ABSTRACT:
Background: The COVID-19 public health emergency increased demand for healthcare services, prompting emergency policy changes that expanded access via telehealth.
Objective: To identify determinants of state telehealth policies related to in-state licensure waivers and payment parity.
Methods: A retrospective, longitudinal analysis of monthly state telehealth policy changes between January 2020 and December 2022 was conducted. Multivariate logistic regression was used to estimate the relative importance of public health, state health policy and socio-economic factors for waiving in-state licensure requirements or implementing payment parity.
Results: Waiver implementation and maintenance were more likely in ACA expansion states, states with higher COVID-19 elderly mortality rates, and increased new health center market entry but less likely in states with Democratic governors, Interstate Licensure Compact participation and Certificate of Need laws. Payment parity was more likely in states with Democratic governors, higher elderly vaccination rates, and CON laws, but was less likely in IMLC states.
Conclusions: The adoption and maintenance of telehealth policy changes was influenced primarily by public health shocks and health policy factors, as well as the political orientation of state governors. Comparatively, socioeconomic conditions were less influential.
Keywords:
Introduction
The COVID-19 public health emergency (PHE) prompted an unprecedented transformation in healthcare delivery which highlighted the potential of telehealth in expanding access to care. As social distancing measures contributing to deferral of care were introduced in March 2020, the Centers for Medicare & Medicaid Services (CMS) and state medical boards waived regulatory restrictions to accommodate the transition of in-person visits to an online setting.1,2,3,4 These waivers ranged from relaxation of in-state licensure requirements for out-of-state physicians to changes in reimbursement for telehealth delivery of services (payment parity). At the same time, the relaxation of potential HIPAA penalties for good faith use of telehealth facilitated patient access to telehealth services via different modalities (live video, mobile health, remote patient monitoring, store-and-forward), unrestricted from originating site requirements or established-patient requirements to initiate care. The adoption of emergency waivers varied significantly in duration, cost of physician certification across states, or even more nuanced ways. This study examines the determinants of state-specific licensure restrictions relaxations (hereafter, waivers) and the introduction of equal reimbursement for in-person and virtual care (hereafter, payment parity).
During the PHE, despite the urgent need for regulatory changes, including telehealth waivers and payment parity, there was still some resistance. There were concerns that the rapid transition to remote modalities may create a digital divide, potentially exacerbating differences in access to care.5 Skeptics voiced concerns about the potential long-term consequences of government-imposed mandates. These stakeholders emphasized the importance of market-driven flexibility, arguing that policies such as telehealth parity laws could lead to inefficiencies, increased healthcare costs, and overutilization of care.6 It has been contended that healthcare systems should have the freedom to negotiate reimbursement terms based on market dynamics, rather than adhering to uniform regulatory requirements.7 This resistance highlighted the barriers policymakers had to navigate, underscoring the tension between ensuring rapid access to care through regulatory measures and maintaining market efficiency.8
Amidst these policy debates and changes, questions emerge: Which objective of this paper is to identify policy-relevant state-level factors are associated with state policymakers’ decisions to waive, temporarily or permanently, regulatory barriers that restrict access to care via telehealth or adopt payment parity laws during the PHE? These are important questions with profound implications for the supply of available physicians and welfare implications for state residents and state-licensed physicians. Given disparities in telehealth availability and access, decisions made by state policymakers regarding regulatory waivers for telehealth services and payment parity laws can have far-reaching implications on access to care and patient welfare.9,10,11,12,13,14,15,16 These flexibilities are crucial for improving healthcare access among underserved populations, including elderly patients, minority populations, those requiring interpreter services, Medicaid recipients, and residents living near state borders.17,18,19,20 However, concerns have been voiced about the unintended consequences these telehealth flexibilities may have on wasteful spending by creating opportunities for increased reimbursement through inappropriate billing and, ultimately, fraud.21,22
The rollback of these flexibilities with the re-introduction of licensure barriers to entry of out-of-state physicians has prompted patients to incur substantial search costs in pursuit of in-person access to care at remote in-state facilities.23 Reduced healthcare supply may endanger patients’ access to care during a particularly strenuous period for health systems with rising medical expenditures.24,25 Patients, in quest of in-person care, often find themselves traversing longer distances, ensnared by reinstated in-state licensure requirements.26 The adverse effects of licensure waiver expirations on access to care may be even more pronounced by the shift in patient preferences towards online modalities.
