The document compares data on health insurance coverage estimates from the Current Population Survey (CPS), American Community Survey (ACS), and Small Area Health Insurance Estimates (SAHIE). It discusses the methods, geographies, variables, years of data available, and similarities and differences between the three data sources. Key highlights include that CPS provides estimates from 1987 to present for the nation and states, ACS provides more granular sub-state estimates but from 2008 to present, and SAHIE combines ACS with administrative records to provide county-level estimates for 2008 to 2011.
The decennial census determines the allocation of hundreds of billions of federal program dollars. Federal agencies and private entities use data on race, ethnicity, national origin, sex, age, and disability to determine where disparities exist and where community groups could assist. This workshop brings together professionals working to collect data for the census to discuss recently analyzed data with community groups searching for information to support program objectives and goals.
The Impact of Same-Sex Marriage Laws on Health Insurance Coverage: Evidence f...soder145
This document analyzes the impact of same-sex marriage laws on health insurance coverage using data from five states. It finds that when states legalized same-sex marriage, health insurance coverage through employers increased for same-sex couples. In states that transitioned from no recognition to marriage, coverage increased 3.6-4.5 percentage points for same-sex partners. In states that replaced civil unions with marriage, coverage increased 0.4-1.8 percentage points. The findings suggest that same-sex marriage laws provide some protections for LGBT workers by allowing them to add partners to employer-sponsored insurance plans.
Using Small Area Estimates for ACA Outreachsoder145
This document discusses using small area estimates to improve outreach for the Affordable Care Act. It summarizes research on estimating uninsured rates at the zip code tabulation area (ZCTA) level using American Community Survey data and two statistical models: a conditional autoregressive (CAR) model and a composite model. The CAR model provides more reliable estimates but is complex, while the composite model is easier to implement but less established. Maps of estimates can help target outreach efforts.
Medicaid Undercount in the American Community Survey: How does Minnesota Comp...soder145
The summary is as follows:
1) An analysis of 2008 Medicaid enrollment records and American Community Survey data found an implied undercount of Medicaid coverage in the ACS of 22.9%.
2) The undercount was higher among older age groups, those with family incomes over 138% of poverty, and varied by state.
3) This undercount led to an overestimate of the uninsured rate in the ACS of 1.2 percentage points or 3.2 million people. However, there may be other factors offsetting this bias.
This organization helps states analyze health data and inform policy decisions. It uses large-scale surveys like the American Community Survey to provide estimates of health insurance coverage at the state and local level over time. This includes information on subpopulations and the potential impact of policies like the Affordable Care Act. The organization provides online access to these data and training to help states effectively use data to develop evidence-based health policies.
The document discusses the history and purpose of the US Census and American Community Survey (ACS). The Census has counted the US population every 10 years since 1790, while the ACS provides more detailed annual estimates between Census counts. The ACS replaced the long form Census in 2010 and samples 3 million addresses per year to estimate demographic and socioeconomic trends for areas with populations over 65,000. Users must be aware of margins of error and compare similar ACS estimates (1-year, 3-year, or 5-year) when analyzing data.
Medicaid Undercount in the American Community Surveysoder145
This document summarizes research comparing Medicaid reporting in the American Community Survey (ACS) to administrative enrollment data. Key findings include:
- The ACS appears to undercount Medicaid enrollment, though not as much as some other surveys. The undercount increases with age, income, and varies by state.
- Misreporting Medicaid enrollment in the ACS translates to an overestimate of the uninsured population of around 1.2 percentage points or 3.2 million people.
- The undercount is larger for those with more limited Medicaid benefits or shorter enrollment tenure, though the ACS still represents a valuable data source for policy analysis.
First half on how to use Census Data. Presentation from the perspective of a data person in a Governmental Agency. Second part is about combined Census and an example of how I used ESRI's amazing Tapestry Data.
The decennial census determines the allocation of hundreds of billions of federal program dollars. Federal agencies and private entities use data on race, ethnicity, national origin, sex, age, and disability to determine where disparities exist and where community groups could assist. This workshop brings together professionals working to collect data for the census to discuss recently analyzed data with community groups searching for information to support program objectives and goals.
The Impact of Same-Sex Marriage Laws on Health Insurance Coverage: Evidence f...soder145
This document analyzes the impact of same-sex marriage laws on health insurance coverage using data from five states. It finds that when states legalized same-sex marriage, health insurance coverage through employers increased for same-sex couples. In states that transitioned from no recognition to marriage, coverage increased 3.6-4.5 percentage points for same-sex partners. In states that replaced civil unions with marriage, coverage increased 0.4-1.8 percentage points. The findings suggest that same-sex marriage laws provide some protections for LGBT workers by allowing them to add partners to employer-sponsored insurance plans.
Using Small Area Estimates for ACA Outreachsoder145
This document discusses using small area estimates to improve outreach for the Affordable Care Act. It summarizes research on estimating uninsured rates at the zip code tabulation area (ZCTA) level using American Community Survey data and two statistical models: a conditional autoregressive (CAR) model and a composite model. The CAR model provides more reliable estimates but is complex, while the composite model is easier to implement but less established. Maps of estimates can help target outreach efforts.
