastructure remains comparatively underdeveloped, and its design, particularly its consent model, shapes how much clinical data is actually available at the point of care. This section draws on Nevada-specific information about the state’s exchange alongside national peer-reviewed studies of consent models, EHR adoption, and interoperability.

5.1. HealtHIE Nevada: Structure, growth, and constraints

Nevada has one statewide health information exchange, HealtHIE Nevada, a private nonprofit that operates as the only HIE open to the entire Nevada healthcare community. ⁴³ It collects and shares records from acute care hospitals, emergency departments, urgent care sites, skilled nursing facilities, physician offices, laboratories, and imaging centers, among other providers. As of its most recent reporting, more than 70 healthcare organizations across the state are connected to the network. ¹¹

Nevada’s HIE is distinguished by its consent model. Nevada operates under an opt-in framework, in which patients must actively consent before their health data is shared through the exchange. Many other states, including the neighboring states of Arizona and Utah, use an opt-out model, in which data is shared by default unless a patient declines.^11,44 The two approaches embody a genuine trade-off rather than a simple hierarchy. Opt-out models maximize data availability, so that a provider querying the HIE can expect to find records for most patients. Opt-in models prioritize explicit patient authorization, which protects autonomy and can matter for patients with reasons to be cautious about data sharing, but they reduce the completeness of the exchange, since records are available only where consent has been obtained, often during a brief and busy clinical encounter.

National peer-reviewed evidence documents the operational consequences of these models. In a cross-sectional analysis of U.S. nonfederal acute care hospitals, Apathy and Holmgren found that hospitals in opt-in states were 7.8 percentage points more likely than those in opt-out states to report regulatory barriers to health information exchange (p = 0.03). ⁴⁵ The burden fell hardest on hospitals with less advanced health IT; among hospitals that had not attested to Meaningful Use Stage 2, the association held strongly (7.7 percentage points, p = 0.02), whereas among more technologically mature hospitals the effect was attenuated. ⁴⁵ In a broader legal analysis, Mello et al. identified variation in state consent requirements as a leading legal barrier to HIE growth nationally, noting that providers operating across state lines tend to default to the strictest standard they encounter, which further limits information flow. ⁴⁶

The COVID-19 emergency provided an unplanned test of the state’s exchange under looser rules. Under the emergency declaration, HealtHIE Nevada was temporarily permitted to share data for patients who had never been asked to consent, rather than only those who had actively opted in. According to the exchange, this produced a 36% increase in the number of patients whose data was accessible through the system, and the organization offered providers free portal access and connected 23 additional care organizations during the period. ¹¹ When the emergency provisions lapsed, the state returned to its opt-in framework and much of the expanded access contracted. The episode illustrates the data-availability cost of opt-in, but it also indicates why any shift toward opt-out would need deliberate safeguards, since the pandemic expansion effectively enrolled patients who had never actively consented.

HealtHIE Nevada has also announced a partnership with Holon Solutions, a health-data integration company, intended to improve delivery of actionable data into provider and payer workflows. ⁴⁷ The exchange has acknowledged that national interoperability networks built on the Trusted Exchange Framework and Common Agreement (TEFCA) and Qualified Health Information Networks (QHINs) do not by themselves ensure that relevant data reaches the right clinician at the right point in a workflow. ⁴⁷ The partnership’s results are not yet documented, but it reflects a recognition that data availability and data usability are distinct problems.

Consent design is therefore more than an administrative choice. States using opt-out or hybrid models generally achieve higher record availability (Table 4), but consent design also affects data quality and patient trust, not only volume. Incomplete opt-in enrollment can leave clinicians with partial records that are less reliable at the point of care, while a poorly communicated shift to opt-out risks eroding the trust of communities, including some historically underserved groups, that have legitimate reasons for caution about default data sharing. This concern is empirically grounded. In a national survey of 19,567 veterans, a preference for opt-out consent varied sharply by race and ethnicity, endorsed by 56.8% of White respondents but only 40.3% of Black, 44.9% of Hispanic/Latino, 48.3% of Asian/Pacific Islander, and 38.3% of Native American respondents (P < .001), leading the authors to call for culturally sensitive implementation of health information exchange. ⁴⁸ A framework that raises availability while preserving trust would require transparent notification, culturally appropriate and language-concordant consent processes, straightforward mechanisms for patients to review and withdraw sharing, and attention to the sensitivity of particular data types. The relevant question for Nevada is thus not simply opt-in versus opt-out, but how to increase data availability without sacrificing the patient trust on which the exchange depends.

Table 4.

Digital health infrastructure comparison: Nevada, Arizona, and Utah.

