CSHP Medicaid Portfolio

Answering the Call to Evaluate the Impact of ACOs

State legislation in 2011 (P.L. 2011, Chapter 114) created a pilot project to assess the efficacy of ACOs in enhancing Medicaid’s cost-effectiveness through reducing utilization of expensive, but avoidable hospital care while enhancing the quality of community-based services. To incentivize providers to participate in the ACO demonstration, the state offered opportunities to share in savings generated by the ACOs if they achieved quality care targets. 

The law sought to promote policy learning by understanding ACOs’ effectiveness in achieving quality and savings goals. Subsequently, state Medicaid officials approved three ACOs in Camden, Newark, and Trenton, and tapped CSHP for analytic expertise, given the methodological complexity involved in assessing the ACO pilot.

In 2012, CSHP recommended an approach to calculate ACO savings, with extensive consultation with state Medicaid officials. Analyses concluded that the three ACOs did not produce appreciable cost savings over the limited period of the demonstration, yet suggested that ACOs yielded benefits in meeting the health care needs of underserved populations. 

Among other things, ACOs served as conveners and connectors among diverse health and social service providers in their communities. To preserve these benefits, New Jersey Governor Phil Murphy signed a bill in January 2020 transitioning the three ACO pilots into formal Regional Health Hub (RHH) partnerships and adding a fourth RHH in Passaic County. Learn more about the health hubs here. 

New Jersey’s decision to provide CSHP with Medicaid data as well as CSHP’s ability to produce rigorous findings established important precedents that served as the bedrock for future work. This initial analytic collaboration required navigating inherently complex legal, data security, and privacy concerns, which often impede such analytic arrangements between state Medicaid agencies and external research organizations. 

CSHP’s access to New Jersey Medicaid data fortified an analytic partnership that has deepened since this first collaboration.

Articles & Presentations

• DeLia, D., & Yedidia, M. J. (2020). The Policy and Practice Legacy of the New Jersey Medicaid ACO Demonstration Project. Journal of Ambulatory Care Management, 43(1), 2–10.
• DeLia, D. (2017). Spending Carveouts Substantially Improve the Accuracy of Performance Measurement in Shared Savings Arrangements: Findings From Simulation Analysis of Medicaid ACOs. INQUIRY: The Journal of Health Care Organization, Provision, and Financing, 54.
• Cantor, J. "Achieving Better Care and Lower Costs in Health Care for Low-Income Populations." Public Health & Preventive Medicine Grand Rounds, Rutgers New Jersey Medical School, Newark, New Jersey, 2014.
• Chakravarty, S., Cantor, J., Tong, J. & DeLia, D. "Advancing New Jersey Safety Net ACOs: New Findings on Opportunities for Better Care and Lower Costs." State House Seminar, 2013.
• Cantor, J. "New Jersey Safety Net ACOs: New Findings on Opportunities for Better Care and Lower Costs." PICO New Jersey Conference, Promoting Good Care: Innovation and Organizing in Health Care, Newark, New Jersey, 2013.
• DeLia, D. "Statistical Risks in the Establishment of ACO Expenditure Savings." Seventh National Medicaid Congress, Arlington, Virginia, 2012.
• DeLia, D. "How Exactly Will Providers Be Held Accountable? Emerging Methods of ACO Performance Measurement." Corporate Research Group, Webinar, 2012.
• DeLia, D., Cantor, J. & Hoover, D. "Critical Issues in Performance Evaluation for Medicaid ACOs." Academy Health Annual Research Meeting, Seattle, Washington, 2011.

