Challenges Faced by Medicaid Managed Care Coordinators Working With Members With Substance Use Disorder

ABSTRACT

Objectives: Medicaid managed care organization (MCO) care coordinators play a crucial role in assisting high-need Medicaid members with substance use disorder (SUD) and facilitating their connections with medical and social services. This study assessed challenges faced by care coordinators serving patients with SUD, including the types and frequencies of barriers, associated care coordinator and patient factors, and their relationship with burnout and job satisfaction.

Study Design: Web-based survey data from 322 Virginia Medicaid MCO care coordinators.

Methods: Coordinators rated 15 barriers related to providing services to patients with SUD. Principal components analysis (PCA) identified 3 subscales categorizing these challenges (challenges accessing resources, administrative and regulatory burden, and data integration). Multivariable linear regression explored associations between coordinator and patient factors and subscales for categories of barriers. Pearson correlations were used to examine the relationship between these barriers and job satisfaction.

Results: Coordinators reported a high frequency of challenges in many care coordinating activities: Between 49% and 82% reported each barrier as “somewhat” of a problem or a “major” problem. Using PCA, 3 main categories of barriers were identified. Having a high proportion of patients with SUD was associated with greater difficulties in accessing resources (P < .01) and data integration issues (P < .05), and working for specific MCOs was associated with all 3 categories of barriers (P < .05). Job satisfaction and burnout were correlated with all 3 categories as well and were most strongly associated with administrative and regulatory burden.

Conclusions: Care coordinators face multiple challenges serving Medicaid members, particularly those with SUD. State-level Medicaid policies supporting care coordinators may help.

Am J Manag Care. 2025;31(6):In Press

Takeaway Points

• Medicaid managed care organization care coordinators face frequent barriers to performing their jobs.
• These barriers to job performance fall into 3 main areas: accessing medical and social resources for Medicaid members, managing a large caseload within changing regulatory environments, and obtaining needed data to track and follow members.
• Care coordinators with a greater proportion of their caseload having a substance use disorder were more likely to report barriers to job performance; increased resources may be needed to better serve this population.
• Differences in reports of barriers by managed care organizations suggest that there may be opportunities for managed care organizations to learn from each other.

Nationally, in 2020, 46.3 million people reported having a substance use disorder (SUD),1 and Medicaid is the largest payer of SUD treatment.2 To serve these members, many state Medicaid programs use managed care: Across 41 states with Medicaid managed care, 72% of members are enrolled in managed care organizations (MCOs); these members are frequently served by care coordinators. MCO care coordinators link patients with services and resources to address medical and social needs.3-5 This is particularly important for members with SUD, who often have high rates of emergency department (ED) visits, hospitalizations, and health-related social needs.6-10 Care coordinators may perform multiple roles for members with SUD, encouraging treatment retention through continued engagement, addressing barriers to treatment, and facilitating transitions through different levels and types of care,3 as well as helping build members’ personal, family/social, and community recovery capital.

Virginia has embraced managed care; its Medicaid agency contracts with 6 MCOs, where care coordinators are responsible for managing their members’ medical and behavioral health needs, including in Virginia’s Section 1115 waiver for SUD, the Addiction and Recovery Treatment Services (ARTS) program. ARTS aligns Virginia’s delivery of addiction services with the American Society of Addiction Medicine’s continuum of care, allowing for payment of residential treatment, increasing access to medication for SUD, increasing reimbursement rates for addiction services, covering peer support services, and carving in behavioral health.11,12 These ARTS care coordinators are licensed mental health professionals with at least 2 years of experience working with patients with SUD and are charged with assisting in transitions between levels of care and providers and ensuring that multiple data sources, including utilization data and health risk assessments, are incorporated in care planning.13,14

Previous studies of care coordinators in different settings have shown that they face multiple challenges in performing their jobs, including a large caseload, difficulty finding community resources, and a lack of communication among data systems.7,15-17 Importantly, some of these challenges, such as high administrative burden and low-level administrative tasks, have been shown to be associated with burnout.18 In the context of Medicaid managed care for SUD, previous studies have suggested that prior authorization for SUD treatment and network adequacy may be challenges.19-21 However, there is currently limited evidence documenting the perceptions among Medicaid care coordinators of these potential challenges when working with patients with SUD nor how they contribute to their job satisfaction. Further, little is known about the factors associated with these challenges. Such information is vital to strengthen the nonclinical workforce to ensure patients with SUD fully benefit from treatment as states expand both their use of managed care in Medicaid and Section 1115 waiver programs.

