Federalism and the Value of Institutional Experience During a National Disaster: Identifying Determinants of Rapid Emergency Medicaid Waiver Adoption During the Covid-19 Pandemic

On January 31, 2020, HHS Secretary Azar declared covid-19 a national public health emergency, which was followed by President Trump’s March 13^th proclamation declaring the covid-19 outbreak a national emergency (Proclamation No. 9994). In tandem, these two executive actions permitted Secretary Azar to invoke the Section 1135 Waiver Authority, immediately granting medical providers across the country “blanket” regulatory flexibilities (42 U.S.C. 1320b–5). That day, Florida became the first state to initiate additional regulatory flexibilities through an 1135 waiver request (CMS 2020). By April 16, all fifty-one states had submitted a request for specific flexibilities (Medicaid 2020).

While the HHS Secretary can permit “blanket” waivers over the affected regions, once the Section 1135 Waiver authority has been invoked, states in the designated emergency area can begin initiating state-specific flexibility and capacity requests (CMS 2017). In recent decades, especially with the passage of the Patient Protection and Affordable Care Act (PPACA) which further empowered state waiver institutions (2010), governors and agency directors have been largely responsible for requesting waivers (Thompson, 2013). Though state legislatures have codified statutes which either expedite or hinder a governor’s ability to act unilaterally, most state legislatures passively allow the executive branch sole authority to request 1135 waivers, leaving governors and agency directors to exercise authority (Hinton, 2019; NCSL 2017).

Emergencies pose an immediate threat to health so it can be safely assumed that, all else equal, a more rapidly requested waiver will be more effective. For the covid-19 emergency, thirty-four days separate the first and last waiver request (CMS 2020). But what caused some states to request a waiver sooner than others? Was this variation a function of covid-19 outcomes? Or, were other state-specific factors contributing to the timing of a request? Previous studies suggest that financial capacity and politics significantly influence the utilization of current waivers (Nattinger, 2016; Nattinger & Kaskie, 2017). Yet, no study has systematically investigated the determinents of emergency waiver adoption.

While likely uncorrelated with the state’s covid-19 situation, this analysis hypothesizes that Section 1135 waiver precedent from previous emergencies is a major determinant of the timing of a covid-19 waiver request. Along with previous 1135 Waiver experience, this analysis tests if the timing of covid-19 waiver requests are associated with contextual (supply and demand), institutional, political, or external factors. For example, were states with higher proportion of people susceptible to covid-19 hospitalizations more likely quickly demand an increase in hospital capacity? Or, were 1135 Waiver decisions driven by state supply of hospitals? Additionally, after controlling for contextual factors how do state agency, legislative, and executive capacity influence 1135 Waiver time to adoption? And what role, if any, does state ideology play in the realm of emergency waiver negotiations?

Covid-19 has reminded policy-makers that national disasters do not impact states uniformly. Given that 1135 Waivers were designed to provide states flexibility to meet their contextually specific needs, ideally emergency waiver activity during covid-19 will be determined by each state’s need during the first month of the pandemic. If, however, factors unrelated to need are driving 1135 Waiver timing, then without further action existing disparities could be intensified as a result of underlying differences between the states.

Methods

This study utilizes a Time-to-Event analytical design to identify significant determinants influencing the adoption of a state’s 1135 Waiver request. These study designs have traditionally been used by public health researchers to model survival (Lee & Go, 1997). More generally, any event which is a function of the length of time from onset can be incorporated into a Time-to-Event analysis (Schober & Vetter, 2018). In primary model, the event of interest is a state requesting a Section 1135 Waiver, while the time between disaster proclamation and state request date is the dependent random variable. The primary independent (binary) variable is whether a state has previously requested Section 1135 Medicaid flexibilities during previous emergencies.

Time-to-event policy analyses can be modelled with a multitude of approaches, each allowing for different levels of interpretability and complexity. To enhance the robustness of this study, three different approaches are used: Kaplan-Meier, Cox Proportional Hazard, and Parametric (Gamma).

The Kaplan-Meier analysis, considered the most general, is a non-parametric model which evaluates the time to survival between two distinct groups (Dudley 2016). As a non-parametric model, the Kaplan-Meier estimate will not be sensitive to the underlying distribution of a state’s time to request. This Kaplan-Meier model compares the timing to a covid-19 waiver request between states with and without 1135 waiver precedent from previous emergencies. However, this Kaplan Meier estimate cannot control for any other covariates influencing a state’s timing to request (Rich 2010).