The objective of this paper is to identify policy-relevant, state-level determinants associated with telehealth licensure and payment parity policies during the PHE, while distinguishing factors such as public health outlook, healthcare supply and demand, state policy, and socio-economic characteristics. Our findings reveal the extent to which telehealth policy is primarily shaped by regulatory inertia, public health imperatives, or other factors. An improved understanding of these determinants can enhance decision-making processes, enabling policymakers to recognize when public health conditions are appropriate for extending telehealth flexibilities and payment parity in a post-PHE policy landscape. Furthermore, empirical researchers can leverage these first stage estimates to assess the causal effect of these policies on clinical outcomes in future research.
Materials and Methods
Study Design
We conducted a longitudinal analysis from January 2020 through December 2022 of state-level predictors of waiver introduction and rescindment (waiver maintenance hereafter) and the establishment of payment parity for telehealth services in all 50 states and DC in monthly frequency. The aim was to assess the direction and magnitude of the relationship between our outcomes and 13 explanatory variables, which were systematically classified into three overarching categories: public health outlook, state policy, and socioeconomic factors. The selection of these determinants was informed by prior literature and intends to capture the different aspects of the policy landscape. Studies of lockdown severity highlight the importance of political factors such as the political affiliation of a state's governor behind policy decisions and pre-PHE state-level economic freedom.27,28 State policy during the PHE may also be following voter preferences and risk attitudes towards COVID-19 as revealed by internet searches regarding stay-at-home orders in hotspots during the first stage.29 Further, expanded broadband access by a greater proportion of the state population is associated with enhanced telehealth access policies.10 As for payment parity, there is mixed evidence regarding the likelihood that healthcare facilities will utilize telehealth across payment parity adoption and non-adoption states.30,31,32 State-level participation in the Interstate Medical Licensing Compact (IMLC) is another predictor of facility-level telehealth adoption.9 However, there is no overarching evidence to this date regarding the relative importance of state-level public health conditions, state policy and socio-economic factors as determinants of telehealth policy variation during the PHE.
Statistical Analysis
To estimate the relationships of interest we employed multivariate logistic regression models. This approach allows us to assess the association of multiple variables with a policy decision simultaneously. In examining the correlation of independent variables with Waivers and Payment Parity, we used two distinct multivariate regression models, each incorporating the same set of 13 independent variables. One regression analyzed Waivers, while the other focused on Payment Parity. We designated Odds Ratios (OR) for the presentation of our estimates which assign values greater than 1 to indicate positive correlations, less than 1 for negative relationships, and equal to 1 signifying no significant effect of the independent variable on policy implementation. We clustered standard errors at the state level as the policies we considered vary by state (Supplementary Appendix-Model Specification).
Moreover, to illustrate the temporal and geographical adoption patterns of Waivers and Payment Parity, we constructed plots representing the evolution of these policies by month and state (Figures 1 and 2). The statistical analyses were all conducted utilizing Stata 17.1 software (StataCorp LP, College Station, TX).
In-state Licensure Requirement Waivers*
Evolution of Telehealth Payment Parity Adoption*
Policy Outcomes
Our two primary outcomes represent the maintenance and adoption of two pivotal telehealth policies respectively: (1) Waivers of in-state licensure requirements, which allow healthcare providers licensed in a different state to offer healthcare services in another state without obtaining in-state licensure, and (2) Telehealth Payment Parity, which mandates that reimbursement rates for telehealth services be equivalent to those for in-person services. We encoded the waivers and payment parity outcomes as dependent binary variables based on information from the Federation of State Medical Boards (FSMB) and the Center for Connected Health Policy (CCHP), respectively. The outcomes take the value of 0 in a month when a state has not yet introduced or has revoked waivers or payment parity and 1 otherwise in a month when a state actively implemented waivers or full payment parity. As a result, states with payment parity laws but less than 100% reimbursement rates for telehealth services compared to in-person such as Louisiana were coded as 0.