To better understand the challenges faced by these Medicaid managed care coordinators in Virginia’s ARTS program, we adapted the Agency for Healthcare Research and Quality (AHRQ) Care Coordination Organizational Design Model (Figure 1).22 This model posits that the clinical setting and patients drive the need for care coordination. Whether these needs are effectively met is determined by coordinating capacity, which in turn is shaped by the tools and resources available to care coordinators; when coordinating needs match coordinating capacity, there is a “good fit,” and effective care can be delivered. We used the model to examine whether there are specific types of barriers faced by ARTS care coordinators serving patients with SUD that may prevent a good fit. We then proposed a categorization scheme for these barriers and explored the patient, care coordinator, and MCO factors associated with each of these categories of barriers. Lastly, we looked at the relationship between these barriers and care coordinator job satisfaction and burnout.

METHODS

Data Source

Data were gathered from a web-based survey of Virginia Medicaid care coordinators. As a federally required evaluation, this research was considered exempt by the Virginia Commonwealth University Institutional Review Board (HM20008646). Lists of care coordinators and their contact information were obtained from each of the 6 MCOs and included the universe of care coordinators employed by the MCOs (N = 1318). Care coordinators were sent the survey via email and received up to 3 follow-up reminders after approximately 30 days if they did not respond. Data collection occurred from April to July 2022. We received 322 completed surveys for a response rate of 24%.

Variables of Interest

We queried coordinators about their demographics and other characteristics, including age, gender, race, ethnicity, educational background, and number of years of care coordinating experience, both in general and with Medicaid members specifically. We also asked care coordinators about their caseload, including the number of members they serve, changes in their caseload over the past year, the needs of those members, and their engagement with those members; additional details are in the eAppendix (available at ajmc.com).

Based on discussions with Virginia’s Medicaid agency and prior qualitative interviews with care coordinators,23 we asked coordinators about 15 barriers to performing their role as care coordinators serving Medicaid members (listed in Figure 2 and the eAppendix). Coordinators were also asked about the tools they used to do their jobs and how useful they found them; these responses were dichotomized as “do not use tool” and “use tool: not helpful” vs “use tool: somewhat helpful” and “use tool: very helpful” (eAppendix Figure).

Care coordinators were asked to rate how much they “feel worthwhile at work,” agree that “my work is meaningful,” and “feel in control when dealing with difficult problems or people at work,” as well as to report the frequency of burnout. Additional information is provided in the eAppendix.

Analytical Methods

Descriptive statistics. Characteristics of care coordinators, barriers faced, and tools used were summarized using counts and frequencies. Due to the skewed nature of the data for care coordinator patient caseload characteristics, both in terms of the overall number of patients and the percentage of patients with specific characteristics, these characteristics were summarized using medians and IQRs. Individual items assessing care coordinator satisfaction and burnout were summarized using means and SDs; complete frequency distributions of these items can be found in the eAppendix.

Creation of subscales. To help better understand the patterns of barriers, we used principal component analysis (PCA) to identify categories of barriers, reduce the dimensionality of the data, and increase interpretability.24 We used the factor loadings from PCA as the basis for subscale development. Subscales with scores ranging from 1 to 3 were then created by taking the mean of all items for each subscale, with higher scores indicating greater difficulty. Additional details are in the eAppendix.