To include additional variables which could potentially identify factors influencing a state’s timing to request, two other approaches are used: A Cox Proportional Hazard Function and Parametric Model. A Cox Proportional Hazards analysis estimates the associated “risk” of requesting a waiver at any given time (conditional on not having already requested a waiver). Conversely, the parametric model estimates the effect of each variable on the length of time to waiver request. Along with interpretability, this parametric model holds other benefits over the Kaplan-Meier and Cox methods. Typically, parametric models may not be favored as they require additional assumptions related to the selected distribution (Abadi 2012; Siannis 2005). However, a Generalized Gamma incorporates multiple distributions and provides greatest flexibility under minimal assumptions (Cox 2007; Cox & Matheson, 2014; Matheson 2017). Another benefit to the parametric model is the inclusion of robust standard errors, which can account for potential heteroskedasticity in the model (Yau, 2001; Gutierrez, 2002). Following a framework developed by previous time-to-event studies, the Gamma analysis fit a Contextual, Institutional, Political, External, and a combined Integrated model (Berry, 1990; Nelson, 2007; Eaton, 2013). As a sensitivity analysis, Cox model estimates will be reported, along with a test of the assumption that risks do not differentially vary over time for each model.

The data for each state’s Section 1135 Waiver request date were obtained from CMS correspondence with state Medicaid Directors. Previous 1135 Waiver activity were obtained by a systematic process 1) identifying previous public health emergencies for all states (DHHS, 2020), 2) identifying which public health emergencies led to an invocation of Section 1135 Waiver authority (DHHS 2020), 3) reviewing archival correspondence (CMS 2020; PHE 2019; ASTHO 2010) and federal government reports (81 FR 63859).

Following guidance from previous policy determinants research (Imhof & Kaskie, 2008; Nattinger, 2016; Nattinger & Kaskie, 2017), this study’s conceptual framework motivates the inclusion of state indicators related to the supply and demand of covid-19 care (contextual factors); administrative, executive, and legislative capacity to respond to a pandemic (institutional factors); and state ideology (political factors). Additionally, this study includes state and regional indicators to conceptualize external factors which may have influenced when and how a state requested a Section 1135 Waiver. State demand for covid-19 response was operationalized as the percentage of the population over age 65, percentage of the population with multiple co-morbidities, and the percentage of the population covered by Medicaid insurance (Jordan 2020). Given the intensity of treatment necessary to care for covid-19 patients, state supply factors include hospitals per capita and Intensive Care Unit (ICU) beds per capita (Hancock, 2020; Waldman 2020). State Medicaid agency capacity was operationalized using recent state expenditure data (Medicaid, hospitals, and total healthcare spending) and if the state had a current Section 1115 Medicaid Waiver (Jordan 2020; (Hinton 2019). Legislative and Executive Capacity were operationalized with salary and staff expenditure data, while the Executive model also included “Line Item Veto” and additional public health emergency authority (Jordan 2020; Perkins 2019). State ideology included the current Governor’s political affiliation, the percentage of Democrats in the current state senate, and the estimated percentage of citizens with “liberal views” (Jordan 2020; NCSL 2019; NGA 2020). Finally, along with the covid-19 cases and deaths at the time of the requested waiver, the external model also included a binary variable indicating if a new 1135 Waivers was requested in the region. Regions were determined by state networks (Olsen 2019).

Results

Unadjusted, Bivariate Kaplan-Meier, Cox, and Parametric Models

States with Section 1135 precedent in previous disasters submitted requests to CMS more quickly than states without prior experience, however these differences were only marginally significant (Figure 1). Figure 1 shows that states with at least one previous 1135 Waiver experience requested a covid-19 waiver more quickly (p = 0.1023). Additionally, states with two or more prior 1135 experiences requested a covid-19 waiver more quickly than states with one or fewer previous 1135 waiver experiences (Figure 2, p = 0.0500). In this unadjusted model (Table 1), the Cox Proportional Hazard for states with 1135 precedent indicated a higher likelihood of requesting a covid-19 waiver at any given time (Hazard Ratio 1.5605), however this effect was not significantly different than states without precedent. For the parametric model, however, the time-to-waiver request was (marginally) significantly less for states with previous 1135 Waiver experience (Time Ratio = 0.7522).

Integrated Model

As expected, the Full Integrated Model had the best fit (p < 0.0001). Within this integrated model, four indicators were significantly associated with a shorter time to request: history of a previous waiver (0.7248, p <0.01), state health expenditures (0.9994, p <0.001), a democratic governor (0.6794, p <0.05), and a new 1135 Waiver request in the region (0.8424, p <0.001). The only variable with a statistically significant association with longer time-to-request were covid-19 cases (1.0230, p<-.001). Table 2 reports the full estimates from each model’s effect on time-to-waiver request, as well as the Cox Proportional Hazards results as a sensitivity analysis.