Policy Determinants
Our analysis encompasses 13 policy determinants, as detailed in the Tables section (A Tables). To facilitate this analysis, all variables, originally recorded at daily or weekly intervals, were aggregated to monthly frequencies by state, resulting in a total of 1,836 observations. The variables were broadly classified into three categories. This section will provide an overview of selected variables from each category, noting that a detailed description of every variable is not required due to the straightforward nature of most policy determinants under examination.
Public Health Outlook Determinants include variables as New Health Centers which represent the number of new health centers created in each month and state over the study period. Therefore, the variable does not measure aggregate health center supply but health center creation per month and state. A 0-100 index for telehealth popularity based on the number of internet searches for “telehealth” and associated terms is employed as a proxy for demand and titled Google Trends Popularity.33 The vaccination determinant aims to quantify the percentage of seniors (aged 65 and over) in a given state and month who have received a primary vaccination series, defined as completing two doses of a two-dose vaccine or one dose of a single-dose vaccine.
We employed state policy indicators of active health policy margins such as whether the state has expanded Medicaid under the Affordable Care Act (ACA), participation in the Interstate Medical License Compact (IMLC) based on the state's date of implementation, Certificate of Need (CON) laws and political climate such as whether the Governor is a Democrat and whether the Governor politically aligns with the serving President.
Lastly, we incorporate Socioeconomic Conditions variables that may influence access to care such as the Number of Unemployed individuals and Total Medicaid and Child Health Insurance Program enrollees (CHIP). Using month and state specific Civil population, we express these continuous variables as rates per 100,000 individuals to account for population size effects.
Data Sources
We combined state-level telehealth policy variation information from the FSMB and the CCHP with time-varying, state-specific factors reflecting public health outlook, state policy and socio-economic conditions from the Center for Medicare and Medicaid Services (CMS), the Area Health Resource Files, the Bureau of Labor Statistics, the Center for Poverty Research at the University of Kentucky, the Kaiser Family Foundation, the IMLC, the National Conference of State Legislatures and Google Trends in monthly frequency from January 2020 through December 2022.
Results
Waivers of in-state licensure requirements were introduced in all 50 states and DC, whereas payment parity was adopted by 34 states. Waivers were active for a period spanning as little as 2 months to 33 months, and payment parity was effective across states for 10 to 36 months or the full sample period. The average number of deaths in the general and nursing home population are 576 and 88 respectively. As for healthcare policy, 59% of states participated in the IMLC, 71% had CON laws in place, and 74% had expanded Medicaid eligibility rules under the ACA. Most state governors were Republican (54%), and, in nearly half (48%) of the states, governors were aligned politcally with the serving President (Table 1). These variables reflect state-specific observations, where maximum values often correspond to more populous states, such as California, while mean values represent the national average, offering a broader view of the policy landscape.
Summary Statistics
States that had expanded Medicaid were associated with a higher likelihood of maintaining telehealth waivers (OR 1.929, 95% CI [1.587, 2.344]), implying that such prior policy decisions might have facilitated rapid responses during health crises. Furthermore, the mortality rate from COVID-19, especially deaths occurring in nursing homes, was a more significant predictor of telehealth waivers (OR 1.286, 95% CI [1.105, 1.495]), indicating that state policy may have been influenced by the rising death toll among elderly individuals. There is a marked 71% percent increase in the probability of states enacting payment parity policies in states with increased vaccination rates among the elderly. The creation of new health centers notably influenced the maintenance of waivers (OR 1.101, 95% CI [1.062, 1.141]), reflecting a link between infrastructural health expansions and telehealth policy flexibility (Table 2).
Marginal Odds Ratios for Waivers and Payment Parity
States with Democratic governors had lower odds of adopting and maintaining active waivers (OR 0.600, 95% CI [0.487, 0.740]), and gubernatorial political affiliation was associated positively with the adoption of payment parity (OR 1.374, 95% CI [1.124, 1.680]). These associations likely reflect broader policy regimes—such as IMLC participation and Medicaid expansion—rather than party affiliation itself acting as a policy driver.
Higher vaccination rates among the elderly were another positive predictor for the adoption of payment parity (OR 1.710, 95% CI [1.309, 2.234]), possibly echoing Medicare's comprehensive coverage and prioritization of the older demographic.