Reports

• DeLia, D., Kumar, R., Nova, J., Lloyd, K. & Goldin, D. (2018). "Spending and Utilization Indicators in the New Jersey Medicaid ACO Demonstration Project." Rutgers Center for State Health Policy.
• DeLia, D., Yedidia, M. & Lontok, O. (2018). "Update on ACO Operations and Care Management Strategies in the New Jersey Medicaid ACO Demonstration Project." Rutgers Center for State Health Policy.
• Cantor, J., Chakravarty, S., Tong, J., Yedidia, M., Lontok, O. & DeLia, D. (2014). "The New Jersey Medicaid ACO Demonstration Project: Seeking Opportunities for Better Care and Lower Costs among Complex Low-Income Patients." Rutgers Center for State Health Policy.
• Yedidia, M., Lonok, O. & Cantor, J. (2013). "Development of Medicaid Accountable Care Organizations (ACOs) in Three New Jersey Communities." Rutgers Center for State Health Policy.
• DeLia, D. & Cantor, J. (2012). "Recommended Approach for Calculating Savings in the NJ Medicaid ACO Demonstration Project." Rutgers Center for State Health Policy.

Tracking Results from the Transition to Managed LTSS

In the early 2000s, under then Center Co-Director and Research Professor Dr. Susan Reinhard, CSHP offered technical assistance to states that helped rebalance LTSS toward homes and communities. With the waiver demonstration, New Jersey policymakers launched a significant initiative to improve the state’s performance on this front.

In 2012, state Medicaid officials received federal approval of a demonstration waiver that, among other things, sought to transform Long Term Services and Supports (LTSS) delivery by moving it into managed care. LTSS involves assistance with daily living activities such as bathing and eating. The 2012 waiver demonstration aimed to advance the shift by assigning managed care organizations (MCOs) a key role in delivering LTSS. 

New Jersey turned to CSHP to meet the federal requirement that §1115 demonstrations undergo a formal, independent evaluation. CSHP issued several progress reports about the 2012-2017 demonstration and an overall assessment of the waiver’s impact. While these reports identified certain challenges, they also pointed to positive developments. Encouraged by these findings, the state obtained federal approval to renew the §1115 demonstration for two subsequent five-year periods, with CSHP again serving as program evaluator.

The number and proportion of LTSS recipients receiving care in homes and communities grew dramatically over the decade of the two demonstrations. Importantly, by 2019, over half of the state’s Medicaid LTSS beneficiaries received assistance in homes and communities rather than in nursing homes or other institutions. 

In addition to increasing access to HCBS, the MCO transition lowered per-person costs. By 2019, per person, inflation-adjusted spending on HCBS by MCOs declined by about 20% compared to prior costs. The evaluation did not find that waiver demonstrations impacted HCBS quality; rather, an examination of multiple indicators suggested that quality remained consistent.

While the transition of LTSS to MCOs was a major focus of CSHP’s waiver evaluation, the Center also assessed other waiver components. Notably, CSHP evaluated the Delivery System Reform Incentive Program (DSRIP) embedded in the initial waiver. DSRIP aimed to reward hospital-based networks that enhanced care access and improved quality and population health while lowering Medicaid costs. Evaluation found that DSRIP improved outcomes related to certain chronic health conditions, including hospitalization reductions and emergency department (ED) visits among those with asthma. 

Dissemination of CSHP evaluation findings about New Jersey’s DSRIP experience helped inform a national movement to implement hospital pay-for-performance initiatives to advance population health and health equity. CSHP found in surveys and interviews that while NJ DSRIP largely achieved its health improvement goals, stakeholders identified the need to cover short-term costs to maintain financial viability of DSRIP initiatives, particularly in safety net hospitals.

Long-term evaluation and learning through waiver demonstrations helped support New Jersey’s continuous aims of enhancing the accessibility, quality, and cost-effectiveness of care under its Medicaid program. In turn, this work has made CSHP appreciate the challenges in achieving these improvements and seek analyses to help identify paths toward progress. These evaluations also enhanced CSHP’s experience and capacity in drawing on large Medicaid data files to help contribute to the knowledge base on Medicaid innovation across the nation. 

Over the last decade, this has become a signature area of policy expertise for CSHP and a foundation of the Center’s effort to expand its data capacity to inform strategies to improve population health.

