State Data Spotlight: Rhode Island Health Indicators
This State Data Spotlight describes Rhode Island's Health Indicator System for Medicaid enrollees. The Rhode Island Medicaid Research and Evaluation Project uses existing public health data, Medicaid administrative data and state-level survey data to actively inform program activities and evaluation.
The Health Indicator System was established by the state in 1999 to monitor and evaluate health services within the Medicaid program, and also to provide a useful framework for data collection for all Rhode Islanders. They system helps policymakers identify how specific Medicaid interventions have impacted the health status of enrollees, and is used to inform future initiatives and interventions. January 2012
Webinar: FMAP and Income Conversion Methodology Study
In this webinar, experts from CMS, RAND, and SHADAC discuss the Federal Medical Assistance Percentages (FMAP) claiming and Modified Adjusted Gross Income (MAGI) income conversion methodologies that states will need to implement under the Affordable Care Act. These methodologies will be needed to determine who is newly eligible for Medicaid under the Affordable Care Act and who would have been eligible before the Affordable Care Act took effect, had they applied for coverage (i.e., the “previously-eligible”), and to enable states to convert their current financial eligibility standards for Medicaid to the new MAGI-based standards.
The US Department of Health and Human Services (HHS) has contracted with the RAND Corporation, SHADAC, and the National Conference of State Legislatures (NCSL) to evaluate and refine proposed methodologies for (1) identifying individuals newly versus previously eligible for Medicaid for purposes of FMAP claiming, and (2) converting current state Medicaid eligibility standards to the new MAGI-based standards. Once the methodologies have been finalized, SHADAC will be providing technical assistance to states to implement them.
Whatever methodology or methodologies are ultimately chosen must be accurate but also administratively practical so that undue burden is not placed on states. The goal of this webinar is to provide information about the approach of the feasibility study, and to solicit input on the study’s design in order to ensure that the expertise and concerns of state officials and other stakeholders inform the project.
Please send input on the methodologies and study design to jsonier@umn.edu by November 4, 2011.
States interested in study participation should contact Lisa Hiatt at hiatt@rand.org.
Modified Adjusted Gross Income: Implications for Medicaid Eligibility Systems under the ACA
This ACA Note discusses the implementation of the new income definition--Modified Adjusted Gross Income or "MAGI"--that will be used to determine Medicaid income eligibility across the country in 2014 when the Affordable Care Act (ACA) takes full effect. The implementation of MAGI is complicated by the requirement that each state distinguish between two different eligibility groups that will garner different federal medical assistance percentages (FMAPs)--the "newly-eligible" expansion population and the "previously-eligible" population that would have met the state's pre-ACA income thresholds. This report discusses the complexities that this scenario will raise for state Medicaid eligibility systems and how these issues might be addressed.
Counting Uninsurance and Means-Tested Coverage in the American Community Survey: A Comparison to the Current Population Survey
Objective. To compare health insurance coverage estimates from the American Community Survey (ACS) to the Current Population Survey (CPS-ASEC).
Data Sources/Study Setting. The 2008 ACS and CPS-ASEC, 2009.
Study Design. We compare age-specific national rates for all coverage types and state-level rates of uninsurance and means-tested coverage. We assess differences using t-tests and p-values, which are reported at <.05, <.01, and <.001. An F-test determines whether differences significantly varied by state.
Principal Findings. Despite substantial design differences, we find only modest differences in coverage estimates between the surveys. National direct purchase and state-level means-tested coverage levels for children show the largest differences.
Conclusions. We suggest that the ACS is well poised to become a useful tool to health services researchers and policy analysts, but that further study is needed to identify sources of error and to quantify its bias.
Summary of State-level Data and Information in Reports Released by MACPAC
SHADAC compiled this summary of state-level data and information released by MACPAC in the Medicaid and CHIP Program Statistics (MACStats) section of the March and June 2011 MACPAC reports to Congress.
This serves as a quick reference tool for state analysts and policymakers. The tables identified in this document provide state-level information about Medicaid/CHIP enrollment, spending, benefit levels, and managed care status.
The MACPAC reports to Congress on Medicaid and CHIP are available at this link.