Conversely, the presence of IIMLC was associated with lower odds of adopting and maintaining active waivers or payment parity (OR 0.872, 95% CI [0.722, 1.053]) for waivers and (OR 0.544, 95% CI [0.444, 0.666]) for payment parity. This could be indicative of such compacts providing a regulatory framework that lessens the urgency or perceived benefit of adopting additional telehealth regulations.
For the influence of CON laws, the data showed that these laws were associated with a 14.2% decrease in the odds of a state maintaining waivers (OR 0.858, 95% CI [0.709, 1.038]). In terms of payment parity, CON laws significantly increased the likelihood of adoption (OR 1.245, 95% CI [1.010, 1.535]), indicating a meaningful impact on policy enactment equating to approximately a 24.5% increase in the likelihood of enacting payment parity measures (Figure 3).
Odds Ratio
Discussion
We explored the relative importance of public health, policy and socio-economic factors influencing the adoption of waivers and payment parity policies in telehealth during the PHE from January 2020 to December 2022. Our study unveiled that health shocks, notably within the elderly population, significantly correlated with a higher likelihood of states maintaining waivers. Conversely, policy factors had a more substantial influence on the adoption of payment parity policies. Notably, states with pre-existing telehealth flexibilities, such as Medicaid expansion under the ACA, exhibited a stronger propensity towards adopting both licensure waivers and telehealth payment parity policies.
Our results support the idea that healthcare access was expanded in the face of negative health shocks to older adults as suggested by the large estimated magnitudes of the association of COVID-19 mortality rates in nursing homes and vaccination rates among older adults with licensure waiver maintenance. These findings indicate that heightened mortality rates, particularly in nursing homes, may have contributed to broader systemic pressures, given the elevated need for hospital services by the elderly upon contracting COVID-19. Thus, facilitating telehealth consultations, especially via out-of-state physicians, was associated with efforts to mitigate system strain. This view is in line with survey evidence of perceptions of local and national stakeholders about the complementary role of (The above figure displays the Odds ratios and 95% confidence intervals for each Dependent variable. The following variable was omitted from this graphic for interpretability: ACA Medicaid Expansion Status; Waivers OR=1.929, 95% CI: 1.587, 2.344, Payment Parity OR=4.297; 3.287, 5.618) telehealth to licensure waivers in expanding access to care.34 The observed positive association of waivers with the establishment of new health rights also indicates that waivers were more likely in states with expanding health system supply which itself may be due to the presence of substantial unmet demand for healthcare services or an underlying healthcare supply strain.
Regarding payment parity adoption, its strong, positive association with vaccination rates of the elderly supports a potential connection with a public health effort to sustain health system stability as COVID-19 vaccination coverage in the state population expanded. Political congruence between state and federal executive branches could facilitate the adoption of relatively costlier reimbursement practices as payment parity because it may allow for smoother policy implementation and offer an opportunity to harmonize pre-existing state Medicaid reimbursement policies with federal initiatives.
As for state policy determinants, the expansion of Medicaid is associated with both Waiver and Payment Parity maintenance, likely due to its dual aim of extending healthcare access, thereby naturally aligning with the expansion of telehealth services as a cost-effective modality. In contrast, political variables such as having a Democratic governor reveal lower odds of enacting and maintaining active licensure waivers and higher odds for payment parity. During the early stages of the COVID-19 pandemic, most policy decisions were made by state governors through executive orders, and the implementation of telehealth waivers followed a similar pattern. Across the US, with few exceptions, these waivers were enacted relatively early in the pandemic, with every state adopting them by July 2020. However, as the pandemic evolved, the political context became increasingly polarized, with political affiliation playing a role, among numerous factors, in influencing policy decisions, particularly regarding lockdowns and vaccine mandates. The existing literature suggests that Democratic states were more likely to implement stricter COVID-19 policies, including mask mandates and lockdowns, compared to Republican states, which generally adopted fewer mitigation measures and experienced higher infection rates.35 However, our findings challenge this expectation in the context of telehealth waivers as states with Democrat governors were more likely to repeal waivers than Republican states, which may be explained by their higher adherence to existing interstate compacts, such as the IMLC. These compacts effectively enabled out-of-state telehealth services, potentially reducing the perceived need for waivers. States with Democratic governors and, potentially, a history of expanded publicly provided health insurance coverage, may have emphasized structural reforms over temporary measures. Consequently, they might have leveraged established frameworks such as the IMLC, reducing reliance on waivers. Indeed, Democratic states were more likely to have participated in such compacts before the pandemic, whereas Republican states were less likely to join until 2021 or later, with some not entering until 2022 or even 2023. As such, compact adherence emerges as an important mediator in the interpretation of the estimated relationships of political affiliation with policy outcomes. Another mechanism potentially influencing this policy variation within the political landscape may be differences in vaccination attitudes and uptake between Republican and Democratic voters reported in prior studies.36
CON laws, traditionally designed to restrain healthcare costs, present an intriguing dichotomy in their association with waiver likelihood versus payment parity. Introducing payment parity was likely to maintain waivers, which may reflect how additional regulatory processes may influence healthcare service availability.37 Conversely, the increased likelihood of payment parity adoption in these states operates in the opposite direction to potentially elevate overall healthcare spending.