Indicator	Nevada	Arizona	Utah
HIE consent model	Opt-in (HealtHIE Nevada)	Opt-out (Contexture)	Opt-out (UHIN)
Telehealth payment parity (private payer)	Conditional: rural areas, FQHCs, and behavioral health (SB 119, 2023)	Broad parity: reimbursement on the same basis as in-person care (HB 2454, 2021)	Coverage parity only; no explicit private-payer payment parity statute
Medicaid RPM reimbursement	Not reimbursed as a standalone modality	Reimbursed	Reimbursed
BEAD broadband allocation	$416 million	$993 million	$317 million
Primary care shortage	∼65% of population in a primary care HPSA; all 17 counties carry some designation	Meets ∼39% of primary care need (ranked 42nd)	Shortages across rural counties; among the lowest PCPs per capita
Active physicians per 100,000	218 (ranked 45th)	252 (ranked 31st)	210 (ranked 47th)

Sources: Center for Connected Health Policy, State Telehealth Laws (Fall 2025); Manatt Telehealth Policy Tracker (2025); NTIA BEAD allocations; HRSA HPSA Data Warehouse; AAMC State Physician Workforce Data Report; HealthIT.gov state HIE consent policies; Contexture; UHIN.

5.2. EHR adoption and interoperability

Electronic health record (EHR) adoption in the United States has reached near-saturation at the hospital level. By 2021, 96% of nonfederal acute care hospitals had adopted a certified EHR system, up from 28% in 2011; among office-based physicians, the figure was 78%.^3,49 These national figures conceal substantial variation. Small and rural hospitals have consistently lagged urban and large-system counterparts in EHR adoption and, more importantly, in the use of advanced functions such as clinical decision support, patient portal activation, and interoperable data exchange.^50,51

Nevada’s State Medicaid Health IT Plan (SMHP) has tracked EHR adoption among Medicaid providers through the state’s EHR Incentive Program, now the Promoting Interoperability Program. Although most eligible hospitals and many eligible professionals in Nevada have received at least one incentive payment for EHR adoption or Meaningful Use, state officials have noted continued room for improvement in both adoption and optimization. ⁵² The SMHP identified a need for ongoing technical and operational support to help providers use their systems effectively, not merely install them, a distinction that matters because an installed EHR does not guarantee that providers exchange data, engage patients through portals, or use embedded decision-support tools. ⁵²

Interoperability, the ability to send, receive, find, and integrate patient information from external sources, is where the gap between adoption and usefulness is widest. Nationally, 70% of hospitals engaged in all four domains of interoperable exchange by 2023, a 54% increase from 2018. ⁵ Engagement varied widely by hospital type, from 53% of large or system-affiliated hospitals to 22% of independent hospitals. ⁵³ Nevada’s hospital mix includes several small independent and critical-access hospitals in rural areas; on this basis, the state’s rural interoperability is likely to fall toward the lower end of this range, though direct Nevada-specific measurement is not available.

Federal momentum toward interoperability through TEFCA may alter this trajectory. TEFCA became operational in late 2023 with approval of the first QHINs and aims to establish a floor for nationwide exchange through common rules and a trusted governance framework. ⁵ For Nevada, where HealtHIE Nevada is the sole HIE, TEFCA participation could broaden data exchange with out-of-state providers and systems. TEFCA does not, however, override state consent laws; Nevada’s opt-in requirement would continue to apply to data shared through TEFCA-connected networks, and would therefore continue to shape how much Nevada patient data moves through these channels.

A related federal development is the anti-information-blocking provision of the 21st Century Cures Act. Effective April 2021, the information-blocking rule prohibits providers, health IT developers, and HIEs from practices likely to interfere with the access, exchange, or use of electronic health information. ⁵⁴ Opt-in consent models are not themselves information blocking, as they are permitted under HIPAA and state law, but the Cures Act reflects a broader national movement toward freer information flow. Should Nevada revisit its consent model in this context, the evidence reviewed above suggests that a carefully designed shift, for example to opt-out accompanied by transparent patient notification, culturally appropriate consent, and straightforward opt-out and data-review mechanisms, could increase the availability and clinical utility of exchange data. Such a change would need to be evaluated against its effect on patient trust, not data volume alone, particularly among communities whose engagement with the health system is already fragile.

6. Broadband infrastructure and the digital divide

Broadband connectivity is a precondition for every other digital health capability examined in this review. Telehealth statutes, health information exchange, and remote monitoring all assume that patients can get online reliably enough to use them, and in parts of Nevada that assumption does not hold. This section distinguishes among the senses in which broadband can be “lacking”, physical availability, connection speed, subscription, and affordability, because these are frequently conflated and carry different implications for digital health readiness. Here, Nevada-specific deployment and subscription data are read against national studies linking connectivity to telehealth use.

6.1. Current broadband coverage

Estimates of how many Nevadans lack broadband depend on which metric is used. In terms of availability, the FCC’s Broadband Data Collection indicates that close to 100,000 Nevadans live at locations without access to wireline broadband meeting the federal benchmark of 100/20 Mbps (100 Mbps download, 20 Mbps upload), with the shortfall concentrated in rural and frontier areas.^4,55 Using a lower speed threshold, a 2022 report from the governor’s office estimated that approximately 220,000 residents lacked a wired connection capable of even 25 Mbps download, and that roughly 100,000 lived in areas with no wired internet infrastructure at all. ⁵⁶ These figures describe availability rather than use; they do not capture whether households that can obtain service actually subscribe, can afford it, or have connections stable enough to support sustained video consultations. As deployment funds reach the state, availability should improve, though on a timeline measured in years.