DSRIP-Related Articles

• Lloyd, K., Chakravarty, S., Brownlee, S., Farnham, J., & Cantor, J.  (2020). Hospital Responses to DSRIP Program Reforms in New Jersey. Population Health, Equity & Outcomes, 8(2), 4–12.
• Chakravarty, S., Lloyd, K., Farnham, J., & Brownlee, S. (2019). Medicaid DSRIP in New Jersey: Trade-offs between Broad Hospital Participation and Safety Net Viability. Journal of Health Politics, Policy and Law, 44(5), 789–806.

DSRIP-Related Reports

• Chakravarty, S., Lloyd, K., Pizzi, L.T., Palatucci, J.S., Prioli, K. M., Farnham, J., Nova, J., Liu, F. Y. & Nasiriahmadabadi, M. (2021). "A Final Evaluation of the New Jersey Delivery System Reform Incentive Payment (DSRIP) Program: Assessing Program Impact on Outcomes and Cost-Effectiveness." Rutgers Center for State Health Policy.
• Farnham, J., Lontok, O., Lloyd, K. & Chakravarty, S. (2020). "Evaluation of the New Jersey DSRIP Program:Findings from the Third Round of Stakeholder Interviews." Rutgers Center for State Health Policy.
• Chakravarty, S., Lloyd, K., Brownlee, S. & Farnham, J. (2018). "A Summative Evaluation of the New Jersey DSRIP Program: Findings from Stakeholder Interviews, Hospital Surveys, Medicaid Claims Data, and Reported Quality Metrics." Rutgers Center for State Health Policy.
• Chakravarty, S., Lloyd, K., Brownlee, S., Farnham, J. & Zhang, Katie (2015). "A Midpoint Evaluation of the New Jersey DSRIP Program: Findings from Stakeholder Interviews, Hospital Survey, Medicaid Claims Data, and Reported Quality Metrics." Rutgers Center for State Health Policy.

Improving Care for High Utilizers

In a 2014 budget address, then New Jersey Governor Christie noted that, in the prior year, 5% of Medicaid recipients accounted for 50% of its costs, calling out impacts of those with “chronic emergency room visits,” “complex medical conditions,” and repeat inpatient stays on New Jersey’s health care spending. The Governor then tasked Rutgers “to expand the scope” of its research to help “innovate and improve” care for Medicaid patients with high utilization inside New Jersey.  

I am calling on New Jersey’s most important medical and research institutions -- Rutgers Biomedical and Health Sciences, University Hospital, and Rutgers Camden, to join with our Medicaid managed care organizations to help us devise a program to innovate and improve health care delivery under Medicaid and Family Care.

Chris Christie

Governor of New Jersey

In response to this request, Rutgers convened a Working Group on Medicaid High Utilizers, which analyzed Medicaid data and convened stakeholders to develop recommendations for policymakers grappling with how to improve care for these patients. CSHP confirmed that small groups accounted for large shares Medicaid’s $9.4 billion spending in 2013, with the top 1% of spenders having 20 times the rate of avoidable hospitalizations than the bottom 90%, and the top 10% of spenders accounting for 75% of all spending. Read the Working Group's full report here.

Moreover, looking over time, CSHP found “persistence” in highspend among this population, with high rates of overall inpatient admissions, including avoidable hospitalizations and readmissions. Those within the top 1% were more likely to have a disability, be near the end of life, or receive Long-Term Services and Supports. A striking 85% of these patients had a mental health or substance abuse diagnosis. These findings set the table for additional CSHP work focused on improving care for New Jersey’s at-risk populations.

Monitoring Trends in Cancer Screening

New Jersey has the tenth-highest rate of cancer incidence rate in the United States. The second leading cause of death in New Jersey, thousands of residents die from preventable cancers each year. NJ FamilyCare provides coverage for cancer prevention services and screenings to thousands of beneficiaries throughout the state. However, the New Jersey Department of Human Services estimates nearly 1 in 5 Medicaid recipients could lose coverage under President Donald Trump’s 2025 tax cut and spending bill.