Regression and correlation analysis. To understand the factors associated with greater difficulty in performing care coordinator activities, we used multivariable linear regression. Based on the AHRQ model, we included variables to measure coordinating capacity and coordinating mechanism (years of experience as a care coordinator for Medicaid members, training, caseload, change in caseload, and use of tools) as well as setting, patients, and coordinating needs (proportion of members with SUDs; having a high level of members with medical needs, need for long-term services and supports [LTSS], need for assistance with activities of daily living [ADLs], and intellectual and developmental disability; and MCO). Additional information on variable selection is in the eAppendix. For individual items, missingness ranged between 0.3% and 8.9%, so we used multiple imputation with chained equations (SAS’ PROC MI) for missing independent variables for all analyses. To understand the relationship between the severity of barriers and job satisfaction and burnout, we used bivariate correlations. All analyses were completed in SAS 9.4 (SAS Institute Inc) and used an α of .05.

RESULTS

Care Coordinators and Whom They Serve

We received 329 completed surveys; 7 respondents did not provide outcome information for our outcomes of interest and were excluded, yielding a final analytical sample of 322. Most respondents were women, with a majority being non-Hispanic White and having training as a licensed health care professional and a bachelor’s degree or higher in human services or a related field (Table 1). Most care coordinators had 5 or more years of care coordinating experience, with 3 to 5 years with Medicaid. Respondents reported a median caseload of 144 members, with almost two-thirds reporting an increase in caseload over the past year. Care coordinators reported that most of their members had physical health problems and needed assistance with ADLs/LTSS. A median (IQR) of 24% (10%-50%) of their caseload members had an SUD. Care coordinators used a range of tools to help manage their caseload, finding ED/hospitalization data and health risk assessments to be the most used and most helpful (eAppendix Figure); care coordinators reported frequent use of telehealth tools (eAppendix Table 1).

Barriers Faced by Care Coordinators

Between 49% and 82% of care coordinators reported each of the individual barriers as a “major problem” or “somewhat of a problem” (Figure 2). For 8 of 15 individual barriers, problems were widespread, with more than three-fourths reporting facing problems with the specific barrier. To better understand patterns of barriers, we used PCA for categorization. We identified 3 main categories of barriers: (1) challenges accessing resources (finding in-network providers for mental health, SUD, physical health, LTSS; delays accessing treatment facilities and MCO authorization; resources for social services), (2) administrative and regulatory burden (paperwork, size of caseload, changes in COVID-19 and other regulations), and (3) data integration problems (data systems within and between MCOs, member data accuracy, data links to social services) (eAppendix Table 3). Means for all 3 scales were similar, ranging from 2.07 to 2.11, corresponding to slightly worse than “somewhat of a problem.”

Factors Associated With Barriers and Association Between Barriers and Job Satisfaction

We used multivariable linear regression to assess specific factors associated with barriers (Table 2). Specific MCOs were associated with all 3 scales: challenges accessing resources, administrative and regulatory burden, and data integration problems. Having more patients with SUD was associated with greater barriers in challenges accessing resources and data integration problems. Both a substantial increase in caseload in the past year and a high proportion of members who need help with ADLs were associated with care coordinators having higher administrative burden scores. Care coordinators experiencing greater difficulties with data integration problems tended to be more experienced. The use of specific tools and their association with specific scales was limited, with 3 exceptions: The use of Medicaid discontinuation data was associated with less difficulty with administrative burden and data integration problems, and the use of ED care coordination was associated with greater challenges accessing resources.

Care coordinators reported high job satisfaction and low burnout (eAppendix Table 3). Higher scores on all 3 subscales of barriers were negatively correlated with job satisfaction and burnout (r ranging from –0.25 to –0.55) (Table 3). Specifically, burnout had the strongest correlation with all 3 scales (challenges accessing resources, –0.36; administrative and regulatory burden, –0.55; data integration problems, –0.36). Administrative and regulatory burden was the most strongly correlated with 3 of 4 individual items, except “My work is meaningful,” which was most correlated with the data integration problems subscale (r = –0.36).