Medicaid Undercount in the American Community Survey: How does Minnesota Comp...soder145
The summary is as follows:
1) An analysis of 2008 Medicaid enrollment records and American Community Survey data found an implied undercount of Medicaid coverage in the ACS of 22.9%.
2) The undercount was higher among older age groups, those with family incomes over 138% of poverty, and varied by state.
3) This undercount led to an overestimate of the uninsured rate in the ACS of 1.2 percentage points or 3.2 million people. However, there may be other factors offsetting this bias.
This organization helps states analyze health data and inform policy decisions. It uses large-scale surveys like the American Community Survey to provide estimates of health insurance coverage at the state and local level over time. This includes information on subpopulations and the potential impact of policies like the Affordable Care Act. The organization provides online access to these data and training to help states effectively use data to develop evidence-based health policies.
The document discusses the history and purpose of the US Census and American Community Survey (ACS). The Census has counted the US population every 10 years since 1790, while the ACS provides more detailed annual estimates between Census counts. The ACS replaced the long form Census in 2010 and samples 3 million addresses per year to estimate demographic and socioeconomic trends for areas with populations over 65,000. Users must be aware of margins of error and compare similar ACS estimates (1-year, 3-year, or 5-year) when analyzing data.
Medicaid Undercount in the American Community Surveysoder145
This document summarizes research comparing Medicaid reporting in the American Community Survey (ACS) to administrative enrollment data. Key findings include:
- The ACS appears to undercount Medicaid enrollment, though not as much as some other surveys. The undercount increases with age, income, and varies by state.
- Misreporting Medicaid enrollment in the ACS translates to an overestimate of the uninsured population of around 1.2 percentage points or 3.2 million people.
- The undercount is larger for those with more limited Medicaid benefits or shorter enrollment tenure, though the ACS still represents a valuable data source for policy analysis.
First half on how to use Census Data. Presentation from the perspective of a data person in a Governmental Agency. Second part is about combined Census and an example of how I used ESRI's amazing Tapestry Data.
Medicaid Reporting in the ACS: Findings from Linked Administrative and Survey...soder145
This document summarizes a study that analyzed Medicaid reporting in the American Community Survey (ACS) by linking ACS data to Medicaid administrative records. The study found an implied Medicaid undercount in the ACS of 23%, though coverage was better reported in the ACS than in some other surveys. The undercount varied by age, income, state, benefit type, and enrollment tenure. The undercount contributed to an overestimate of the uninsured population of around 1.2 percentage points or 3.2 million people nationally.
The document discusses various data sources that can be used for community needs assessments, including Census data, Neighborhood Scout, Kids Count, and Michigan school data. It provides details on accessing demographic and socioeconomic information from the Census Bureau at the city, ZIP code, and census tract level. It also describes how to obtain data on real estate, crime rates, and education metrics from Neighborhood Scout, Kids Count, and the Michigan Department of Education website.
The document discusses the past, present, and future of traditional survey research. It addresses declining response rates in telephone surveys over the past decade, with landline response rates dropping substantially and cell phone response rates leveling off in recent years. The document also examines whether this decline in response rates has negatively impacted data quality, finding that telephone survey biases have remained relatively stable. Additionally, it compares data quality from non-probability internet panels to traditional telephone surveys, finding few differences between the two after weighting is applied. The future of survey research is uncertain, but telephone surveys may only last another 10 years as landline ownership continues to decline rapidly.
The GSSI initiative provides annual address and spatial feature updates through a partnership program. The partnership program allows tribal, state, county, and local governments to exchange address and spatial data with the Census Bureau. As of February 2014, 247 partners had provided address lists and street centerlines to the Census Bureau. The Census Bureau uses the partner data to update the Master Address File and TIGER/Line files through an interactive review process. The American Community Survey produces annual population and housing characteristic estimates for small areas and groups. Census data products like TIGER/Line files and American FactFinder are available on the Census Bureau website.
NADO Conference - Equity and Regional Economic Development Oct2022.pdfnado-web
This document summarizes a presentation given by Maura Kay of New Growth Innovation Network (NGIN) on analyzing regional economic data through an equity lens. Kay discussed approaches to analyzing data on populations, wages, employment, and industries in six economic development regions, with the goal of understanding impacts on inclusion and identifying opportunities for an equitable recovery from COVID-19 impacts. Key aspects included disaggregating data by race, ethnicity, gender, education and considering both shared challenges and unique needs across regions. The presentation concluded with discussing using data analysis to provide targeted technical assistance to organizations.
This document provides instructions for accessing and analyzing data on limited English proficiency (LEP) populations and poverty levels from the American Community Survey (ACS). It discusses:
1) How to access LEP information and LEP by poverty status using the ACS Public Use Microdata Sample (PUMS) data through the Census DataFerret tool.
2) How to manipulate the PUMS dataset in Excel to calculate household income, assign poverty status indicators, collapse family size categories, and summarize the data by poverty status.
3) How to sort the data to identify and summarize numbers of LEP and non-LEP individuals by poverty status using language ability variables from the ACS.
