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Blog & News
Medicaid expansion and the Medicaid undercount in the American Community Survey (Health Services Research Article)
November 20, 2019:
Researchers at SHADAC have long been interested in the issue of “Medicaid undercount,” or the discrepancies that exist between survey estimates of enrollment in Medicaid and the number of enrollees that are actually reported in state and national administrative data—a pattern in which the former estimate is reported consistently lower than the latter. Studies on the subject have shown that nearly all surveys undercount Medicaid/CHIP relative to administrative sources, but the magnitude of the undercount range can vary broadly between major federal surveys (e.g., the American Community Survey, the Current Population Survey, the Medical Expenditure Panel Survey, etc.).
A new paper from researchers Michel Boudreaux (University of Maryland), Brett Fried (SHADAC), James Noon, and Joanna Pascale (U.S. Census Bureau), is the latest in a series of projects and publications that look at the differing enrollment measurements found between the American Community Survey (ACS) and the Medicaid and CHIP data provided by the Centers for Medicare and Medicaid Services (CMS) in order to gauge the degree of difference. In this latest article, the authors not only compare measurements from the survey with administrative data but also, in a first-of-its-kind study, cross-compare measurements between states that either did or did not adopt Medicaid expansion.
Federal surveys vs. administrative data
As noted in the article’s introduction, federal surveys have a multiplicity of useful features regarding data evaluation (e.g., broad population sources, timeliness, detail at a variety of geographic and demographic levels, availability, etc.). The ACS in particular, is an excellent source of such data, as it collects information from a large sample size (over 4 million people annually) representative of state and sub-state geographies, and the health insurance and income questions are asked with consistency.[1]
Additionally, the ACS is a notable exception to the undercounting of Medicaid/CHIP as Boudreaux and a team of researchers previously published in a paper on the 2009 ACS, which they found actually overcounted Medicaid/CHIP administrative records by 8 percent. One facet to the goals of this study was to measure the discrepancies between the ACS and administrative data over time (using data years 2010-2016) and investigate whether the 2009 ACS overcount has persisted.
The role of Medicaid expansion
Another facet was the possibility of discerning any patterns in discrepancies between ACS and Medicaid/CHIP enrollment data with regard to state decisions to adopt Medicaid expansion, or not. Higher undercounting as a result of Medicaid expansion could be possible, the authors theorized, for a number of reasons, including:
- Eligibility increase among populations less likely to report Medicaid coverage, such as adults and higher income individuals.
- Insurance marketplace portals that do not clarify exact source of coverage for individuals enrolling in Medicaid/CHIP.
- Lack of adequate specificity in source of coverage questions in the ACS.
Conclusions
Merging state and administrative data allowed the researchers to produce estimates for years 2013, 2014, 2015, and 2016 at a state level, which were then divided into several subgroups: All states, Nonexpansion states, Early expansion states, 2014 expansion states, and Late expansion states.
Results from each group varied, with years of both over- and undercount recorded, but overall showed a few consistent patterns. First, that among almost all groups (with the exception of “Nonexpansion states”) the ACS reversed course starting in 2013 and began to almost consistently undercount Medicaid/CHIP enrollment. And second, that the degree of discrepancy tended to increase each year from 2013 to 2016, though the degree of increase varied from group to group (lower for “All states” vs. higher for “Late expansion states”).
Overall, the authors concluded, Medicaid expansion did affect measurements from the ACS, with discrepancies between survey and administrative data increasing in years (and states) surrounding expansion. However, they did note that the degree of discrepancy in the ACS (7.9 percent) was much smaller when compared to other surveys (22.0 percent in the CPS and NHIS), suggesting that continual investments and revisions to survey systems, such as the recent redesign of the CPS, may continue to help reduce these discrepancies.
Read the full article for more detail on the data and methodology used in the paper, as well as discussion of the results and implications for surveys.
Related Reading
The Medicaid Undercount Project
Accuracy of Self-reported Health Insurance Coverage among Medicaid Enrollees
The Medicaid Undercount: Synthesis of Research
Uncovering the Missing Medicaid Cases and Assessing Their Bias for Estimates of the Uninsured
Notes
[1] See the annual “Comparing Federal Government Surveys that Count the Uninsured: 2019” brief for more details on features and differences of federal surveys and guidance on when to use data from each one.