Nevada’s geography contributes substantially to these gaps. Approximately 86% of the state’s land is federally owned, and much of its rural territory is desert with long distances between population centers. ⁵⁵ Extending fiber to a ranch in Nye County or a tribal reservation in Humboldt County costs far more per household than wiring a Las Vegas suburb, and private providers have historically had limited incentive to build in these areas while public investment remained insufficient to close the gap.

This is beginning to change through public investment. Under the Broadband Equity, Access, and Deployment (BEAD) program, established by the Infrastructure Investment and Jobs Act of 2021, Nevada has been allocated approximately $416 million to expand broadband access, the largest such investment in the state’s history.^57,58 Phase III of the state’s High-Speed Nevada Initiative, administered by the Governor’s Office of Science, Innovation and Technology, targets more than 52,000 unserved and underserved locations through a combination of fiber, fixed wireless, and low-earth-orbit satellite deployment. ⁵⁹ Nevada was among the first states to complete provider selection and submit its final BEAD proposal for federal approval, and one of the largest subgrants, $142.6 million to Stimulus Technologies, will fund fiber deployment to more than 17,000 unserved and underserved rural locations.^58,60

Federal deployment funding does not, however, address affordability. More than 200,000 Nevada households enrolled in the Affordable Connectivity Program (ACP), which subsidized broadband subscriptions for low-income households, before its federal funding lapsed in 2024. ⁵⁵ Without a replacement subsidy, some of these households may be unable to maintain the subscriptions they had acquired, so that expanded infrastructure availability could coincide with declining subscription among lower-income residents. Availability and adoption are therefore distinct problems, and progress on one does not guarantee progress on the other.

6.2. Broadband as a determinant of digital health access

The association between broadband access and telehealth use is well documented in the peer-reviewed literature. In a national study, Wilcock et al. found a direct association between broadband availability and telemedicine use, with better-connected areas significantly more likely to have residents using telehealth. ⁶¹ Analyzing the 2021 National Health Interview Survey, Park et al. found that adults in rural areas were 42% less likely to use telemedicine than urban counterparts, a disparity attributed substantially to connectivity. ⁶²

A 2025 cross-national ecological study identified a threshold effect. Below approximately 40–50% rural internet penetration, telehealth investment showed minimal impact on preventive-care access regardless of clinical-side spending; above that threshold, telehealth adoption and preventive-care utilization were strongly correlated. ⁶³ On this evidence, broadband functions as a precondition for telehealth rather than a supplement to it, since below a certain level of connectivity telehealth programs build capacity that part of the target population cannot reach, although the study’s ecological, cross-national design limits its direct applicability to Nevada.

A 2024 Federal Reserve Bank of Richmond analysis made the geographic overlap explicit, reporting that areas designated as high-need health professional shortage areas had broadband subscription rates of 51%, compared with 73% for the broader population. ⁶⁴ The communities with the fewest providers thus tend to have the least reliable connectivity. This overlap is visible in Nevada (Figure 2): all 14 rural and frontier counties carry primary care or mental health HPSA designations, and these same counties show the lowest household broadband subscription in the state. For these communities, the populations most in need of telehealth are among the least equipped to use it.

Tribal lands face a connectivity disadvantage beyond general rurality. A national analysis found that household internet access is 21 percentage points lower on American Indian reservations than in neighboring non-tribal areas, with download speeds roughly 75% slower and basic-service prices 11% higher; conventional cost factors such as terrain and population density explained the price gap but only a fraction of the access and speed gaps. ⁶⁵ For Nevada’s tribal communities, concentrated in the rural counties already shown to have the lowest broadband subscription (Figure 2), this compounding disadvantage bears directly on telehealth reach.

Federal and professional bodies have moved to recognize this connection formally. The FCC’s Connect2Health Task Force has characterized broadband as a “super-determinant of health” for its influence on other social determinants, including education, employment, and healthcare access. ⁶⁶ The American Medical Informatics Association has urged since 2017 that broadband be classified as a social determinant of health, ⁶⁷ and SAMHSA has noted that broadband’s influence on health outcomes persists after controlling for income, education, and rurality. ⁶⁶

Availability is necessary but not sufficient for digital health readiness. Even where broadband exists, effective use depends on affordability, device ownership, digital literacy, language-concordant platforms, disability accessibility, and privacy, and adoption is consistently lower among older adults, non-English speakers, and people with less formal education even when service is physically available.^64,68 In Nevada, where the median age skews older in several rural counties and nearly a quarter of Clark County households use Spanish as their primary language, the gap between broadband availability and realized digital health access is unlikely to be closed by infrastructure investment alone. Deployment paired with digital-literacy programs, multilingual onboarding, and device access is required to translate connectivity into usable telehealth.