The document
American Community Survey and the CensusLynda Kellam
The document discusses the history and basics of the US Census and American Community Survey (ACS). It explains that the Census counts the entire population every 10 years and includes basic demographic questions, while the ACS replaced the long form and samples 1 in 6 households annually for more detailed socioeconomic questions. The ACS provides timely annual or multi-year estimate data for areas with populations over 65,000, while the Census provides a single point-in-time count every 10 years.
This document summarizes research presented by Gilbert Gonzales examining the impact of same-sex marriage laws on health insurance coverage using data from four states. The analysis found that legalizing same-sex marriage led to a 7.5-8.2% increase in health insurance coverage for women in same-sex relationships. There was limited evidence of impacts for men or in Iowa, which adopted marriage but had no prior relationship recognition. Replacing civil unions with marriage allowed detectable gains in coverage. The results suggest that access to a spouse's employer-sponsored insurance through legal marriage improves coverage for same-sex couples.
The document summarizes New York State's annual assessment and accountability discussion. It provides data on student performance on English and math assessments from 2006 to 2008. Achievement increased in most grades and subgroups in both subjects. The performance of English language learners and students with disabilities also improved overall. The state is proposing a growth model for accountability that measures student progress toward proficiency from year to year.
The document summarizes annual state assessment results for English language arts and math in New York from 2006 to 2008. It shows that achievement increased statewide for most grades and subgroups, though Grade 8 English scores declined slightly. The achievement gap narrowed for black and Hispanic students. More students with disabilities met standards in both subjects each year. Graduation rates increased over time as well.
Data Presentation for ServiceLink of Carroll County by Jess Carsonjanethuntslrc
What Do We Know About Carroll County? Using Data to Shape a Common Agenda
Prepared by Jess Carson, Vulnerable Families Research Scientist, Carsey School of Public Policy, University of New Hampshire
October 15, 2014
For more information contact Janet Hunt, jhunt@servicelinklrpph.org
The Sample Registration System (SRS) was initiated in India in 1964-1965 to provide reliable demographic data for planning purposes, as birth and death registration was previously voluntary and incomplete. The SRS provides annual estimates of population composition, fertility, mortality, and medical attention at birth/death for India and major states. It covers about 8.1 million people based on a system of dual recording of births and deaths in representative sample units. Key estimates include population by age/sex, fertility rates, mortality rates, and maternal mortality. The SRS is implemented by the Office of the Registrar General and involves state census offices and part-time enumerators.
Establishing a Baseline for the Affordable Care Act: How Accessible and Affor...soder145
This presentation provides an overview of health care access and affordability in Minnesota prior to the Affordable Care Act (ACA). It analyzes data from 2007-2013 on indicators such as having a usual source of care, ability to get needed care, cost-related access problems, and affordability burdens. The results show that while most Minnesotans had access to care, the uninsured and those with public coverage faced greater challenges, being less likely to have a usual provider, more likely to delay care due to costs, and more likely to face financial burdens. The ACA was expected to most impact the individual market and public programs.
The document analyzes changes in demographics and policy concerns in New York State Assembly District 92 from 2002 to 2012. It found significant increases in the Hispanic population and those with lower incomes, and decreases in the white population and young adults. This affects policy concerns around education funding and the minimum wage. Transportation is also a key issue given the suburban nature of the district. Changes in demographics can make it difficult to address all policy needs.
2017 Health Insurance Coverage Estimates: SHADAC Webinar Featuring U.S. Censu...soder145
Join us for an overview of the 2017 health insurance coverage estimates from two key, large-scale federal data sources: The American Community Survey (ACS) and the Current Population Survey (CPS).
This webinar will examine the new estimates with technical insight from experts at the U.S. Census Bureau, which administers both the ACS and CPS, and from SHADAC researchers.
Attendees will learn about:
The new 2017 national and state coverage estimates
When to use which estimates from which survey
How to access the estimates via Census reports and American FactFinder
How to access state-level estimates from the ACS using SHADAC tables
SHADAC researchers and Census experts will answer questions from attendees after the presentation.
Panel #1: Demographic and Economic Considerations for Future Housing NeedsHeartland2050
This document summarizes housing options and challenges for older residents in Nebraska. It discusses the importance of aging-friendly communities that provide essential services within walking distance and adequate transportation. It also describes strategies for aging in place, including home modifications and payment sources. Specific housing models are outlined, such as visitable homes, universal design, supportive housing like accessory dwelling units and congregate housing. Challenges around affordability and accessibility in rural Nebraska are also addressed.
The document summarizes the progress and plans of the UK Office for National Statistics' (ONS) Administrative Data Census Project. The project aims to replace the traditional census with population statistics derived from administrative data by 2021. So far, the project has had success producing population estimates from linked health and tax records. However, fully replacing the census will require improved access to additional administrative data, better data linkage methods, and methods to produce a wider range of statistical outputs to meet user needs. The assessment concludes that while estimates of population size and numbers of households may be feasible by 2023, fully replacing the census with administrative data alone is unlikely due to limitations in available data and methods. Continued progress will depend on new legislation, engagement with
Trends and Disparities in Children's Health Insurance: New Data and the Impli...soder145
This document summarizes key findings from an analysis of trends in children's health insurance coverage between 2016 and 2017. Some key points:
- The uninsured rate among children in the U.S. increased from 4.7% in 2016 to 5% in 2017, reversing over a decade of decline. This represented nearly 270,000 additional uninsured children.