DISCUSSION

To understand the challenges faced by Medicaid MCOs’ care coordinators serving patients with SUD, we conducted a survey of these care coordinators. To the best of our knowledge, this is the first study comprehensively examining the specific barriers experienced by MCO care coordinators, guided by the AHRQ framework. To understand patterns of barriers, we used PCA, finding 3 broad categories of barriers faced by care coordinators: (1) challenges connecting patients with social and health resources, (2) administrative and regulatory burden, and (3) data system–related issues. Having a higher proportion of patients with SUD was associated with 2 of 3 categories of barriers (challenges accessing resources and data integration problems); employment by specific MCOs was associated with all 3 categories. Greater barriers were associated with burnout, demonstrating the need for further resources and regulations to support care coordinators in overseeing Medicaid MCO services.

Our finding of difficulty in connecting patients to health and social resources is consistent with the existing body of literature on care coordination across multiple patient populations, including those with SUD or acute social needs, and across diverse health care settings.7,15,16 Although prior work highlights the importance of connecting individuals to community resources to address social needs, these studies also noted that these resources are often limited; care coordinators cannot refer individuals to services that are not present in the community.7,15,16 Similarly, adequate MCO networks are needed for referrals to physical and behavioral health providers as well as SUD treatment.25,26 We specifically found that care coordinators with a greater proportion of their caseload having SUD faced greater challenges in this area. This likely reflects the need for not just SUD-specific treatment but also the higher level of behavioral health, physical health, and social needs of members with SUD, as well as a reluctance on the part of some providers to work with patients with SUD.27 Additionally, although Medicaid expansion and Section 1115 SUD waivers such as ARTS have substantially increased access to treatment, challenges remain.28

Importantly, particular MCOs were associated with greater challenges in connecting patients with resources to address both medical and health-related social needs. However, the study did not examine the specific cause of the variation across MCOs, representing a crucial potential policy lever. Some MCOs may be investing more in connections with community resources and have larger networks for SUD, behavioral health, and physical health treatment. Contractual requirements at the state level to help foster connections to community resources and newly developed CMS standards for Medicaid MCOs to ensure network adequacy may help address these problems.26,29 Such policy-based solutions may be implemented on a broader scale through Section 1115 waivers such as that in Massachusetts, which mandates cooperation between community organizations and accountable care organizations for patients with behavioral health and LTSS needs.30

In line with our work, prior studies have shown that a high caseload and paperwork burden are challenges faced by care coordinators. A previous study of care coordinators in primary care found that several coordinators managed more than 300 patients and that the size of the caseload was challenging.16 Additionally, care coordinators in that study noted that particularly “time-consuming patients” can create additional work. Similarly, we found that a higher caseload of individuals in need of LTSS was associated with experiencing more administrative burden, which may suggest that it is not only the size of the caseload but also the specific types of needs that may be challenging. Many of those with LTSS needs are dually eligible for Medicare and Medicaid, and Virginia has a mature managed LTSS program with greater contractual requirements for care coordination for this group than other states.31 Not surprisingly, we found that an increase in caseload was associated with greater concerns over administrative burden. Care coordinator ability to engage with a growing caseload, including via telehealth, may add to this burden. Interestingly, MCO was associated with administrative burden, which may suggest that some MCOs are better able to balance the size and complexity of caseloads or that administrative burden differs by MCO.

Similarly, issues related to data access are a recurring theme in the literature, with suboptimal data systems and lack of interoperability reported as major barriers to care coordination.16,17 Even when there are systems in place to ensure the transmission of needed information, such as discharge summaries, information may be duplicative or inefficiently organized.32 Although past work has pointed to the limitations experienced by care coordinators in accessing ED, hospitalization, and electronic health record data,33 care coordinators in our study reported high rates of using these tools, perhaps reflecting the impact of information sharing requirements in the 21st Century Cures Act, such as event notifications for hospitalizations.34,35 Instead, our results show problems specific to Medicaid managed care: accuracy of information collected by the state agency that is on file and information sharing when members switch MCOs. Prior work highlights challenges such as the difficulty in maintaining current information such as hours of operation, as well as identifying electronic systems that communicate between the health system and community resources, which care coordinators cited as a major issue in our study.16,17 Such issues might be alleviated by the care management platforms that allow both health care providers (including MCOs) and community organizations to document efforts and would provide information when members change MCOs.36 Last, the association between data integration problems and care coordinators having a greater proportion of members with SUD may reflect limitations due to confidentiality restrictions on SUD treatment with Title 42 of the Code of Federal Regulations; although recent Substance Abuse and Mental Health Services Administration amendments have sought to ease these restrictions, further reform may be necessary.27,28