7. Emerging digital health technologies

Beyond telehealth and health information exchange, a further set of digital health technologies is reaching Nevada’s healthcare system. Artificial intelligence (AI), remote patient monitoring (RPM), and mobile health (mHealth) tools are at differing stages of adoption, and the peer-reviewed evidence on their performance in settings like Nevada’s, which are workforce-constrained, geographically dispersed, and unevenly connected, remains limited. This section distinguishes among the several technologies grouped under “AI,” maps the available Nevada-specific and national evidence to each, and then examines the validation, safety, bias, and governance questions that determine whether these tools narrow or widen existing disparities.

7.1. Artificial intelligence: Categories and evidence

The term “AI” in healthcare spans several distinct technologies with different functions and risk profiles, a distinction that matters for evaluating readiness and safety. Diagnostic support tools interpret images or signals, for example screening retinal photographs for diabetic retinopathy or flagging findings on radiographs. Clinical decision support systems synthesize patient data to guide management. Patient triage tools direct patients to appropriate levels of care. Remote monitoring analytics interpret data streams from home devices. Population health prediction models estimate risk across patient panels to target resources. Administrative automation handles scheduling, documentation, and billing. Generative AI produces new text or images in response to prompts. These categories carry different evidentiary and safety requirements, since a diagnostic tool that misses disease and a triage tool that misroutes a patient fail in different ways, and a population-health model that misallocates resources can entrench inequity even when it appears accurate overall. This review treats them separately rather than as a single technology.

National evidence on AI in rural U.S. healthcare is sparse and concentrated in a few categories. In a 2025 scoping review, Brown et al. screened nearly 2,800 records and identified only 26 studies of AI development or deployment in rural U.S. settings; 14 concerned predictive population-health models and 12 described data or research infrastructure, half cited a lack of data and analytic resources as a barrier to development and validation, and none described generative AI being trained, tested, or deployed in a rural setting. ⁶⁹ The authors cautioned that, without deliberate attention, AI-driven gains could bypass rural healthcare and widen disparities. A systematic review by Perez et al. of 40 articles on AI and telemedicine in rural communities identified recurring barriers of insufficient infrastructure, high upfront cost, and shortage of specialized workforce, while noting promise in AI-assisted diagnostics, including diabetic retinopathy, cardiac, and radiology applications, and in AI-enhanced remote monitoring of chronic conditions.^70,71

Beyond diagnostic and monitoring applications, AI methods are also entering health-behavior domains relevant to chronic-disease management. A scoping review of 25 studies of AI applications for measuring food and nutrient intake found that these tools improved the accuracy and reduced the labor of dietary assessment and enabled real-time monitoring, while identifying unresolved challenges in recognizing diverse foods, algorithmic fairness, and data privacy. ⁷² In workforce-shortage settings such as Nevada’s, technology-supported nutrition assessment of this kind could extend the reach of scarce dietetic and chronic-disease expertise, though, as with the other AI categories reviewed, no Nevada-specific deployment or evaluation has been published.

Nevada-specific evidence on AI deployment is limited and, at present, derives almost entirely from a single news source rather than peer-reviewed or independently verified reporting; the following examples should be read with that limitation in mind. ²³ A Las Vegas-based company, CareCognitics, reportedly uses a machine-learning platform for remote monitoring of patients with chronic conditions in rural areas, a form of remote monitoring analytics. ²³ Some rural Nevada hospitals have reportedly adopted AI tools for administrative tasks such as data entry and scheduling, and a mobile MRI system shared across four rural hospitals reportedly uses AI-supported image analysis to compensate for the absence of on-site radiologists, a form of diagnostic imaging support. ²³ None of these deployments has been evaluated in a peer-reviewed study, which limits any assessment of their effect on outcomes, cost, or equity. Las Vegas also hosts both the Consumer Electronics Show and the HIMSS conference, giving Nevada health systems regular proximity to emerging health technologies, though whether this proximity translates into earlier adoption rather than mere exposure is not established.

7.2. Validation, safety, bias, and governance

The categories above share a common gap in the Nevada and rural evidence base, namely a lack of validation. Half of the rural AI studies identified by Brown et al. cited insufficient data and analytic resources for development and validation, and none of the Nevada deployments described above has been independently evaluated.^23,69 Deploying unvalidated tools in the settings where validation is hardest carries particular risk, because performance established in large urban academic centers does not necessarily transfer to smaller, differently resourced rural populations. Generative AI illustrates the same point at the technology frontier. Large language models are attracting rapid clinical interest, but current models remain prone to fabricated outputs, embedded bias, and degraded performance outside the settings represented in their training data, and require rigorous, application-specific validation before deployment in care. ⁷³ For rural systems that lack the informatics capacity to conduct such validation locally, these requirements compound the adoption barriers documented above.

Bias is a specific and well-documented hazard. In a widely cited analysis, Obermeyer et al. found that a commercial risk-prediction algorithm affecting millions of patients systematically underestimated the health needs of Black patients, because it used healthcare cost as a proxy for illness and less is spent on equally sick Black patients; correcting the proxy would have more than doubled the proportion of Black patients identified for additional care, from 17.7% to 46.5%. ⁷⁴ The mechanism, a training signal that encodes existing inequities, is directly relevant to Nevada, where AI tools trained on data that under-represent rural, tribal, Hispanic/Latino, or non-English-speaking populations could reproduce or amplify the disparities documented throughout this review. A tool that performs well on average can still perform poorly for the subgroups least represented in its training data.