This increase in payment parity odds, given cost control regulations such as CON laws, could indicate a shift towards encouraging telehealth use over in-person care. By implementing payment parity policies, state regulators may have aimed to incentivize healthcare supply more generously. This hypothesis gains support from recent evidence that, while payment parity had little effect on telehealth use before the pandemic, its presence during and after the pandemic led to a significant 74% increase in telehealth utilization.31 This rise underscores the importance of payment parity in encouraging the use of telehealth services. Consequently, for states looking to alleviate pressure on their healthcare systems and mitigate costs, introducing payment parity may be viewed as another policy lever to incentivize a shift from in-person to virtual care.
Additionally, the reported association of IMLC participation with decreased odds of maintaining both waivers and payment parity policies appear intuitive, as participation already facilitates interstate telehealth. This raises the possibility of a potential substitution effect between waivers and compacts and connects to ongoing policy debates about whether medical boards through licensure, or state governments through executive orders should regulate interstate telehealth services.38,39 Moreover, the potential for enhanced physician growth and a higher density of physician practice locations in IMLC states may have facilitated adequate access to care, thereby reducing importance of waivers.40 Concerning socioeconomic factors, our analysis did not identify a statistically significant relationship between unemployment rates or Medicaid enrollment and the adoption of either waivers or payment parity. This suggests that socioeconomic considerations may play a limited role in the decision-making process for enacting these policies.
Though not explicitly examined in this first stage analysis, prior evidence suggests mixed clinical effectiveness of telehealth during the PHE.41 Retrospective analysis using a large, integrated health system dataset, reveals that telehealth visits, while expanding access, were associated with higher follow-up rates for conditions such as musculoskeletal pain and abdominal concerns when compared to in-person visits. Others, however, emphasized the overall positive impact of telehealth on patient access and satisfaction.42 These findings, though not directly aimed at waivers, suggest that although telehealth visits improve accessibility, they may not fully address the complexity of certain clinical conditions. A second-stage analysis could explore how these waivers affect clinical outcomes across diverse patient populations, providing essential data to inform future telehealth policies.
The quantitative analysis presented in this study is enriched by real-world narratives that illustrate the profound impact and challenges of telehealth policy decisions during the COVID-19 pandemic. Healthcare systems experienced unprecedented shifts in service delivery, with regulatory flexibilities transforming telehealth into a key resource for patients unable to access in-person care. These policy changes not only expanded access but also prompted a reevaluation of regulatory barriers, such as state-specific licensing restrictions and reimbursement models, which had historically hindered the broader adoption of telehealth.43
Anecdotal reports from the Wall Street Journal indicate substantial challenges related to cross-state telehealth restrictions.26 A New Jersey lawsuit highlighted the challenges of inconsistent state medical licensing laws for telehealth providers. The case demonstrated how these outdated regulations, designed for in-person care, hinder remote healthcare delivery, especially in specialty care. It emphasized the need for regulatory harmonization, as these rules impeded timely access to essential services. Healthcare providers also faced operational issues, including strained technology infrastructure and variability in patient engagement and adherence.43 Together, these narratives underscore the fragmented nature of decision-making during the pandemic, offering a deeper understanding of the barriers and motivations that shaped telehealth policy implementation, and the data presented in this study.