- The increase was driven by a decline in public coverage, particularly Medicaid. Uninsurance rose across most demographic groups.
- There was considerable variation between states, from a low of 1.4% uninsured in Vermont to a high of 10.7% in Texas.
- States with low uninsurance typically had high rates of employer-sponsored insurance or
Exploring Disparities Using New and Updated MEasures on SHADAC's State Health...soder145
Slides from webinar webinar introducing two new measures of health outcomes and social determinants of health on SHADAC’s State Health Compare—Unhealthy Days and Unaffordable Rents. This presentation, hosted by SHADAC researchers Brett Fried and Robert Hest, examine these new measures and highlight how the estimates can be used to explore disparities between states and among sub-populations.
Medicaid Reporting in the ACS: Findings from Linked Administrative and Survey...soder145
This document summarizes a study that analyzed Medicaid reporting in the American Community Survey (ACS) by linking ACS data to Medicaid administrative records. The study found an implied Medicaid undercount in the ACS of 23%, though coverage was better reported in the ACS than in some other surveys. The undercount varied by age, income, state, benefit type, and enrollment tenure. The undercount contributed to an overestimate of the uninsured population of around 1.2 percentage points or 3.2 million people nationally.
The document discusses various data sources that can be used for community needs assessments, including Census data, Neighborhood Scout, Kids Count, and Michigan school data. It provides details on accessing demographic and socioeconomic information from the Census Bureau at the city, ZIP code, and census tract level. It also describes how to obtain data on real estate, crime rates, and education metrics from Neighborhood Scout, Kids Count, and the Michigan Department of Education website.
The document discusses the past, present, and future of traditional survey research. It addresses declining response rates in telephone surveys over the past decade, with landline response rates dropping substantially and cell phone response rates leveling off in recent years. The document also examines whether this decline in response rates has negatively impacted data quality, finding that telephone survey biases have remained relatively stable. Additionally, it compares data quality from non-probability internet panels to traditional telephone surveys, finding few differences between the two after weighting is applied. The future of survey research is uncertain, but telephone surveys may only last another 10 years as landline ownership continues to decline rapidly.
The GSSI initiative provides annual address and spatial feature updates through a partnership program. The partnership program allows tribal, state, county, and local governments to exchange address and spatial data with the Census Bureau. As of February 2014, 247 partners had provided address lists and street centerlines to the Census Bureau. The Census Bureau uses the partner data to update the Master Address File and TIGER/Line files through an interactive review process. The American Community Survey produces annual population and housing characteristic estimates for small areas and groups. Census data products like TIGER/Line files and American FactFinder are available on the Census Bureau website.
NADO Conference - Equity and Regional Economic Development Oct2022.pdfnado-web
This document summarizes a presentation given by Maura Kay of New Growth Innovation Network (NGIN) on analyzing regional economic data through an equity lens. Kay discussed approaches to analyzing data on populations, wages, employment, and industries in six economic development regions, with the goal of understanding impacts on inclusion and identifying opportunities for an equitable recovery from COVID-19 impacts. Key aspects included disaggregating data by race, ethnicity, gender, education and considering both shared challenges and unique needs across regions. The presentation concluded with discussing using data analysis to provide targeted technical assistance to organizations.
This document provides instructions for accessing and analyzing data on limited English proficiency (LEP) populations and poverty levels from the American Community Survey (ACS). It discusses:
1) How to access LEP information and LEP by poverty status using the ACS Public Use Microdata Sample (PUMS) data through the Census DataFerret tool.
2) How to manipulate the PUMS dataset in Excel to calculate household income, assign poverty status indicators, collapse family size categories, and summarize the data by poverty status.
3) How to sort the data to identify and summarize numbers of LEP and non-LEP individuals by poverty status using language ability variables from the ACS.
The document
American Community Survey and the CensusLynda Kellam
The document discusses the history and basics of the US Census and American Community Survey (ACS). It explains that the Census counts the entire population every 10 years and includes basic demographic questions, while the ACS replaced the long form and samples 1 in 6 households annually for more detailed socioeconomic questions. The ACS provides timely annual or multi-year estimate data for areas with populations over 65,000, while the Census provides a single point-in-time count every 10 years.
This document summarizes research presented by Gilbert Gonzales examining the impact of same-sex marriage laws on health insurance coverage using data from four states. The analysis found that legalizing same-sex marriage led to a 7.5-8.2% increase in health insurance coverage for women in same-sex relationships. There was limited evidence of impacts for men or in Iowa, which adopted marriage but had no prior relationship recognition. Replacing civil unions with marriage allowed detectable gains in coverage. The results suggest that access to a spouse's employer-sponsored insurance through legal marriage improves coverage for same-sex couples.
The document summarizes New York State's annual assessment and accountability discussion. It provides data on student performance on English and math assessments from 2006 to 2008. Achievement increased in most grades and subgroups in both subjects. The performance of English language learners and students with disabilities also improved overall. The state is proposing a growth model for accountability that measures student progress toward proficiency from year to year.