Although care coordinators reported high job satisfaction and low burnout, we found that both lower levels of job satisfaction and higher levels of burnout were correlated with higher levels of administrative burden and problems with data integration. This mirrors prior qualitative and survey work showing that both insufficient organizational support and low-level administrative tasks were associated with burnout.18 Future work is needed to better understand the relationship between specific barriers and job satisfaction and burnout.

Limitations

First, this study is cross-sectional, and we are unable to draw any causal inferences. Second, our findings are based on only the ARTS program in Virginia Medicaid and may not be generalizable. Third, although our study focused on the experiences of care coordinators working with patients with SUD, the majority of the caseload and time spent on care coordination were for patients with LTSS needs, which may have influenced their responses and perceptions. Fourth, the overall response rate for this survey was only 24% and respondents may not be representative of all care coordinators working with Medicaid populations.

CONCLUSIONS

This unique survey provides insights into the challenges of providing SUD services to Medicaid populations from the perspective of those employed by MCOs to assist members in accessing these services. We identified a high prevalence of barriers in 3 distinct areas: resource access, data integration problems, and administrative burden. We found that specific barriers were associated with particular MCOs and having a greater proportion of patients with SUD and that higher reported barriers were associated with both burnout and decreased job satisfaction. Our work suggests the need for further policy and regulatory changes aimed at supporting Medicaid care coordinators who serve patients with SUD, such as improved access to social and medical resources and greater data integration.

Author Affiliations: Department of Health Policy (SJM, VV, HS, AJB, PJC) and Medical Scientist Training Program (SJM, DZ, HS), Virginia Commonwealth University, Richmond, VA; Virginia Department of Medical Assistance Services (AH, JL, AM), Richmond, VA.

Source of Funding: Ms Marks was supported by National Institutes of Health (NIH)/National Institute on Minority Health and Health Disparities (NIMHD) award F30MD019536. Dr Shadowen was supported by NIMHD award F30MD018324. Financial support for this work was provided by CMS and the Virginia Department of Medical Assistance Services (IAG No. 407, Appendix K) as part of the Addiction and Recovery Treatment Services 1115 waiver evaluation, the Substance Use Prevention that Promotes Opioid Recovery and Treatment for Members and Communities (SUPPORT) Act: Section 1003 Demonstration Project to Increase Substance Use Provider Capacity. The content is solely the responsibility of the authors and does not necessarily represent the official views or the endorsement of the Virginia Department of Medical Assistance Services or the NIH.

Author Disclosures: Ms Marks was supported by NIH/NIMHD award F30MD019536. Dr Shadowen was supported by NIH/NIMHD award F30MD018324. Ms Harrell, Mr Lowe, and Dr Mitchell are employed by the Virginia Department of Medical Assistance Services, which administers the program described in this article. 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 (SJM, VV, AH, JL, PJC); acquisition of data (AH, PJC); analysis and interpretation of data (SJM, VV, DZ, HS, JL, AM, PJC); drafting of the manuscript (SJM, VV, DZ, HS); critical revision of the manuscript for important intellectual content (SJM, VV, DZ, HS, AH, JL, AM, AJB, PJC); statistical analysis (SJM, PJC); provision of patients or study materials (AH, PJC); obtaining funding (AJB, PJC); administrative, technical, or logistic support (AH, AM, AJB); and supervision (AJB, PJC).

Address Correspondence to: Sarah J. Marks, MS, Virginia Commonwealth University, 830 E Main St, Richmond, VA 23219. Email: markss2@vcu.edu.

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