Beyond the PHE, these findings align with broader policy analyses of post-pandemic lessons learned. The rapid regulatory innovations prompted by the COVID-19 pandemic underscore several essential lessons for future telehealth policymaking. First, the swift expansion of licensure waivers and payment parity policies highlighted the necessity for adaptive, state-level flexibility to maintain continuous healthcare access. This study's results underscore the importance of regulatory adaptability for emergency preparedness. Moving forward, regulators should contemplate the creation of emergency response protocols that facilitate the swift implementation of licensure waivers and payment parity policies during public health emergencies. Second, the widespread adoption of telehealth demonstrated the potential of these modalities to address significant care gaps. Expanding specialty health services through telehealth and reducing barriers in licensing and reimbursement structures is considered helpful in alleviating persistent specialty physician shortages in the face of growing demand.34 The study shows that relaxation of telehealth policy is positively associated with public interest in the care modality. Lastly, as telehealth services increasingly cross state lines, the urgency for standardized, secure, and interoperable data-sharing frameworks becomes evident. While states leveraging interstate compacts, such as the IMLC, minimized the need for waivers and modeled effective cross-state care, interoperable data systems will be essential for ensuring patient safety, continuity of care, and regulatory oversight in an evolving telehealth landscape. These insights equip regulators with policy indicators to enhance their readiness to public health emergencies, balancing flexibility with rigorous oversight to support sustainable, equitable telehealth access in the future. Additional obstacles that state policymakers may need to overcome to implement policy changes include distrust towards medical experts and political polarization, both of which have been shown to influence attitudes and behaviors related to COVID-19.44,45 A potential solution may involve policymakers actively engaging with local communities to foster trust and ensure transparent communication regarding telehealth policies and benefits. Public education campaigns that emphasize the safety, effectiveness, and accessibility of telehealth may enhance public trust and facilitate broader adoption.
Another important consideration is the potential benefit of establishing a standardized interstate licensure framework in advance of future public health crises. The variation in state-based telehealth policies during the pandemic revealed inefficiencies in the ability to quickly implement and scale telehealth services. A more coordinated approach to physician licensure could enhance system preparedness and facilitate continuity of care across state lines.46 Additionally, as telehealth utilization continues to evolve, ongoing legal and regulatory challenges highlight the need for a structured framework that balances state regulatory authority with the benefits of increased interoperability.47
In sum, the determinants of telehealth policy adoption, specifically concerning waivers and payment parity during the COVID-19 pandemic, encompass a broad spectrum of factors, from public health imperatives and existing healthcare policies to political influences and healthcare infrastructure demands. These elements collectively underscore the critical importance of responsive, flexible healthcare policy frameworks. Such frameworks are essential for navigating the evolving landscape of healthcare challenges, ensuring that telehealth remains a cornerstone of future healthcare delivery.
Study Limitations
This study is subject to several limitations. First, it is essential to acknowledge the correlational nature of our model and the potential confounders that may affect the observed coefficients.
Second, we do not account for non-health-related state policy responses such as shelter-in-place orders which may be an important omitted variable in our study setting. Studies have shown that the introduction of government-imposed social distancing measures reduced the COVID-19 caseload growth by 5.4 to 9.1 percentage points within 5 to 20 days, which may influence state policy responses1.
Third, due to the recency of the study period, only a limited number of determinants is available to construct measures of hospital competition such as a Herfindahl-Hirschman index (HHI). To circumvent this issue, we instead rely on a measure of new medical right business formation, which encapsulates some of the elements an HHI would but fails to accurately estimate market power and correlated factors such as insurance competition within each market.
A fourth limitation lies in the binary coding of the payment parity outcome which does not capture variation in reimbursement rates and may lead to loss of policy-relevant information regarding near-parity implementations (eg, 75% reimbursement rates and service-dependent parity).