CSHP colleague Jennifer Tsui, PhD, MPH, then an Assistant Professor at Rutgers Cancer Institute of New Jersey and the Rutgers School of Public Health, worked with Rutgers Center for State Health Policy to examine screening patterns among Medicaid enrollees diagnosed with colorectal cancer. Subsequent studies would focus on screening patterns among the entire Medicaid population – not just for colorectal cancer, but for lung cancer as well.

Building on this work, CSHP Associate Research Professor Ann M. Nguyen led an analysis of Medicaid cancer screening trends in New Jersey, the most up-to-date at the time, as well as companion studies of best practices and key factors for facilitating cancer screenings, working closely with Anita Kinney, associate director for Population Science and Community Outreach at Rutgers Cancer Institute and director of ScreenNJ. Learn more in this Rutgers Today Q&A featuring Drs. Nguyen and Kinney.

Articles

• Tsui, J., DeLia, D., Nova, J. Rotter, D. Kulkarni, A., Demissie, K. Stroup, A.M. & Cantor, J.C. (2018). Primary Care Utilization, Late-Stage Diagnosis, and Timeliness of Treatment among Medicaid Cancer Patients: Early Signals following the ACA Expansion. Cancer Epidemiology, Biomarkers & Prevention, 27(7 Supplement), PR07.
• Tsui, J., DeLia, D., Stroup, A.M., Nova, J., Kulkarni, A. Ferrante, J.M. & Cantor, J.C. (2019). Association of Medicaid Enrollee Characteristics and Primary Care Utilization with Cancer Outcomes for the Period Spanning Medicaid Expansion in New Jersey. Cancer, 125(8), 1330–1340.
• McGee-Avila, JK., Doose, M., Nova, J., Kumar, R., Stroup, A.M. & Tsui, J. (2020). Patterns of HIV Testing among Women Diagnosed with Invasive Cervical Cancer in the New Jersey Medicaid Program. Cancer Causes & Control, 31(10), 931–941.
• Nguyen, A.M., Waldron Corredor, A., Liu, F. Y., Yun, X., Nova, J., Kinney, A.Y., Cantor, J.C. & Tsui, J. (2025). Breast, Cervical, and Colorectal Cancer Screening Among New Jersey Medicaid Enrollees: 2017-2022. JCO Clinical Cancer Informatics, 9.
• Waldron Corredor, A., Nguyen, A.M., Nova, J., Ma, Y., Cantor, J.C., Kinney, A.Y. & Tsui, J. (2025). Provider and Organizational Factors Impacting Routine Cancer Screening Among Older Medicaid Enrollees. Health Services Research, 61(2).
• Xie, J., Waldron Corredor, A., Yun, X., Nova, J., Kinney, A.Y., Tsui, J., Cantor, J.C. & Nguyen, A.M. (2026). Lung cancer screening among Medicaid older adults in New Jersey, 2017–2022. Preventive Medicine, 213, 108668.

Reports

• Tsui, J., Michael, M., Koller, M., Nova, J., Davis, S.N., Carey Perez de Alejo, E., Cantor, J.C. & Kinney, A.Y. (2021). Trends in Cancer Screening among Medicaid Enrollees in New Jersey: 2011–2017. Rutgers Center for State Health Policy.

Support for Development of the New Jersey Medicaid Office of Business Intelligence

The NJ Medicaid program established its Office of Business Intelligence to improve its capacity to conduct rapid analyses of importance for the development of innovations in Medicaid. To help accomplish this goal, the NJ Medicaid agency engaged CSHP to assist in the development, staffing, and operations of the Business Intelligence Unit. This assistance expands the current data analytic capabilities of Medicaid and enables it to rapidly identify and address emerging trends relevant to Medicaid beneficiaries and develop actionable intelligence on ways to improve quality of care and improve program efficiency within the NJ FamilyCare (Medicaid) population. 

CSHP is recruiting, training, and mentoring/supervising data analysts who are deployed to the Medicaid BIU. The Center is also providing research technical assistance to the Medicaid team. This project is funded by the NJ Division of Medical Assistance & Health Services. Learn more.