The person-month demographic and clinical characteristics of the CCO-enrolled intervention sample (n=154,324 person-months) and ACC-assigned comparator sample (n=40,510) at baseline are presented in Table 1. The comparator sample included more person-months from older, Medicaid/Medicare dual eligible beneficiaries than the intervention sample (Table 1). In the pre-period the intervention and comparator groups had similar person-month risk of ED visits (22.7% vs. 20.2%) and inpatient hospitalizations (9.9% vs. 9.0%). Characteristics of the intervention and comparator samples stratified by Medicaid program type are presented in Supplemental Table 1, available online.

Among SSI Medicaid beneficiaries, we observed a larger projected decrease in ED visit risk among the intervention sample versus the comparator sample at 12 months post enrollment (Table 2, DID: −6.6%; 95% confidence interval: −11.2%, −2.1%). As shown in Figure 1, changes in both the level (−3.7%, p=0.016) and slope (−0.3%, p=0.02) for ED visits were significantly different for the intervention sample versus the comparator sample. We did not find a difference in hospitalization risk between the intervention and comparator samples of SSI Medicaid beneficiaries.

Among Medicaid expansion beneficiaries, we observed a greater decrease in hospitalization risk among the intervention sample versus the comparator sample at 12 months post enrollment (Table 2, DID: −5.8%; 95% confidence interval: −11.4%, −0.2%). As shown in Figure 2, while differences in the level change did not reach significance (−3.1%, p=0.14), there was a significant difference in the slope change for hospitalizations (−0.2, p=0.03).

We did not observe differences for the other tested comparisons at 12 months post enrollment, including no significant difference in the change of either ED visits or hospitalization for TANF beneficiaries (Figure 1) and Medicare/Medicaid dual beneficiaries. For Medicare/Medicaid duals (Figure 2), gradual monthly declines in ED visit and hospitalization risk were about half a percentage point more per month for CCO enrollees than for comparators (ED: DID slope=−0.52%, p=0.032; hospitalization: DID slope=−0.48%, p=0.027). In our sensitivity analyses limited to beneficiaries with at least one month of data in the pre-period and one month of data in the post-period, we found similar effect magnitudes for the Medicaid SSI, expansion, and Medicare/Medicaid samples to the main analysis. Analyses among TANF enrollees were limited by low sample size. The results of our other two sensitivity analyses were consistent with the overall pattern of results, with the majority showing no statistically significant differences in outcomes between the intervention and comparison populations.

In an evaluation of a care coordination organization (CCO) intervention for high-cost, high-need Medicaid beneficiaries with diabetes, at 12 months post-enrollment we found no evidence of reduced utilization with the CCO program in six of eight comparisons. However, we observed larger reductions in the ED visit risk for beneficiaries receiving Medicaid through the SSI program and in the hospitalization risk for Medicaid expansion enrollees relative to comparators receiving a less-intensive, practice-level intervention. Strengths of this analysis include a multi-state sample with comprehensive administrative data to measure utilization outcomes, as well as a rigorous, quasi-experimental difference-in-difference design with a comparison group selected to minimize selection bias.

While they need to be replicated in other datasets, our limited findings of decreased ED utilization for Medicaid SSI beneficiaries with diabetes and fewer hospitalizations for high-cost, high-need Medicaid expansion beneficiaries indicate potential benefits of care coordination interventions for these subgroups. To qualify for SSI without Medicare, adults must demonstrate that they have an impairment preventing them from performing “substantial gainful activity” for at least one year.²⁶ These patients may have a higher burden of behavioral and social health needs than other Medicaid beneficiaries, and often receive care in a poorly coordinated network of emergency departments, hospitals, psychiatric inpatient facilities, community clinics, jails and substance abuse clinics.²⁷ Analyses of high-cost, high-need Medicaid expansion beneficiaries demonstrate similar complex needs and cross-sector service use.²⁸ The CCO intervention may have helped provide these beneficiaries with a new, single point of initial contact with the health system. There are few studies of care coordination among high-cost, high-need Medicaid expansion beneficiaries. However, an intention-to-treat analysis of an intensive care management program among Medicaid SSI beneficiaries in Washington State found no overall effects on either ED or hospital utilization at 24-month follow-up. The investigators did identify an increase in outpatient mental health service use and prescription drug costs, outcomes not measured in the current analysis.²⁹