Publication
Comparing Federal Government Surveys That Count the Uninsured: 2019
With the release of new insurance coverage estimates from surveys conducted by the U.S. Census Bureau, the Agency for Healthcare Research and Quality, and the Centers for Disease Control and Prevention, SHADAC recently updated our annual brief “Comparing Federal Government Surveys that Count the Uninsured.”
This brief provides an annual update to comparisons of uninsurance estimates from four federal surveys1:
- The American Community Survey (ACS)
- The Current Population Survey (CPS)
- The Medical Expenditure Panel Survey - Household Component (MEPS-HC)
- The National Health Interview Survey (NHIS)
In this brief, we present current and historical national estimates of uninsurance along with the most recent available state-level estimates from these surveys. We also discuss the main reasons for variation in the estimates across the different surveys.
Download a PDF of the Comparing Federal Government Surveys Brief.
Last year’s brief with data from 2017 can be accessed here.
1 Another federal survey that provides estimates of the uninsured is the Behavioral Risk Factor Surveillance System (BRFSS), which provides uninsurance estimates for the adult population 18 years and over nationally and among states.
Publication
2018 ACS Tables: State & County Uninsured Rates, with Comparison Year 2017
The interactive map on this page links to tables containing state and county uninsurance estimates for 2018. These estimates come from the 2018 American Community Survey (ACS) via the U.S. Census Bureau's data.census.gov tool.
Click on a state to see state and county uninsurance rates by characteristics (for example, age, race/ethnicity, and poverty level) for 2018 and comparison year 2017. Due to sample size constraints, single-year ACS estimates are available at the county level only for counties with a population greater than 65,000.
Click here to view uninsurance estimates for the United States.
Click here to view uninsurance estimates for Puerto Rico and its municipios.
Note: These tables present uninsured rates, which indicate the share of the population that is uninsured. For example, a 10 percent uninsured rate for adult women indicates that 10 percent of all adult women are uninsured.
Additional Estimates (50-State Comparisons)
Maps & Tables of Private, Public, & Uninsured Change from 2017 to 2018
Private Coverage Rates by State, Change from 2017 to 2018, for All People
Public Coverage Rates by State, Change from 2017 to 2018, for All People
Uninsurance Rates by State, Change from 2017 to 2018, for All People
About the ACS
The ACS is a household survey that began in 2005 and produces annually updated data on a variety of population characteristics, including health insurance coverage. In total, the ACS surveys approximately three million US households each year. An important feature of the ACS is that it includes a large enough sample for state‐level and sub‐state estimates.
The ACS began asking survey respondents about health insurance coverage during the 2008 calendar year. Specifically, the survey asks respondents about current coverage for each person in the respondent’s household. A person is categorized as “insured” if he or she has coverage at the point in time at which the survey is administered.
Why Aren’t Estimates Provided for All Counties?
Due to sample size constraints, single-year ACS estimates are available at the county level only for counties with a population greater than 65,000.
How Are these Estimates Different from the Estimates that SHADAC Publishes Using Census Bureau Micro-Data Files?
Two definitions used by the Census Bureau to generate the tabulations above differ from those that SHADAC uses to generate tabulations for State Health Compare. The definitional differences are as follows:
Family
- The Census Bureau defines a family as all related people in a household.
- SHADAC defines a family using a measure called the “Health Insurance Unit” (HIU), which includes all individuals who would likely be considered a family unit in determining eligibility for either private or public coverage.
Family Income
- The Census Bureau determines family income as a percentage of the Federal Poverty Level (FPL), which is a definition of poverty used primarily for statistical purposes. For example, FPL is used to estimate the number of Americans living in poverty each year.
- SHADAC determines family income as a percentage of the U.S. Department of Health and Human Services’ Federal Poverty Guidelines (FPG), which is a measure used for administrative purposes. For example, FPG is used to determine eligibility for federal programs such as Medicaid and the Supplemental Nutrition Assistance Program (SNAP).
- To learn more about the difference between FPL and FPG click here.
Publication
October 1st Webinar - An Annual Conversation with the U.S. Census Bureau: New Coverage Data from the ACS & CPS on the New Site for Census Bureau Data
Date: October 1, 2019
Time: 12:00 p.m. - 1:00 p.m. Central / 1:00 p.m. - 2:00 p.m. Eastern
New 2018 data on health insurance coverage from the American Community Survey (ACS) show a nationwide increase in uninsurance from 8.7 percent in 2017 to 8.9 percent in 2018. State-level estimates within the ACS indicated uninsurance also grew significantly in eight states while decreasing significantly in just three.