These risks raise questions of explainability and accountability that are not yet settled in Nevada policy. When an AI tool substitutes for a scarce specialist, such as image analysis standing in for an absent radiologist, the basis for its outputs and the locus of responsibility for error become material clinical and legal questions. Data governance is a further prerequisite, since AI performance depends on the completeness and quality of the underlying data, which links directly to the interoperability and consent-related data gaps discussed in Section 5. A fragmented data environment constrains not only clinical exchange but also the reliability of any analytics built upon it. For these reasons, the emerging-technology question for Nevada is not only whether tools are adopted, but whether they are validated, monitored for subgroup performance, explainable to clinicians, and governed by clear lines of accountability before they are relied upon in care.

7.3. Remote patient monitoring and mobile health

Remote patient monitoring has a comparatively strong evidence base. A 2024 systematic review by Tan et al. of 29 studies from 16 countries found that RPM during hospital-to-home care transitions improved medication adherence, patient safety, and quality of life across multiple conditions, though cost evidence was mixed and implementation-dependent. ⁷⁵ An earlier systematic review by Taylor et al. of 91 studies found that RPM reduced hospital admissions in 49% of studies, length of stay in 49%, and emergency department presentations in 41%, with the strongest effects in chronic obstructive pulmonary disease and cardiovascular disease. ⁷⁶

A 2025 state-of-the-field review by Paul et al. reported that RPM expanded substantially during COVID-19 and has been sustained in clinical practice, with emerging evidence of improved adherence and outcomes comparable to in-person care, while noting that programs require iterative design to serve patients with limited digital literacy. ⁷⁷ An economic-evaluation review by Jiang et al. found RPM can be cost-effective for chronic disease management, though cost-effectiveness depends on capital investment, clinical context, and organizational processes that differ substantially between, for example, a Clark County health system and a critical-access hospital in Pershing County. ⁷⁸

For Nevada, the rationale for RPM is strong in principle. A state with severe provider shortages, long distances to specialists, and a high chronic-disease burden is well suited to remote monitoring of conditions such as diabetes, hypertension, heart failure, and COPD. As noted in Section 4, however, Nevada’s Medicaid RPM reimbursement is limited, and as detailed in Section 6, the patients who could benefit most are often those least able to transmit data reliably from home. This is an instance of the recurring pattern in which need and capacity are inversely distributed.

Mobile health tools, including smartphone applications for self-management, symptom tracking, and medication adherence, show a similar pattern. The evidence base is substantial and generally positive for specific uses, particularly diabetes self-management and behavioral health. ⁷⁹ A meta-analysis of 43 randomized controlled trials involving 9,328 adults with type 2 diabetes found that mHealth-delivered diabetes self-management education and support, which typically includes dietary and lifestyle components, produced modest but significant improvements in glycemic control (HbA1c reductions of approximately 0.2–0.4 percentage points). ⁸⁰ Technology-supported nutrition and lifestyle care can also be delivered synchronously. A scoping review of 73 studies of telehealth-delivered nutrition and physical activity interventions for adults in rural areas, most conducted in the United States and delivered predominantly by videoconference, found the model feasible across chronic-disease prevention and management contexts. ⁸¹ These delivery models are directly relevant to Nevada’s rural and frontier counties, where dietetic and lifestyle-medicine services are scarce, but they presuppose the same connectivity and digital-literacy conditions documented in Section 6. Smartphone ownership and reliable cellular data are not universal, however, and Nevada’s rural and frontier communities are among those least likely to have both. ⁶⁸ The Nevada Primary Care Association has deployed mobile health units with telehealth capability to reach underserved populations, including areas without a fixed clinic, a hybrid model that bridges physical and digital delivery. ⁸²

Across AI, RPM, and mHealth, the pattern is consistent. The peer-reviewed literature supports the potential of these technologies in settings like Nevada’s, but Nevada-specific deployment evidence is largely anecdotal and unevaluated, and the infrastructure, workforce, validation, and governance conditions needed to realize that potential are only partly in place. Emerging technologies are therefore best understood not as a solution to Nevada’s access problems but as tools whose benefit depends on the same infrastructure and equity conditions that constrain the rest of the state’s digital health system.

8. Health equity implications

Sections 3 through 7 documented Nevada’s telehealth policy gains, HIE constraints, broadband shortfalls, and early adoption of emerging technologies. This section examines their distributional consequences. Digital health tools are not equity-neutral; each carries an enabling mechanism and an excluding mechanism, and its net effect depends on mediating conditions such as connectivity, language, digital literacy, insurance, and housing. Telehealth can remove the travel burden that falls hardest on rural patients, yet it excludes those without broadband or a private space for a consultation. Patient portals can widen access to records, yet they disadvantage patients with limited English proficiency or low digital literacy. Remote monitoring can support chronic-disease management, yet it is inaccessible to patients without a smartphone, stable housing, or the insurance coverage that funds it. Whether Nevada’s digital health system narrows or widens disparities therefore depends less on the tools themselves than on the conditions under which different populations encounter them. The analysis below applies this mechanism-based lens to rural and frontier communities, to racial, ethnic, and linguistic minorities, and to socioeconomically disadvantaged groups.