The document summarizes annual state assessment results for English language arts and math in New York from 2006 to 2008. It shows that achievement increased statewide for most grades and subgroups, though Grade 8 English scores declined slightly. The achievement gap narrowed for black and Hispanic students. More students with disabilities met standards in both subjects each year. Graduation rates increased over time as well.
Data Presentation for ServiceLink of Carroll County by Jess Carsonjanethuntslrc
What Do We Know About Carroll County? Using Data to Shape a Common Agenda
Prepared by Jess Carson, Vulnerable Families Research Scientist, Carsey School of Public Policy, University of New Hampshire
October 15, 2014
For more information contact Janet Hunt, jhunt@servicelinklrpph.org
The Sample Registration System (SRS) was initiated in India in 1964-1965 to provide reliable demographic data for planning purposes, as birth and death registration was previously voluntary and incomplete. The SRS provides annual estimates of population composition, fertility, mortality, and medical attention at birth/death for India and major states. It covers about 8.1 million people based on a system of dual recording of births and deaths in representative sample units. Key estimates include population by age/sex, fertility rates, mortality rates, and maternal mortality. The SRS is implemented by the Office of the Registrar General and involves state census offices and part-time enumerators.
Establishing a Baseline for the Affordable Care Act: How Accessible and Affor...soder145
This presentation provides an overview of health care access and affordability in Minnesota prior to the Affordable Care Act (ACA). It analyzes data from 2007-2013 on indicators such as having a usual source of care, ability to get needed care, cost-related access problems, and affordability burdens. The results show that while most Minnesotans had access to care, the uninsured and those with public coverage faced greater challenges, being less likely to have a usual provider, more likely to delay care due to costs, and more likely to face financial burdens. The ACA was expected to most impact the individual market and public programs.
The document analyzes changes in demographics and policy concerns in New York State Assembly District 92 from 2002 to 2012. It found significant increases in the Hispanic population and those with lower incomes, and decreases in the white population and young adults. This affects policy concerns around education funding and the minimum wage. Transportation is also a key issue given the suburban nature of the district. Changes in demographics can make it difficult to address all policy needs.
2017 Health Insurance Coverage Estimates: SHADAC Webinar Featuring U.S. Censu...soder145
Join us for an overview of the 2017 health insurance coverage estimates from two key, large-scale federal data sources: The American Community Survey (ACS) and the Current Population Survey (CPS).
This webinar will examine the new estimates with technical insight from experts at the U.S. Census Bureau, which administers both the ACS and CPS, and from SHADAC researchers.
Attendees will learn about:
The new 2017 national and state coverage estimates
When to use which estimates from which survey
How to access the estimates via Census reports and American FactFinder
How to access state-level estimates from the ACS using SHADAC tables
SHADAC researchers and Census experts will answer questions from attendees after the presentation.
Panel #1: Demographic and Economic Considerations for Future Housing NeedsHeartland2050
This document summarizes housing options and challenges for older residents in Nebraska. It discusses the importance of aging-friendly communities that provide essential services within walking distance and adequate transportation. It also describes strategies for aging in place, including home modifications and payment sources. Specific housing models are outlined, such as visitable homes, universal design, supportive housing like accessory dwelling units and congregate housing. Challenges around affordability and accessibility in rural Nebraska are also addressed.
The document summarizes the progress and plans of the UK Office for National Statistics' (ONS) Administrative Data Census Project. The project aims to replace the traditional census with population statistics derived from administrative data by 2021. So far, the project has had success producing population estimates from linked health and tax records. However, fully replacing the census will require improved access to additional administrative data, better data linkage methods, and methods to produce a wider range of statistical outputs to meet user needs. The assessment concludes that while estimates of population size and numbers of households may be feasible by 2023, fully replacing the census with administrative data alone is unlikely due to limitations in available data and methods. Continued progress will depend on new legislation, engagement with
Trends and Disparities in Children's Health Insurance: New Data and the Impli...soder145
This document summarizes key findings from an analysis of trends in children's health insurance coverage between 2016 and 2017. Some key points:
- The uninsured rate among children in the U.S. increased from 4.7% in 2016 to 5% in 2017, reversing over a decade of decline. This represented nearly 270,000 additional uninsured children.
- The increase was driven by a decline in public coverage, particularly Medicaid. Uninsurance rose across most demographic groups.
- There was considerable variation between states, from a low of 1.4% uninsured in Vermont to a high of 10.7% in Texas.
- States with low uninsurance typically had high rates of employer-sponsored insurance or
Exploring Disparities Using New and Updated MEasures on SHADAC's State Health...soder145
Slides from webinar webinar introducing two new measures of health outcomes and social determinants of health on SHADAC’s State Health Compare—Unhealthy Days and Unaffordable Rents. This presentation, hosted by SHADAC researchers Brett Fried and Robert Hest, examine these new measures and highlight how the estimates can be used to explore disparities between states and among sub-populations.
Leveraging 1332 State Innovation Waivers to Stabilize Individual Health Insur...soder145
Presentation by SHADAC Senior Research Fellow Emily Zylla at the 2018 Association for Public Policy Analysis & Management (APPAM) Fall Research Meeting in Washington, DC.
