Medicaid Managed Care Network Adequacy Standards and Mental Health Care Access

ABSTRACT

Objectives: Medicaid is the largest payer of mental health (MH) services in the US, and more than 80% of its enrollees are covered by Medicaid managed care (MMC). States are required to establish quantitative network adequacy standards (NAS) to regulate MMC plans’ MH care access. We examined the association between quantitative NAS and MH care access among Medicaid-enrolled adults and among those with MH conditions.

Study Design: Cross-sectional study with a difference-in-differences design.

Methods: Using the 2016-2019 National Survey on Drug Use and Health, we included Medicaid enrollees aged 18 to 64 years in 15 states. Subgroup analyses included enrollees with MH conditions who experienced in the past year (1) serious psychological distress, (2) a major depressive episode, and/or (3) suicidal thoughts. Outcomes assessed whether in the past year the enrollee had any (1) MH services, (2) inpatient MH stays, (3) outpatient MH visits, (4) MH prescription, and (5) unmet MH care needs.

Results: Among 9300 adults aged 18 to 64 years, 27.2% had MH conditions. Among all adults, NAS were marginally associated with increased use of any MH services (adjusted OR, 1.4; 95% CI, 1.0-2.1; P = .055) but were not associated with other outcomes. Among enrollees with MH conditions, no statistically significant association between NAS and MH care access was observed.

Conclusions: Current quantitative NAS requirements may have few impacts on improving MH care access for adults and those with MH conditions without the implementation of additional interventions. States should consider adjusting enforcement strategies and adopting other interventions alongside NAS.

Am J Manag Care. 2025;31(1):In Press

Takeaway Points

States are required to set network adequacy standards (NAS) for Medicaid managed care plans to ensure adequate access to mental health (MH) care. We examined the association between NAS and MH care access (including any MH services, inpatient MH stays, outpatient MH visits, MH prescriptions, and unmet MH care needs) among all adults aged 18 to 64 years and those with MH conditions.

• NAS were not associated with significant changes in MH care access among all adults aged 18 to 64 years and those with MH conditions.
• Current quantitative NAS requirements may have limited effectiveness in improving MH care access for Medicaid enrollees without additional interventions.

More than 1 in 5 adults in the US experiences a mental health (MH) condition every year.¹ Within this population, approximately one-fifth are covered by Medicaid.² Notably, more than 80% of Medicaid-enrolled adults receive services and insurance coverage through Medicaid managed care (MMC) plans.³ Under this arrangement, state Medicaid agencies contract with private insurance plans to provide health services and insurance coverage for a monthly per-enrollee payment.⁴ Although MMC plans are required to cover a broad range of MH services, many MMC enrollees face barriers to accessing needed MH services.

MMC enrollees usually receive services from in-network providers who contracted with their MMC plans. However, in efforts to contain medical spending and improve care quality, MMC plans often selectively contract with providers to form narrow provider networks, which can limit MMC enrollees’ access to care.^5-7 The access constraints imposed by narrow provider networks can be especially binding for enrollees who might otherwise seek care from out-of-network MH providers. Notably, more than 50% of MH providers listed on MMC plans’ provider directories do not see any Medicaid patients, and more than 60% of office-based MMC in-network psychiatrists do not accept new patients.^8-10

To improve access to care for MMC enrollees, the federal government has mandated that states set network adequacy standards (NAS) to regulate MMC plans’ provider networks. These NAS requirements were initially detailed in the 2016 MMC final rule and have continued to evolve.¹¹ The current NAS requirement, as outlined in the 2020 MMC final rule, requires specifying quantitative standards for 1 or more types of commonly used NAS (hereafter “quantitative NAS”), including standards on travel time and distance, appointment wait times, and provider-to-enrollee ratios.¹² Notably, although the requirement of quantitative NAS officially took effect in 2020, many states had already adopted quantitative NAS before the effective date.