8.1. Rural and frontier communities

Rural and frontier Nevada illustrates how barriers compound. As described in Section 3, all 14 rural and frontier counties carry mental health HPSA designations covering their entire populations, and an estimated 89% of rural residents lack adequate primary care access. ¹⁶ As described in Section 6, these same areas have the lowest broadband subscription in the state and remain years from full fiber deployment even with BEAD investment. ⁵⁵ As described in Section 5, Nevada’s opt-in HIE consent model leaves records for patients who move between rural and urban providers frequently incomplete. ⁴⁵ The mechanism of exclusion is cumulative: a rural patient may hold a telehealth benefit on paper, lack the broadband to use it, lack a complete record to inform the visit, and lack a nearby provider if the virtual visit fails.

The distinction between access and willingness matters here. El-Toukhy et al. found that rural–urban telehealth disparities were driven by access rather than preference. Rural and low-income adults were as willing to use telehealth as urban adults but less likely to have access, and the barriers they reported most often were not knowing how to use the technology, lacking a private space for a visit, and unreliable internet. ⁸³ The mechanism is therefore addressable, but through community-level investment in digital literacy, devices, and connectivity rather than clinical telehealth capacity alone. Building telehealth infrastructure without addressing these mediating conditions expands capacity that part of the rural population cannot convert into a completed visit.

Nevada’s tribal communities face the deepest version of this pattern. More than 20 tribal reservations and colonies lie within the state, many in remote locations, ²⁵ and tribal lands carry a structural connectivity disadvantage beyond general rurality. As Section 6 documented, tribal lands trail nearby areas sharply in broadband access, speed, and price, gaps that conventional cost factors do not fully explain. ⁶⁵ Tribal lands also present permitting and sovereignty considerations that slow broadband deployment even where BEAD funds are dedicated to them. ⁴ This connectivity deficit has a measurable effect on use. As Section 4 noted, AI/AN veterans in a national cohort showed a rural–urban telehealth gap roughly three times that of their non-AI/AN peers, a shortfall the authors linked chiefly to broadband and device access. ⁴¹ Fragmented care compounds the problem, since the Indian Health Service serves many tribal members and IHS facilities in Nevada have historically had limited health IT capacity and inconsistent HIE participation, ⁵² leaving records least complete precisely where continuity is hardest to maintain. A digital health strategy that does not address tribal broadband, IHS interoperability, tribal sovereignty over data, and cultural context will leave one of the state’s most underserved populations further behind. We identified no peer-reviewed study reporting telehealth or digital health utilization among Nevada’s tribal populations, which is itself a priority evidence gap.

8.2. Racial, ethnic, and linguistic disparities

Nevada-specific evidence establishes the racial and ethnic dimension directly. In the Kim et al. analysis discussed in Section 4, Asian and Hispanic/Latino patients were significantly less likely to use telehealth than White patients, and Spanish-speaking patients were less likely still, despite the same provider offering telehealth to all patients. ³⁸ The disparity was in uptake, not availability, which points to mediating barriers rather than absent services.

National studies identify the mechanisms. Rodriguez et al. found that patients with limited English proficiency (LEP) had significantly lower telehealth utilization than English-proficient patients in California, even after adjustment for insurance, age, and chronic conditions, and attributed this to English-centric patient portals, scheduling systems built without language support, and telehealth platforms lacking integrated interpreter services. ⁸⁴ These are mechanisms of exclusion built into the tools themselves, since a portal improves record access for patients who can navigate it in English while disadvantaging those who cannot. In Nevada, where 22.8% of Clark County households speak Spanish as a primary language and Tagalog, Chinese, and other languages represent sizable minorities, the same mechanisms likely apply.

More than 100 studies have documented disparities in patient portal use by age, race, socioeconomic status, and English proficiency. ⁸⁵ A review in the New England Journal of Medicine described how communities affected by “digital redlining,” discriminatory underinvestment in internet infrastructure, tend to be those with the poorest health outcomes, producing a feedback loop in which digital health tools bypass the people who most need them. ⁸⁵ A 2021 review found that being Black, female, or low-income each independently predicted lower likelihood of completing a telehealth visit, and that these disparities persisted after the pandemic expansion of virtual care. ⁸⁶

8.3. Socioeconomic barriers

Nevada’s economy shapes its equity challenges in state-specific ways. Tourism and hospitality account for nearly 30% of employment in the Las Vegas metropolitan area, much of it part-time, seasonal, or gig work. ²⁵ These workers are disproportionately uninsured or Medicaid-enrolled, and Nevada’s uninsured rate reached 13.8% in 2021, with higher rates among Hispanic residents, males, and residents of the three urban counties. ⁸⁷

Insurance status operates directly on access. National HINTS data show telehealth utilization was lowest among the uninsured. ³⁹ The mechanism extends to remote monitoring: RPM can support management of chronic conditions, but it depends on insurance to fund devices and monitoring, a smartphone or home device to transmit data, and stable housing and connectivity to sustain it, so it is least accessible to the low-income, irregularly employed, and unstably housed patients who often carry the highest chronic-disease burden.^39,78 For the Las Vegas tourism workforce, frequently without a regular primary care provider and more likely to use urgent care or emergency departments, telehealth and RPM could be well matched to need if reimbursement and onboarding pathways existed, which at present they often do not.