Modeling State-based Reinsurance: One Option for Stabilization of the Individ...soder145
This document summarizes research on modeling state-based reinsurance programs to stabilize individual health insurance markets. Key findings include:
- An estimated $60 billion is spent annually in the individual market, with 2.5% of enrollees accounting for 48.8% of expenditures.
- State reinsurance programs with varying parameters could reduce insurer costs by $6-14 billion nationally per year.
- Estimated reinsurance costs for four states range from $300,000 to $1.8 billion depending on the attachment point and coinsurance rate.
- Federal transitional reinsurance and proposed legislation allocated $10 billion annually, consistent with these estimates.
Exploring the New State-Level Opioid Data On SHADAC's State Health Comparesoder145
Between 2000 and 2016, the annual number of drug overdose deaths in the United States more than tripled, from 17,500 to 63,500, and most of these deaths involved opioids. Despite widespread increases in overdose death rates from natural and semi-synthetic opioids, synthetic opioids, and heroin, individual states’ death rates varied widely. For example, in 2016, Nebraska’s rate of 1.2 deaths per 100,000 people was the lowest in the U.S. for natural and semi-synthetic opioids, while West Virginia’s rate (the highest) was more than 15 times larger, at 18.5 deaths. These deaths are the most glaring indication of the growing crisis of opioid abuse and addiction that has been spreading unevenly throughout the country over the past two decades.
On this SHADAC webinar, Research Fellow Colin Planalp will examine the United States opioid epidemic at the state level, analyzing trends in overdose deaths from heroin and other opioids, such as prescription painkillers. Using data available through SHADAC’s State Health Compare, he will look at which states have the highest rates of opioid-related deaths and which have experienced the largest increases in death rates.
Mr. Planalp will be joined by SHADAC Research Fellow Robert Hest, who will discuss the data on opioid-related overdose deaths from the U.S. Centers from Disease Control and Prevention (CDC) that are available on SHADAC’s State Health Compare. He will also discuss State Health Compare data from the U.S. Drug Enforcement Administration (DEA) on sales of common prescription opioid painkillers. Mr. Hest will show users how to access and use the data for state-level analyses.
This document summarizes research on the intersection of structural risk factors and insurance-based discrimination on healthcare access inequities. The study analyzed data on over 3,800 non-elderly adults in Minnesota to examine how experiences of insurance-based discrimination vary across gender, race, income and insurance status, both independently and combined. It also assessed how the synergistic effects of structural risk factors and reported discrimination influence access to a usual source of care and confidence in getting needed healthcare services. The results show that structural factors like race, income and insurance status combine to produce greater reported discrimination, which then interacts with those factors to further reduce healthcare access. The implications are that reducing inequities requires attention to the convergence of these structural barriers
This study analyzed characteristics associated with accurate reports of health insurance coverage in census surveys. It found that reporting of public insurance was most accurate among low-income, less educated individuals who likely needed care. Reporting varied by specific public program, with family characteristics impacting Medicaid accuracy and respondent characteristics impacting MinnesotaCare accuracy. Private insurance reporting in the ACS was more accurate among advantaged groups, while the CPS saw greater accuracy among older respondents with long-term coverage. The results provide insight into survey design, editing, and using survey data for policy analysis by identifying who reports coverage most reliably.
- The document presents preliminary results from the Minnesota Long-Term Services and Supports Projection Model (MN-LPM), which projects LTSS utilization and costs for Minnesota's Medicaid elderly population through 2030.
- In 2015, over 54,000 Minnesotans received LTSS through Medicaid, costing $991 million total. The model projects these numbers will double by 2030, with LTSS costs reaching $1.7 billion as HCBS use grows significantly faster than nursing home use.
- The model uses Minnesota-specific data on the characteristics of elderly residents and current LTSS spending patterns to generate projections. It is intended to help evaluate potential policy changes that could impact future LTSS needs and costs in
Modeling Financial Eligibility for Medicaid Payment of LTSS
1) Medicaid long-term services and expenditures (LTSS) are a large and growing part of state budgets. States may restrict LTSS eligibility rules to control costs.
2) The researchers modeled LTSS eligibility rules to understand their impact and potential consequences of restricting access.
3) The model found that restricting income eligibility rules had a larger impact on reducing the number of eligible individuals than restricting asset rules. This is because income rules are more broadly applied and generous under current policies.
Poster, advancements in care coordination mn simsoder145
The document summarizes findings from an evaluation of Minnesota's State Innovation Model (SIM) Initiative. It finds that Minnesota's SIM investments increased organizations' capacity for coordinated care in several ways:
1) It strengthened relationships and knowledge sharing between organizations.
2) It improved some care coordination processes like assessing social needs and accessing data.
3) It expanded access to health information exchange capabilities needed to coordinate care across settings.
- Structured interviews were conducted with 33 current and former state agency and health plan staff across 4 states to understand challenges implementing Section 1115 Medicaid expansion waiver programs.
- Key challenges included the significant administrative resources and coordination required across entities, educating enrollees, and reconciling complex program rules across systems.
- While waiver programs allowed for innovative policy testing, the administrative complexity was substantial and ongoing. Implementation involved major efforts to develop new IT systems and operational protocols within tight timelines.
1. The document analyzes the potential impact and costs of state-based reinsurance programs using data from 2012-2015.
2. It estimates that reinsurance subsidies could range from $6.4 billion to $16 billion annually depending on the attachment point and coinsurance rate.