As above, it should be noted that there was no strong, consistent pattern of evidence across all outcomes and populations that the CCO program significantly reduced high-cost healthcare events. Our results suggest that identification and enrollment of high-cost, high-need Medicaid beneficiaries into a care coordination program may not always be sufficient to result in change in ED and hospital utilization. We used a conservative study design with a comparator group who received an active although weaker practice-level intervention, and additional follow-up time may be required to assess the full effects of this type of comprehensive program. In fact, interventions based on addressing social needs may potentially increase acute care utilization and costs if supports are difficult to access elsewhere, since any weak link in the continuum of community-partnership building, resource referral, and follow-up may drive patients back to existing patterns of interaction with the larger system. As of yet, there is little consensus on the factors that make social needs interventions more likely to be broadly successful, sustainable, and scalable.^15,30

We believe that a future “per-protocol” analysis, evaluating the impact on Medicaid beneficiaries who received the complete CCO intervention as intended, will be an important complementary assessment to the results reported here. Such an analysis will help distinguish between issues of low uptake versus modest intervention effect size, might highlight more or less effective program components for cost savings, and may help quantify the potential impact of the intervention if recruitment and retention efforts are increased.¹³ In addition, future studies examining patient perspectives on this intervention will be invaluable, since evidence suggests that high-need, high-cost patients who perceive higher levels of trust and respect from CHWs and other team members may be more engaged in changing behavior patterns.^15,31-33

An overall limitation of the published literature evaluating interventions that target social determinants is an inability to distinguish between different categories of unmet need. For example, it is unclear whether connecting high-cost, high-need patients with housing supports, food insecurity or income support would be expected to result in similar effects. Since measured of unmet social need such as unstable housing, lack of access to nutritious food and inability to afford basic costs of living are not captured in claims data, it has been challenging to study subgroups of patients who fall into these categories. To address this issue, a working group including UnitedHealthcare and the American Medical Association proposed an additional 23 specific ICD-codes to the Centers for Medicare and Medicaid Services (CMS) to record different categories of unmet need, which are currently released for public comment.³⁴ If these codes are approved for use in Medicaid and Medicare, they will be enacted in fall 2020.

Our analysis has several limitations. First, since issues of unmet social need have accumulated over many years and can be slow to change, longer-term follow-up may be required to identify effects of care coordination interventions such as this one. Second, we did not match our samples for baseline utilization, and there may have been unmeasured differences between the intervention and comparison populations. However, the interrupted time series approach allows the intervention and comparison groups to have different intercepts and slopes in the pre period, so the estimated intervention effects should be consistent as long as the changes in intercepts and slopes from the pre-period to the post-period would have been the same for both groups in the absence of the intervention.³⁵ Finally, while the CCO intervention targeting high-cost, high-need beneficiaries was more intensive than the practice-level ACC intervention from which our comparison Medicaid beneficiaries were drawn, the latter group still may have received additional intervention services, leading to a null result.

In conclusion, we found that an evaluation of a national care coordination program designed by UnitedHealthcare to reduce utilization among high-cost, high-need Medicaid beneficiaries with diabetes was associated with decreased rates of ED visits and hospitalizations for some Medicaid programs but not others. Our findings are consistent with prior results from well-designed studies in this area. Given the oversized contribution of unmet social need and social determinants on health outcomes, finding effective and scalable approaches to address medical, behavioral, as well as social issues is essential in order to improve the performance of the healthcare system in the United States, particularly for high-cost, high-need patients.³⁶