Age is a further axis. Nevada’s rural counties tend to have older median ages, and older adults are less likely to use digital health tools even with broadband access. ⁶⁸ Digital-literacy programs for older adults have shown promise elsewhere, but Nevada has no coordinated statewide digital health literacy initiative. The state’s BEAD plan includes digital-equity provisions, and their effect on older, lower-income, and non-English-speaking residents will depend on implementation choices not yet finalized.

A 2025 scoping review of digital health infrastructure and equity across the United States found that race, ethnicity, education, income, and age each independently predicted lower digital health engagement, with compounding effects where disadvantages overlapped. ⁷ It found no evidence that any statewide policy had, by itself, closed these divides; what mattered was how technologies were designed, deployed, and supported at community level. ⁷ For Nevada, this means the state’s expansive telehealth legislation and incoming broadband investment are necessary but not sufficient conditions for equitable adoption. Closing the gap depends on design choices, multilingual platforms, community-based digital navigators, culturally appropriate content, and reimbursement that does not presume every patient has a smartphone, broadband, and a private space, that determine whether each tool’s enabling mechanism or its excluding mechanism prevails.

9. Discussion

This review assessed Nevada’s position on digital health adoption across telehealth policy and practice, health information exchange, broadband connectivity, and the early adoption of AI and remote monitoring. Its central finding is that Nevada’s policy framework has outpaced the infrastructure, data systems, and equity conditions required to realize it. This mismatch is not unique to Nevada, but its specific form here, shaped by the state’s geography, workforce shortages, and population concentration, offers transferable lessons. The clearest expression of the mismatch is the gap between what the law permits and what the system delivers. Nevada’s telehealth legislation is among the more expansive in the western United States. AB 292 established the framework in 2015, and SB 119 made coverage parity, conditional payment parity, and expanded telehealth access permanent in 2023. Yet the utilization data show that permission did not produce uniform access. Telehealth rose from negligible to 10.8% of outpatient visits within a year, but uptake was uneven by race, ethnicity, and language. ³⁸ Legislation created the opportunity; realized access depended on infrastructure, digital literacy, and trust that legislation alone cannot supply. States that enact telehealth-friendly laws may mistake visible policy for delivered access, because the implementation gaps are less visible than the statutes.

A second finding is that Nevada’s digital health components operate in isolation from one another. The state has a statewide HIE, a broadband deployment plan, a Medicaid telehealth program, and localized AI and RPM adoption, but these are not coordinated. HealtHIE Nevada’s opt-in model constrains the data available through the exchange; broadband investment proceeds on a timeline disconnected from telehealth reimbursement policy; and RPM and AI tools are piloted in rural settings without the Medicaid reimbursement to sustain them or the evaluations to assess them. No single component is failing in isolation, which is precisely why the underlying problem, the absence of coordination across agencies and systems, is difficult to identify from any one vantage point.

Neighboring states offer a comparison (Table 4). Arizona is frequently cited as a regional leader, in part because it invested early in aligning broadband with telehealth and adopted an opt-out HIE consent model that increased data availability. ⁸⁸ Utah has reached higher interoperability maturity through opt-out consent, strong state coordination, and health-system participation. ⁴⁶ The lesson is not that Nevada should replicate either model, and, as discussed in Section 5, a shift toward opt-out would carry consent and trust considerations that these comparisons do not by themselves resolve. Rather, the consistent pattern is that coordinating technology deployment, reimbursement policy, and data governance yields better outcomes than advancing each independently. Table 4 summarizes how Nevada compares with Arizona and Utah across consent model, payment parity, Medicaid RPM reimbursement, broadband allocation, and workforce measures.

A further finding concerns the scarcity of evidence itself. This review identified almost no peer-reviewed research on HealtHIE Nevada’s performance, on outcomes of AI deployment in Nevada’s rural hospitals, or on the effect of the state’s telehealth policy changes on health outcomes. The Kim et al. study remains one of the only Nevada-specific studies on any aspect of digital health adoption, and the national scoping review of rural AI identified just 26 studies, none involving generative AI.^38,69 Digital health policy in Nevada is therefore being made with little state-specific evidence, so that resource allocation reflects assumption more than demonstrated need, and the state’s experience does not feed back into the wider literature. This gap reflects a broader shortage of state-level analysis: published work tends to sit at the federal level, drawing on CMS claims or HINTS data, or at the single-institution level, while the state, where Medicaid reimbursement, consent law, broadband priorities, and licensure reciprocity are actually decided, is comparatively understudied. Integrated state-level analyses of the kind attempted here would benefit both researchers and policymakers.