3. Reinsurance costs are estimated to range from close to $300,000 in Illinois to $2 billion in California under sample programs with an 80/20 coinsurance split.
Comparing Health Insurance Measurement Error (CHIME) in the ACS & CPSsoder145
This document summarizes a study that compared survey responses about health insurance from the American Community Survey (ACS) and Current Population Survey (CPS) to actual administrative insurance records to assess accuracy. The study found that both surveys produced reasonably accurate aggregated estimates but that some types of coverage, like direct purchase plans, were less accurately reported. Specifically:
- Both surveys had high sensitivity in detecting those with any insurance but the ACS performed better for direct purchase plans.
- The predictive power of reported coverage types varied, with direct purchase again less accurately predicted than employer-sponsored coverage.
- Prevalence estimates based on surveys were generally within a few percentage points of administrative records, though CPS estimates were less accurate for
Who Gets It Right? Characteristics Associated with Accurate Reporting of Heal...soder145
This document summarizes a study examining factors associated with accurate reporting of health insurance coverage type. The study used survey data matched to enrollment records from a health plan. It found:
1) Reporting accuracy was highest for those with employer-sponsored insurance and lowest for those with direct purchase or Medicaid coverage.
2) Among those with direct purchase insurance, reporting accuracy was higher for those who were white, non-Hispanic, fully employed, and from higher income households.
3) For Medicaid enrollees, reporting accuracy was higher for those who were unemployed, from lower income and education households.
Medicaid vs. Marketplace Coverage for Near-Poor Adults: Impact on Out-of-Pock...soder145
1) The document analyzes the impact of state Medicaid expansion decisions on out-of-pocket health expenses and insurance coverage for low-income adults making 100-138% of the federal poverty level.
2) It finds that Medicaid expansion was associated with lower total out-of-pocket spending (a reduction of $353), lower premium spending (a reduction of $118), and lower medical spending (a reduction of $235) compared to non-expansion states.
3) Medicaid expansion also increased Medicaid coverage by 11.1 percentage points and decreased the uninsured rate by 4.5 percentage points for this low-income group relative to non-expansion states.
The Impact of Medicaid Expansion on Employer Provision of Health Insurancesoder145
- The study examines the impact of Medicaid expansion under the ACA on employer-sponsored health insurance (ESI) offers, out-of-pocket premiums, and eligibility using data from 2010-2015.
- The results show Medicaid expansion decreased worker eligibility for ESI offers by 4 percentage points but had no effect on ESI offers or out-of-pocket premiums. There was also no differential effect for low-wage establishments.
- The authors note the short-term effects may differ from long-term effects, and ongoing uncertainty could impact employer behavior and outcomes over time as more states expand Medicaid.
Physician Participation in Medi-Cal: Is Supply Meeting Demand? soder145
This document summarizes a webinar presentation on physician participation in California's Medicaid program, Medi-Cal. The presentation was given by Janet Coffman from UCSF and Alan McKay from the Central California Alliance for Health.
Key findings from Coffman's presentation include: California physicians are less likely to accept new Medi-Cal patients than patients with private insurance or Medicare; acceptance rates vary by specialty, practice type, and region; and the most common reasons physicians limit Medi-Cal patients are delays in payment and administrative hassles.
McKay discussed the Alliance's efforts to expand Medi-Cal provider capacity after expansion, including grant programs for recruitment, equipment, practice coaching,
The document summarizes key information from a webinar about 2015 health insurance coverage estimates from the American Community Survey (ACS) and Current Population Survey (CPS). It provides an overview of the surveys' methodologies, measures of health insurance coverage, changes in insurance rates from 2013 to 2015, and resources for accessing public data from the ACS and CPS. New products for analyzing health insurance coverage from both surveys were also announced.
The document summarizes a webinar presented by experts from the U.S. Census Bureau on the Small Area Health Insurance Estimates (SAHIE). SAHIE provides county-level estimates of health insurance coverage across various demographic groups. The webinar discussed the 2014 SAHIE release, which incorporated more up-to-date Medicaid data and showed substantial changes in insurance rates from 2013 to 2014. The webinar also reviewed the data sources and methodology used to produce the SAHIE estimates.
Adding complexity to an already difficult task: Monitoring the impact of the ...soder145
The document summarizes research comparing estimates of Medicaid enrollment in 2013 and 2014 from the American Community Survey (ACS) and Centers for Medicare and Medicaid Services (CMS) administrative data. The research finds that states with the largest increases in Medicaid enrollment according to CMS also tended to have the largest differences between ACS and CMS estimates, with ACS generally reporting lower enrollment. This suggests the ACS may overstate uninsurance rates where Medicaid enrollment increased substantially. However, misreported coverage likely represents shifts between coverage types rather than uninsurance. Future research should analyze additional years of data and link administrative and survey sources to better understand reporting errors.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
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Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
Lee Barnes - Path to Becoming an Effective Test Automation Engineer.pdfleebarnesutopia
So… you want to become a Test Automation Engineer (or hire and develop one)? While there’s quite a bit of information available about important technical and tool skills to master, there’s not enough discussion around the path to becoming an effective Test Automation Engineer that knows how to add VALUE. In my experience this had led to a proliferation of engineers who are proficient with tools and building frameworks but have skill and knowledge gaps, especially in software testing, that reduce the value they deliver with test automation.