Discussion

The critical nature of this ongoing disaster warrants persistent attention from policy-makers at all levels of government. While only a segment of the total covid-19 response, Section 1135 Waivers provide a unique opportunity for states to redirect healthcare resources and expand health system capacity. Yet, this research shows that states have taken different approaches even within the Section 1135 Waiver authority. In summary, institutional (1135 Waiver experience and state agency capacity) and external (a new 1135 Waiver in the region) factors are associated with the timing of a state response. These pre-existing differences between states potentially determining the timing of 1135 policy becomes problematic. However, this new evidence should promote continual innovation by state and local policy-makers. As states continue requesting second and third 1135 Waivers for covid-19 (CMS 2020), the public should expect more timely requests.

The covid-19 pandemic has motivated examinations on American Federalism during a public health emergency. These findings continue that discussion.

Federalism and Covid-19

The framers of the U.S. Constitution, while never explicitly using the term “emergency,” understood the risks and benefits of instituting centralized authority during times of national emergencies (Hamilton, 1787). Fearing the risk of unchecked presidential authority as a precursor to tyranny, emergency powers were not allocated to the executive branch (Hamilton and Madison 1788). Rather, Article 1, Section 8 of the U.S. Constitution grants Congress the power to declare war, call upon an army in times of war, and maintain an army during times of peace (critical to any legal analysis of modern emergencies was the foresight to extend these powers to situations seemingly unpredictable in 1788, including disasters during times of peace (Madison 1788)). Yet, despite the risks of concentrated emergency power within the Executive branch, the framers of the Constitution understood the value of such power when responding to an emergency in a timely, effective manner; resulting in largely undefined and broadly interpreted executive authority during emergencies (Fisch, 1990). As presidents began to exert their influence through emergency proclamations and executive orders, the federal Judiciary responded with oversight powers to mitigate presidential overreach (i.e.: Ex parte Merryman 1861; Youngstown Sheet & Tube Co. v. Sawyer 1952).

During the twentieth century, the constitutionally prescribed distribution of emergency powers shifted. Nearing the end of World War II, congress passed the Public Health Services Act (42 U.S.C. ch. 6A § 201); of which section 319 grants the Health and Human Services (HHS) Secretary authority to declare a national public health emergency (42 U.S.C. 247d). Two subsequent statutes continued the shift of emergency power from Congress to the President: The National Emergency Act of 1976 (50 U.S.C. §§ 1601-51) and the Robert T. Stafford Disaster Relief and Emergency Assistance Act of 1988 (42 U.S.C. §§ 5121-5207). Both acts explicitly delegate authority to declare a national emergency to the President. Finally, when both a public health and national emergency are declared, the HHS Secretary can invoke Section 1135 Waiver Authority and grant regulatory flexibilities to providers and hospitals in the designated emergency areas (42 U.S.C. 1320b–5). However, while precedent is limited, just as in the wartime cases against executive overreach, the Judiciary maintains authority to ensure both the President and Secretary act within their delegated emergency powers (PHN v. U.S. 2015).

Contemporary analysis suggests two general approaches to understanding federalism. The first explores the changing power within each branch and level of government; the second explores the propensity for cooperation (Rigby & Haselswerdt, 2013; Weil, 2013) or competition (Shannon & Kee, 1989; Volden, 2005; Weil, 2009) between jurisdictions. The results of this study provide insight for both approaches. Unlike other Medicaid Waivers, which are largely driven by state executives and agency directors (Weissert & Scheller, 2008; Weissert & Weissert, 2017), Section 1135 Waivers place more authority within the federal executive branch. Even after 1135 invocation, which requires two federal actions, the HHS Secretary immediately provides a set of “blanket” flexibilities for all states, minimizing any subsequent request. State power is also reduced from the “bottom-up,” as local or municipal governments and health systems have the ability to bypass state authority to request their own waiver. This reduced authority, however, doesn’t apply generally to the covid-19 pandemic which has shown massive expansion of state executives’ role (Cook 2020). Most interesting, however, is the apparent diffusion between states. By adopting concurrent waivers with other states in each region, the 1135 Waiver diffusion fits other cooperative activity necessary for states to pool resources, signaling that Section 1135 Waiver experience and expertise may be a valuable resource to neighboring states.

Conclusion

This is the first study to identify significant determinants of Section 1135 Waivers. If quality is defined by quicker requests, then the quality of emergency waivers during the covid-19 pandemic are largely determined by institutional and external factors. Meanwhile, supply and demand to do not appear to be driving the timing of emergency waiver decisions. These findings should motivate further research investigating the impact of late adoption effects on covid-19 outcomes, but more importantly, inform immediate policy decisions as state policy-makers continue to navigate the ongoing pandemic

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Appendix

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