These findings point to a small number of coordinated actions. Consent reform is the place to start. As Section 5 argued, moving from opt-in toward opt-out could improve the completeness and clinical utility of exchange data, but only if it is paired with transparent notification, culturally appropriate consent, and easy reversal, and judged against patient trust rather than data volume; the exchange’s pandemic-era gain in data availability hints at the scale of what is possible. ¹¹ A second lever is reimbursement. Medicaid does not yet pay for RPM or store-and-forward telemedicine as standalone modalities, despite clinical evidence supporting both, and closing that gap would let payment catch up with practice. Behavioral health could yield faster gains, since joining the Counseling Compact would open Nevada to out-of-state licensed counselors almost immediately, easing a workforce shortage that local training cannot resolve for years. Underlying all of these is connectivity, and broadband deployment will narrow disparities only if it is accompanied by the community-level digital-literacy support that turns access into use.

These actions would benefit from systematic measurement. A digital health readiness dashboard, a publicly accessible platform tracking conditions across Nevada’s counties, could support coordination and accountability. To be actionable, such a dashboard should include telehealth utilization disaggregated by payer and county; broadband availability and subscription as distinct measures; HIE participation; Medicaid RPM reimbursement status; provider-shortage measures such as HPSA designations and physician-to-population ratios; language-access and digital-literacy indicators; and patient-level equity indicators capturing utilization by race, ethnicity, language, age, and insurance status. Many of the underlying sources, including FCC broadband maps, HRSA HPSA data, ONC health IT dashboards, and state Medicaid claims, are already public and could be integrated. Whether implemented as a state-sponsored tool or an independent research product, ongoing county-level measurement of digital health readiness would let the state monitor progress, identify where conditions are deteriorating, and direct resources by evidence rather than assumption.

10. Limitations

This review has several limitations. As a narrative rather than systematic review, source selection followed the structured but non-protocol-driven process described in Section 2, and no formal risk-of-bias or quality scoring was performed. The search aimed to be thorough across databases and grey literature, but selection bias in the sources identified cannot be excluded.

The central limitation is evidentiary. The synthesis draws on three kinds of evidence of unequal strength: direct Nevada-specific findings, national evidence extrapolated to Nevada, and the authors’ interpretation. Direct Nevada-specific peer-reviewed evidence is scarce. For several domains, including HIE performance, AI deployment outcomes, mobile health utilization, and the health effects of post-pandemic telehealth policy, the available Nevada evidence was confined to state reports, organizational communications, and media coverage. Peer-reviewed sources were prioritized where they existed, but a substantial share of the Nevada-specific claims rests on thinner evidence than the national and comparative ones. That scarcity is itself a finding, and it means conclusions about Nevada should be read as provisional pending primary research.

Several narrower caveats sharpen this point. Some of the disaggregated evidence used to interpret Nevada, including the findings on racial differences in HIE consent preferences and on American Indian and Alaska Native telehealth use, comes from veteran populations, which differ from the general population in age, sex, and health-system access and are therefore indicative rather than directly generalizable. Some Nevada deployment claims, particularly those concerning AI in rural hospitals, rest on a single news source, and the reported pandemic-era rise in HIE data availability comes from the exchange’s own communications rather than independent evaluation. No peer-reviewed study reports telehealth or digital health utilization among Nevada’s tribal populations, leaving the tribal analysis dependent on national evidence and inference, and marking a priority gap for Nevada-specific research.

This review also synthesizes secondary sources alone. It did not survey Nevada providers, patients, or administrators, nor analyze Nevada claims or EHR data directly, and primary research using such data would add depth this approach cannot. Because policy, broadband deployment, and technology pilots are changing quickly, some developments after the March 2026 search date may not be captured.

11. Conclusion

Nevada has built a legislative foundation for digital health that many states lack, with permanent telehealth payment parity, unprecedented broadband funding, an expanding statewide HIE, and early AI and remote-monitoring pilots in its most underserved communities. Infrastructure has not kept pace. Connectivity, complete data, and the conditions for equitable use lag behind the statutes, and the residents whose needs motivated the policy changes, rural, non-English-speaking, tribal, and uninsured, remain least able to use the tools now available, because telehealth uptake, broadband access, and complete health records are all distributed inversely to need.

Nevada’s remaining challenge is coordination, across broadband deployment, reimbursement, data governance, and workforce development, that no single agency currently owns. Progress also depends on community-level investment in digital literacy and language access, and on public measurement of digital health readiness so that it can be tracked rather than assumed. Nevada’s experience carries a wider lesson for state digital health policy. Enacting enabling legislation is necessary but not sufficient, and the harder work of implementation, equity, and evaluation determines whether digital health narrows or widens existing disparities.

ORCID iD

Ubalaeze Solomon Elechi https://orcid.org/0009-0002-3474-1002

Ethical considerations

This study is a narrative review of published literature and publicly available data. No human subjects were recruited, no patient data were collected, and no clinical interventions were performed. Ethical approval was not required.

Data Availability Statement

No new data were generated or analyzed in this study. All data referenced in this review are available from the cited published sources, federal databases, and state government reports described in the Methods section.*