Although NAS are a topic of contemporary interest in federal policy making,^13,14 few studies have examined the effectiveness of NAS in improving access to care for MMC enrollees. We identified only 2 studies on NAS, with both indicating that NAS have not been effective in improving general specialty care access for children and adults.^15,16 Despite the great need for MH care among Medicaid enrollees, to our knowledge, no studies have examined NAS’ effects on access to MH care. We fill this gap in the literature and provide the first evaluation of NAS and their association with key measures of MH care access, including service use and perceived unmet needs,^17,18 for Medicaid-enrolled adults aged 18 to 64 years by drawing on the dynamic policy environment from 2016 to 2019.

METHODS

NAS for MH Providers

We identified the following 15 states with data on NAS from 2016 to 2019 by reviewing publicly available MMC documentation (including MMC contracts and model contracts, requests for proposals, relevant administrative codes, and reports): Arizona, Colorado, Florida, Kentucky, Massachusetts, Minnesota, Missouri (2017-2019; Missouri’s statewide MMC program started in 2017), New Jersey, Ohio, Rhode Island, South Carolina, Tennessee, Virginia (2017-2019; 2016 data were unavailable), Washington, and West Virginia (2017-2019; 2016 data were unavailable).

We constructed a state-year–level data set on adoption (presence vs absence) of quantitative NAS specifically for MH providers based on MMC documentation. Consistent with the current NAS requirement (as specified in the 2020 MMC final rule), we considered the adoption of any quantitative standards on travel time and distance, appointment wait times, or provider-to-enrollee ratios for any MH provider as “presence” of NAS.¹² Additionally, we classified states that did not specify specific standards for any MH providers but included quantitative standards for “behavioral health providers” or “behavioral health services” as presence of NAS. Conversely, nonquantitative standards or absence of any standards for MH providers in MMC documentation were considered “absence” of NAS. For example, because Ohio’s 2016 MMC contract language—“although there are currently no capacity requirements of the non–primary care required provider types, plans are required to ensure that adequate access is available to members for all required provider types”—did not specify any quantitative standards for any MH providers, we considered Ohio in 2016 as having an absence of NAS.¹⁹ See eAppendix 1 (eAppendices available at ajmc.com) for details on specifications of NAS adoption among study states during our study period.

Data and Study Sample

We used 2016-2019 restricted-use data from the National Survey on Drug Use and Health (NSDUH) to identify Medicaid enrollees aged 18 to 64 years for our study sample. Enrollees with missing data in covariates and/or outcome measures (approximately 2.2%) were excluded from analyses. To comply with the disclosure protocol of the Substance Abuse and Mental Health Services Administration (SAMHSA), we reported all sample sizes to the nearest hundred.²⁰

The NSDUH is an annual, nationally representative survey on MH, substance use, and service utilization among noninstitutionalized individuals 12 years and older in the US. During the study years, the NSDUH was administered via computer-assisted self-interviewing methods during in-person interviews, with an overall weighted response rate ranging from 45.8% to 53.3%.^21-24 The restricted-use data provided geographic identifiers (including state and county) in addition to the data available in public-use files, allowing us to link the NSDUH with Area Health Resources Files and the 2016-2019 MMC enrollment reports.²⁵ The protocol and results of this study were reviewed and approved by the SAMHSA.

For subgroup analyses, we identified Medicaid-enrolled adults aged 18 to 64 years with MH conditions. This subgroup included those who experienced any of the following MH conditions in the past year: (1) major depressive episode (MDE), (2) serious psychological distress (SPD), and (3) self-reported suicidal thoughts. Specifically, the NSDUH’s assessment of MDE is based on the criteria in the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) and includes survey questions adapted from the depression section of the National Comorbidity Survey Replication.²⁶ The assessment of SPD is based on the Kessler Distress Scale, a validated instrument to screen for serious mental disorders.^26,27

Outcomes

Outcomes included 5 measures of MH care access that assessed whether in the past year the respondent had any (1) MH services (including inpatient or outpatient visits and medication prescriptions), (2) inpatient MH stays, (3) outpatient MH visits, (4) MH prescription (ie, “prescription medication that was prescribed to treat a mental or emotional condition”), and (5) unmet MH care needs (ie, “feeling a perceived need for mental health treatment/counseling that was not received”).²⁸ Inpatient settings included psychiatric hospitals, psychiatric or medical units of general hospitals, other types of hospitals, residential treatment centers, and other facilities. Outpatient settings included MH clinics or centers, office-based providers, medical clinics, partial day hospitals or day treatment programs, and other outpatient settings (eg, schools). We provide details on the settings of MH services surveyed in the NSDUH in eAppendix 2.