Fifth, the narrow focus on gubernatorial party affiliation as the primary political variable may be offering a limited perspective of the political landscape. While we considered the inclusion of additional political factors, such as the proportion of the state legislature controlled by each party, these variables exhibited low variation over the study period, inhibiting their predictive power. This lack of further political variables means that our model may not fully account for the broader political context that could have influenced telehealth policy decisions. Nonetheless, the focus on gubernatorial party allegiance is justified by the fact that telehealth waiver decisions were commonly enacted through executive orders issued by state governors. In this context, the governor's party affiliation may have influenced their stance on health policy, driving both the adoption and rescindment of telehealth waivers. While this approach offers a somewhat narrow perspective of state-level political complexity, it includes the primary decision-making force behind telehealth policies during the pandemic.
A sixth limitation lies in the absence of linkages to claims or health outcomes data, which hampers our ability to evaluate the clinical implications of telehealth waivers and parity on health outcomes. Our primary goal is to contribute a shortlist of key state-level policy factors that have significantly influenced telehealth policy. This evidence can inform future empirical analyses of how these legislative changes impact health outcomes. Given the state-level factors are associated with state policymakers’ nature of policy decision-making, identifying these determinants offers health services researchers important explanatory variables for regression adjustment to facilitate subsequent evaluations of these policies’ causal effects on clinical outcomes.
Conclusion
Our study aimed to identify the determinants of telehealth policy during the PHE. Logistic regression analysis revealed the associations between public health outlook, state policy and socio-economic factors with the likelihood of states enacting licensure waivers and implementing payment parity. Notably, the maintenance of licensure waivers and payment parity was primarily influenced by participation in Medicaid expansion under the ACA, public health challenges affecting the elderly, the state governor's political orientation, and pre-existing state healthcare supply policies. These results cast light on the multifaceted considerations that informed telehealth policy decisions, highlighting how public health metrics, political structures, and existing healthcare systems interact to inform policy trajectories in the face of a healthcare emergency.
The study findings contribute to the current policy debate on whether to extend telehealth flexibilities, such as licensure waivers and payment parity, past 2024 by shedding light on the specific state-level conditions that led to the implementation of these policy adjustments. Specifically, a refined understanding of the determinants of state-level telehealth policy is paramount as policymakers deliberate the costs and benefits of perpetuating telehealth initiatives beyond the PHE. The empirical evidence in this study provides fresh perspectives of the dynamics associated with the adoption and rescindment of telehealth flexibilities introduced during the PHE. Moreover, these estimates serve as reference points for legislative changes in future public health emergencies, highlighting factors that have historically correlated with policymaking actions.
Future research should consider the intended and unintended consequences of these policy changes on clinical outcomes, individual medical expenditures and state healthcare spending.
Given the potential for changes in clinician behavior due to payment parity—such as the possibility of fraudulent telehealth billing to secure higher reimbursement—it is important for future research to investigate how the adoption of payment parity might affect instances of reimbursement fraud.22
Acknowledgments
Dr. Koumpias recognizes support from the Undergraduate Research Opportunity Program at the University of Michigan under Project ID 29111, Project 156, and we thank Bingzhi “Icey” Li for excellent research assistance.
Supplementary Appendix
A.1 Model Specification
To identify determinants of telehealth policy, we estimate the following logit regressions equation:
where Yit = {Waiversit, PaymentParityit}, a vector of binary outcomes denoting in-state licensure requirement waivers and payment parity adoption, respectively, in state i in month t, is regressed on several explanatory variables collected in vector X with uit being the error term.
Additionally, we specify state and month-fixed effects and cluster standard errors at the state level.
A.1 Data normalization
Summary Statistics for Normalized Variables
Footnotes
Open Access: © 2025 The Authors. Published by the Journal of Medical Regulation. This is an Open Access article under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC, https://creativecommons.org/licenses/by-nc/4.0/), which permits use and distribution in any medium, provided the original work is properly cited, and the use is noncommercial.
Funding/support: The study was supported by the University of Michigan's Undergraduate Research Opportunity Program which aided in recruiting the co-author. The program directors had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation.
Other disclosures: The authors declare that they have NO affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript.
Author Contributions: Conception of original research and project supervision (AK); Design and implementation of the research (AK, MN); Results analysis (MN); Writing of the manuscript and critical revision of the manuscript (AK, MN)
- Received April 29, 2024.
- Revision received February 3, 2025.
- Accepted April 30, 2025.
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