SHADAC hosted a webinar on Tuesday, October 1st, examining the new 2018 health insurance coverage data from both the ACS and the Current Population Survey Annual Social and Economic Supplement (CPS ASEC), along with additional national and state-level ACS estimates of health insurance by coverage type released on Thursday, September 26th and those yet to be released on Thursday, October 17th.
SHADAC researchers were joined by experts at the U.S. Census Bureau,
which administers both the ACS and the CPS, and attendees learned about:
The new 2018 national and state coverage estimates
When to use which estimates from which survey
How to access the estimates via Census reports and the new site: data.census.gov
How to access state-level estimates from the ACS using SHADAC tables
SHADAC researchers and Census experts also answered questions from attendees after the presentation.
Slides from the webinar, as well as a transcript, are available for download.
Event Resources
2018 ACS: National Uninsurance Increased alongside Eight States; Three States Saw Decreases (SHADAC Blog and Infographic)
2018 ACS: Private Coverage Changes Split Evenly among States, Public Coverage Changes Experience Greater Variability than in 2017 (SHADAC Blog and Infographic)
SHADAC's State Health Compare (Data Dissemination Site)
2017 ACS Tables: State and County Uninsured Rates, with Comparison Year 2016 (SHADAC Resource)
U.S. Census Bureau: Health Insurance (Data Dissemination Site)
U.S. Census Bureau Health Insurance (PDF Report)
U.S. Census Bureau Statistical Testing Tool
U.S. Census Bureau Explore Census Data (Data Dissemination Site)
Publication
The Evolving Opioid Epidemic: Observing the Changes in the Opioid Crisis through State-level Data (Webinar)
Date: September 4, 2019
Time: 11:00 a.m. - 12:00 p.m. Central / 12:00 - 1:00 p.m. Eastern
Background
During the past two decades, the national opioid crisis has proved to be persistent and dynamic. After deaths from prescription opioid painkillers grew quietly for years, the U.S. Centers for Disease Control and Prevention rang the alarm in 2011, declaring the growing problem a national “epidemic.” Despite efforts to rein in the crisis, vital statistics show that opioid overdose deaths have continued to grow year-after-year even after this declaration, reaching more than 47,000 deaths in 2017 alone.
While data has shown limited signs of progress in containing deaths from some opioids, statistics also recently illustrated how the opioid crisis has expanded beyond its early dimensions. Although the growth in death rates from prescription opioid painkillers largely plateaued after the CDC announced the epidemic, death rates from heroin soon began a rapid rise, followed closely by an even larger increase in death rates from synthetic opioids such as fentanyl. By 2017, death rates from synthetic opioids were more than double that of prescription opioid painkillers at their peak.
In July 2019, U.S. Health and Human Services Secretary Alex Azar announced that provisional overdose data from 2018 showed a five percent decline in deaths compared to the previous year, but Secretary Azar also acknowledged “other emerging threats, like concerning trends in cocaine and methamphetamine overdoses.”1 The recent significant increases in death rates from cocaine and methamphetamine, in combination with CDC research finding overdoses from those drugs frequently also involve opioids, raises concerns that the crisis may again be transforming and spreading beyond opioids to other illicit substances.
Webinar
In a recent SHADAC webinar, Senior Research Fellow Colin Planalp examined the U.S. opioid epidemic through national and state-level data on drug overdose deaths, including opioids such as prescription painkillers, heroin and synthetic opioids, and non-opioids (but related drugs) such as cocaine and psychostimulants (e.g., methamphetamine). Using data available through SHADAC’s State Health Compare, the webinar detailed changing trends in the opioid crisis and how the specifics vary across states—both in the scale of the epidemic and differences in the top substances of concern.
Mr. Planalp was joined by SHADAC Research Fellow Robert Hest, who explained how to access and use the data on opioid-related overdose deaths through SHADAC’s State Health Compare website. Mr. Hest also provided an overview of related measures available on State Health Compare, such as the U.S. Drug Enforcement Administration (DEA) data on sales of common prescription opioid painkillers.
Event Resources
Download the slides from the Webinar here. 
The Opioid Epidemic (SHADAC Resource Page)
[1] U.S. Department of Health and Human Services (HHS). (2019, July 17). Secretary Azar Statement on 2018 Provisional Drug Overdose Death Data. Retrieved from https://www.hhs.gov/about/news/2019/07/17/secretary-azar-statement-on-2018-provisional-drug-overdose-death-data.html