Statistical Analysis

We used a difference-in-differences (DID) approach to examine the association between NAS adoption and MH care access. Using our state-year–level data on NAS adoption, we classified 15 study states into new-NAS states and comparison states. New-NAS states were states that changed from absence to presence of NAS for MH providers during the study period, including Colorado, Ohio, and West Virginia. Specifically, both Colorado and Ohio newly adopted quantitative NAS in 2018 by setting standards on travel time and distance and provider-to-enrollee ratios for different MH providers.^29,30 Additionally, West Virginia newly adopted quantitative NAS by setting travel time and distance standards for various types of MH providers in 2019.³¹ Comparison states were the 12 states that had adopted NAS for MH providers and had no changes in their standards from 2016 to 2019. Specifically, the new-NAS states were considered the treatment group, and the 12 comparison states were the comparison group in our DID study design. Specification of NAS adoption and classification of new-NAS states and comparison states can be found in eAppendix 1.

The DID approach relies on a parallel trends assumption that the trends in outcomes would be similar between new-NAS states and comparison states after the new-NAS states adopted NAS if they had not adopted NAS. We tested this assumption by analyzing trends in outcomes from the years before new-NAS states adopted NAS. Test results showed no statistically significant differences in the trends during the preadoption years (eAppendix 3).

Our analysis included 2 steps. Using logistic regression models, we first examined the association between NAS and each outcome among all Medicaid-enrolled adults aged 18 to 64 years in our study sample. Second, we conducted subgroup analyses to examine the association among those with MH conditions.

All models controlled for demographic characteristics, socioeconomic characteristics, need-related factors, contextual factors, the NSDUH’s complex survey design, and year and HHS region fixed effects. Demographic characteristics were sex, age, and self-reported race and ethnicity. Socioeconomic characteristics included education, family income, and the metropolitan status of the respondent’s residence. Need-related factors included self-rated overall health and the number of self-reported chronic conditions in the past year (see eAppendix 4 for chronic conditions surveyed in the NSDUH). An additional dichotomous need-related factor indicating whether the respondent had any MH condition (ie, MDE, SPD, and/or suicidal thoughts) was included in the full sample analyses but was excluded in subgroup analyses. Two contextual factors included state-year–level MMC penetration derived from the 2016-2019 MMC enrollment reports³² and county supply of psychiatrists and psychologists per 100,000 population derived from the Area Health Resources Files.³³ Year fixed effects (ie, series of year dummy variables) were applied to control for confounding effects associated with national year-varying trends (eg, national economy). We also applied HHS region fixed effects to control for confounding effects of time-invariant differences across regions (eg, regional differences in Medicaid office administrative processes).

Data were analyzed using Stata/SE 16(StataCorp LLC). We applied “svy” and “subpop” commands to calculate estimates for our analytic sample and used the full data in the NSDUH to estimate robust SEs (ie, Huber-White sandwich estimators) that properly adjusted for the NSDUH’s complex survey design.^21-24 The institutional review board of Emory University approved this study.

RESULTS

Sample Characteristics

This cross-sectional study included 9300 Medicaid enrollees aged 18 to 64 years. Among all these adults, 56.4% were self-reported non-Hispanic White, 18.8% were non-Hispanic Black, and 18.1% were Hispanic. More than one-fourth of these enrollees experienced any MH condition in the past year (27.2%), and more than one-third had 1 or more chronic conditions (39.4%) (Table 1). Additionally, 25.2% of these enrollees used any MH services in the past year, and MH prescription was the most common type of MH treatment used (21.6% vs 3.1% for inpatient stays and 13.7% for outpatient visits).

