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Assessing the Impact of an Integrated Care System on the Healthcare Expenditures of Children With Special Healthcare Needs

Mircea I. Marcu, PhD; Caprice A. Knapp, PhD; David Brown, PhD; Vanessa L. Madden, BSc; and Hua Wang, MS
This study analyzes the effect of a managed care program on Medicaid expenditures for children with special healthcare needs using a quasi-experimental design.
We found that the average annual outpatient costs and total costs have decreased as a result of the implementation of the ICS in Duval County by approximately $1008 and $2340 per CMSN enrollee, respectively. Outpatient, inpatient, pharmacy, and total costs were also lower in Broward County after the implementation of the ICS, but the cost decreases were not statistically significant. ED costs increased slightly, though not significantly. The findings of our analysis suggest that managed care programs such as the ICS have the potential to reduce healthcare costs for this high-risk group of CSHCN.

These findings are complemented by previous findings that the ICS pilot program did not reduce the satisfaction and quality of care for CSHCN, as perceived by the children’s parents.6 Further, there is evidence that the utilization of inpatient and outpatient services decreased for CSHSN.12 These findings suggest that the ICS pilot program has the potential to reduce healthcare costs without changing the patient’s experience. Although we cannot definitively comment on why the cost reductions occurred, we speculate that this could be due to: a) a reduction in the utilization of services, and b) that processing a large volume of claims in a more efficient manner makes it easier to identify billing- and procedural-based inconsistencies.

By estimating alternative models of healthcare costs, this study also contributes to the literature evaluating the performance of different classes of models used to estimate expenditures data.15,22 We found that the GLMs performed the best in our sample of CSHCN; this likely arises because CSHCN are a population with high healthcare costs, which increases the importance of modeling the variance in a flexible way. This supports prior findings that the GLMs outperform other methods when analyzing skewed cost data.22 In addition, because the GLMs are not biased by heteroskedasticity, like other methods, we provide further evidence that the GLM estimators are the best-performing methodology when faced with skewed cost data.

Finally, this study adds to the growing literature on Florida’s 2006 Medicaid reform.8,23-29 In particular, 2 studies examine the impact of Florida’s Medicaid reform on healthcare expenditures of the entire Medicaid population. One study found that Florida’s Medicaid reforms did not result in a statistically significant reduction in costs.29 However, the authors do note that cost reductions may have been achieved for subpopulations with higher healthcare needs— precisely what our study suggests. Another study uses a quasi-experimental design similar to the one used in the current study, and the authors find statistically significant cost reductions that can be attributed to a reduction in the number of nonemergency visits and in average cost per hospital visit.8

A key assumption in any DID analysis is that the trends in healthcare costs pre-treatment across the treatment and control counties are similar. Due to data limitations, we are unable to directly test this for our subsample of Medicaid enrollees. However, a related study, which analyzed the same treatment and control counties during our period of study, illustrates that the common trends assumption is satisfied when analyzing the healthcare costs of all Medicaid enrollees in Florida.8 This finding, coupled with the findings in Table 1 that a wide array of pre-treatment characteristics of the CSHCN are not statistically different across our treatment and control counties, helps defend the common trends assumption in our analysis.

Limitations

Several limitations to this study merit attention. First, we used the CRGs to control for the children’s health status in our models. About one-fifth of the CSHCN were unassigned, meaning that there were not enough claims data to assign them to a health status category, mostly due to gaps in enrollment. Second, we lack information on several explanatory variables of interest, such as household income and parents’ education, which could be linked to the healthcare costs of CSHCN. Third, we are unable to provide any information regarding the impact of the ICS program on access to healthcare service for CSHCN or on outcomes. Although we can state that outpatient costs decreased, for example, we do not know if that decrease results in better, worse, or the same outcomes for the patient. Fourth, the full impact of a managed care program on CSHCN may take several years to be realized. Our study considers a relatively short time horizon.

Despite these limitations, our study is among a limited amount of literature that describes the effects of a managed care program on the healthcare costs of CSHCN. In addition, our study findings contribute to several areas of the CSHCN literature, including Medicaid managed care, carved-out healthcare systems, and Medicaid reform. The findings in this study are timely, as Florida has adopted a statewide managed care system in 2014.30 Many other states are now moving toward a higher degree of managed care penetration, and they can look to Florida as an example of what might be possible for this high-cost group.

CONCLUSIONS
We used a quasi-experimental DID research design to assess the impact that a managed care program aimed at CSHCN has on healthcare expenditures. We found that the program decreased outpatient, inpatient, pharmacy, and total costs for this high-cost group of children. This paper contributes to the limited research that analyzes the impact of managed care programs on healthcare expenditures. These findings suggest that managed care programs such as the ICS have the potential to reduce healthcare expenditures for CSHCNs. Future research should determine the long-term impacts of ICS implementation on healthcare costs, quality, and access to care, and if these impacts are sustainable. This information is crucial to determining if other states should consider adopting this model of care for CSHCN. 

Author Affiliations: Department of Epidemiology and Health Policy Research (MIM, VLM, HW), and the Institute for Child Health Policy (MIM, VLM, HW), University of Florida (HW), Gainesville, FL; Department of Health Policy and Administration, Pennsylvania State University (CAK), University Park, PA; Department of Economics, University of Alberta (DB), Edmonton, Canada.

Source of Funding: None.

Author Disclosures: The 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 (MIM, CAK, DB, VLM); acquisition of data (MIM, CAK, VLM, HW); analysis and interpretation of data (MIM, DB, HW); drafting of the manuscript (MIM, CAK, DB); critical revision of the manuscript for important intellectual content (CAK, DB); statistical analysis (MIM, DB); administrative, technical, or logistic support (VLM, HW); and supervision (CAK).

Address correspondence to: David Brown, PhD, Department of Economics, 8-14 HM Tory Building, University of Alberta, Edmonton, AB, Canada T6G 2H4. E-mail: dpbrown@ualberta.ca.
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