Adult Medicaid enrollees in new-NAS states, compared with those in comparison states, were more likely to be non-Hispanic White (66.8% vs 53.2%, respectively; P < .001), have a family income less than 100% of the federal poverty level (49.6% vs 45.4%; P = .02), and live in small metropolitan counties (37.9% vs 28.2%; P < .001). Enrollees in new-NAS states were also more likely than those in comparison states to experience any MH condition in the past year (30% vs 26.4%; P = .01), to receive any MH treatment (28.8% vs 24.1%; P = .001) and outpatient MH treatment (16.9% vs 12.8%; P < .001), and to report having unmet MH care needs (12.2% vs 9.7%; P = .004) (Table 1).

Association Between NAS and MH Care Access

In our full sample of Medicaid-enrolled adults aged 18 to 64 years, NAS adoption was not statistically significantly associated with our measures of MH care access (Table 2). Although NAS were marginally significantly associated with increased use of any MH services (adjusted OR [aOR], 1.4; 95% CI, 1.0-2.1; P = .055), the association was not statistically significant.

Among enrollees with MH conditions, we found no statistically significant association between NAS and MH care access (Table 3). We observed a positive association between NAS and any inpatient MH stays (aOR, 2.2; 95% CI, 0.9-5.4; P = .097), but the association did not reach statistical significance.

DISCUSSION

In this first study examining NAS and their association with MH care access, we did not find any statistically significant association between the adoption of quantitative NAS and improvement in MH care access among Medicaid-enrolled adults or among the subgroup with MH conditions. Our findings suggest that without additional enforcement or other complementary interventions, solely relying on NAS may have a limited impact on improving MH care access for adult enrollees, especially for those with MH conditions. Considering the great need for MH care among Medicaid enrollees, adopting additional interventions alongside NAS may be essential for states to ensure adequate MH care access for Medicaid enrollees.

Our findings on the absence of associations between NAS adoption and MH care access align with previous evaluations of NAS’ impact on overall specialty care access.^15,16 The absence of association may be partly explained by substantial variation in the rigor of NAS across states. The current NAS requirement grants states considerable flexibility in selecting the types and specific quantitative metrics in their standards, resulting in wide variation in NAS structures across states.³⁴ For example, Massachusetts required all MMC enrollees to travel no more than 30 miles or minutes to MH outpatient services,^35,36 but Colorado allowed enrollees to travel up to 90 miles or minutes to visit an MH provider.^29,35 Furthermore, some states, such as Rhode Island, have established standards for a more comprehensive list of MH providers (eg, adult MH prescribers, pediatric MH prescribers, and MH nonprescribers),³⁷ whereas other states, such as Florida, have set standards only for psychiatrists.^38,39

Insufficient state oversight and enforcement of NAS may also undermine these standards’ effectiveness in improving MH care access. Limited information is available regarding NAS compliance and the extent of state enforcement. Although most states require MMC plans to report their provider directories, few states verify the accuracy of these directories and their compliance with NAS. Because plan directories often are inaccurate and overstate provider availability,^8,10,40 using these directories to evaluate MMC plans’ networks may overestimate plans’ compliance with NAS. Furthermore, it remains unclear whether states have implemented alternative strategies for identifying and discouraging violations. A federal report found that even when instances of violations are identified, states rarely impose interventions (eg, sanctions, payment suspension) to correct these violations.⁴¹

Low MH provider participation in MMC and MH provider shortages may also limit the effectiveness of NAS in improving MH care access. MH providers are less likely to participate in MMC and accept new MMC patients than primary care providers and other specialists.^9,10 Potential reasons for the low provider participation in MMC include low reimbursement rates and the administrative burden associated with billing, contracting, and addressing claims denials and delayed reimbursements.^42-47 Additionally, MH provider shortages can make adhering to NAS particularly challenging, and nearly 50% of the US population resides in areas with a shortage of MH providers.^48,49 Without an adequate supply of MH providers, NAS can become practically less feasible because MMC plans may struggle to find and contract with MH providers in the area.

Another potential explanation for our findings on the absence of association is that NAS, along with other provisions in MMC contracts, may require a longer time to show substantial improvement in MH care access. Although our study and previous evaluations focused on changes in access within 2 years of NAS adoption, contractual terms of NAS and additional policies aimed at strengthening enforcement and compliance may need a more extended period to observe effects.

To achieve NAS’ intended goal of improving MH care access, states and MMC plans may consider adopting additional interventions. First, states may want to consider requiring more stringent NAS measures and improving oversight and enforcement of NAS. Notably, the recently announced 2024 MMC final rule requires states to use independent entities to conduct annual secret shopper surveys or enrollee experience surveys to verify NAS compliance, which may help with improving oversight and enforcement.¹⁴ Second, to increase MH provider participation in MMC, states and MMC plans could consider increasing reimbursement rates, streamlining contracting and billing processes, and shortening reimbursement processing timelines. Third,to extend the MH workforce, states may want to consider adding provider types that can bill Medicaid without a supervising practitioner and allowing reimbursement for services provided by trainees.^46,50 Lastly, future research could investigate the long-term effects of NAS, preferably using post-2022 data to mitigate confounding effects from the COVID-19 pandemic.^51-53

Limitations

This study has limitations. First, because we used repeated cross-sectional data from the NSDUH, causality could not be established. Similarly, this study is subject to limitations of survey data, including nonresponse bias and recall bias. Second, we relied on publicly available MMC documentation to identify the adoption of NAS. Due to limitations concerning data availability, some states with the largest MMC enrollment such as California and New York were not included in the study. Moreover, although our data represent a large data set with key information on Medicaid enrollees’ access to MH services, the sample size within our 15 study states may have limited power to detect some small but clinically significant associations between NAS and outcomes. In addition, we were unable to distinguish MMC enrollees from fee-for-service Medicaid enrollees. Although states determine MMC enrollment (exempt, voluntary, or mandatory) based on Medicaid eligibility categories (eg, low-income adults; aged, blind, or disabled), data on the NSDUH respondents’ Medicaid eligibility categories and corresponding category-specific MMC penetration rates were not available. To mitigate this limitation, we controlled for state-year–level MMC penetration among all adults in our analysis. Lastly, we did not examine the long-term effect of NAS due to changes in the NSDUH’s survey methods in 2020^54-56 and concerns about the COVID-19 pandemic’s confounding effects.^51-53 Additionally, potential differential impacts across service settings, types of NAS (ie, travel time and distance standards vs appointment wait time standards vs provider-to-enrollees ratios), and degree of stringency were not examined. This is an area that warrants future research.

CONCLUSIONS

In this first examination of NAS and MH care access, we found that adopting current quantitative NAS requirements alone may have few impacts on MH care access among adults aged 18 to 64 years and those with MH conditions. Given the substantial demand for MH care among Medicaid enrollees, additional policy efforts should be adopted alongside NAS to ensure adequate MH care access for MMC enrollees, especially for those with MH conditions.

Author Affiliations: Department of Population Health Sciences, Weill Cornell Medicine (JCH), New York, NY; Department of Health Policy and Management, Rollins School of Public Health, Emory University (JRC, ASW), Atlanta, GA; Department of Pediatrics, Emory University School of Medicine (XJ), Atlanta, GA; Children’s Healthcare of Atlanta (XJ), Atlanta, GA.

Source of Funding: This study was supported by Emory University and the National Institute of Diabetes and Digestive and Kidney Diseases (K01DK128384; ASW). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Prior Presentation: This study was presented at the 2023 Association for Public Policy Analysis & Management Fall Research Conference.

Author Disclosures: Dr Cummings and Dr Wilk reported receiving funding from the Substance Abuse and Mental Health Services Administration outside the submitted work. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (JCH, JRC, XJ, ASW); acquisition of data (JCH); analysis and interpretation of data (JCH, JRC, XJ, ASW); drafting of the manuscript (JCH); critical revision of the manuscript for important intellectual content (JCH, JRC, XJ, ASW); statistical analysis (JCH); obtaining funding (JCH); administrative, technical, or logistic support (JCH, JRC, XJ); and supervision (XJ, ASW).

Address Correspondence to: Ju-Chen Hu, PhD, Department of Population Health Sciences, Weill Cornell Medicine, 575 Lexington Ave, 6th Floor, New York, NY 10022. Email: juh4016@med.cornell.edu.

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