In this talk, Lee will share his lessons learned from over 30 years of working with, and mentoring, hundreds of Test Automation Engineers. Whether you’re looking to get started in test automation or just want to improve your trade, this talk will give you a solid foundation and roadmap for ensuring your test automation efforts continuously add value. This talk is equally valuable for both aspiring Test Automation Engineers and those managing them! All attendees will take away a set of key foundational knowledge and a high-level learning path for leveling up test automation skills and ensuring they add value to their organizations.
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
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How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
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- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
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In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
Discover the Unseen: Tailored Recommendation of Unwatched ContentScyllaDB
The session shares how JioCinema approaches ""watch discounting."" This capability ensures that if a user watched a certain amount of a show/movie, the platform no longer recommends that particular content to the user. Flawless operation of this feature promotes the discover of new content, improving the overall user experience.
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📕 Detailed agenda:
Variables and Datatypes
Workflow Layouts
Arguments
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This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
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We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
"What does it really mean for your system to be available, or how to define w...Fwdays
We will talk about system monitoring from a few different angles. We will start by covering the basics, then discuss SLOs, how to define them, and why understanding the business well is crucial for success in this exercise.
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• For those dialing in: All phones are muted
• Submit questions using the chat window at any time
during the webinar
• Troubleshooting:
• Call Readytalk’s help line: (800) 843-9166
• Ask for help using the chat feature
• Download the slides at
http://www.shadac.org/estimateswebinar
• Webinar archive will be posted on SHADAC’s web site
• E-mail notice will be sent to participants
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Julie Sonier
SHADAC
Deputy Director
Joanna Turner
SHADAC
Senior Research Fellow
Brett O’Hara
Chief, Health and Disability Statistics
Branch, U.S. Census Bureau
Jennifer Day
Assistant Division Chief for
Employment Characteristics,
U.S. Census Bureau
Lucinda Dalzell
Chief, Small Area Estimates Branch,
U.S. Census Bureau
Mark Bauder
Mathematical Statistician,
U.S. Census Bureau
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• Current Population Survey (CPS)
• 2012 estimates released September 17, 2013
• American Community Survey (ACS)
• 2012 estimates released September 19, 2013
• Small Area Health Insurance Estimates (SAHIE)
• 2011 estimates released August 29, 2013
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
CPS
• 2-year averages: changes
in state estimates over time
• 3-year averages: compare
across states within a year
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
ACS
Census Bureau published
estimates restricted to the
civilian non-
institutionalized population
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
Data Sources for SAHIE:
• ACS
• Population estimates
• Federal income tax returns
• Supplemental Nutrition
Assistance program records
• County Business Patterns
• Medicaid/CHIP records
• 2010 Census
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CPS ACS SAHIE
Method Survey of civilian
non-institutionalized
population
Survey of U.S.
population (including
group quarters)
Combine ACS
estimates with
administrative data
Annual housing
units interviewed
About 76,000 About 2.3 million N/A
Geography Nation, states Nation, states, sub-
state
Nation, state,
county
Mode Phone and in-
person
Mail, phone, and in-
person
N/A
Uninsurance:
Measure
Uninsured all year Point-in-time Point-in-time
Uninsurance:
Years available
1987 to 2012 2008 to 2012 2008 to 2011
(Using the ACS)*
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* SAHIE estimates using the CPS available for 2000, 2001, and
2005 to 2007
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CPS ACS SAHIE
Coverage types Uninsured, Insured
Private
• Employer
• Direct purchase
Public
• Medicare
• Medicaid
• Military
(TRICARE & VA)
Uninsured, Insured
Private
• Employer
• Direct purchase
• TRICARE
Public
• Medicare
• Medicaid
• VA
Uninsured, Insured
Disability status Yes Yes No
Health status Yes No No
Employer size Yes No No
Medical out-of-
pocket
expenditures
Yes No No
Housing values No Yes No
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CPS ACS SAHIE
Trends over long
time period
1987 forward
State estimates
2-year averages
Sub-state
estimates
1-yr for pop > 65,000
3-yr for pop > 20,000
5-yr for pop < 20,000
1-year for all
counties
Small
subpopulations
Age, income,
poverty, sex,
race/ethnicity (state
only)
Coverage by type Under investigation
Custom tabs
from microdata
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CPS and ACS
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Private Health
Insurance
Public
Coverage
Uninsured
0
10
20
30
40
50
60
70
80
2008 2009 2010 2011 2012
Percent
Solid lines indicate CPS; Dotted lines indicate ACS.
‘11-’12
Change
ACS -0.1
CPS −
CPS +0.4*
ACS +0.6*
CPS -0.3*
ACS -0.4*
* Within-survey change from 2011 to 2012 is statistically significant at the 90 percent confidence interval.
− Represents or rounds to zero.
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Private Health
Insurance
Public
Coverage
Uninsured
0
10
20
30
40
50
60
70
80
2008 2009 2010 2011 2012
Percent
Solid lines indicate CPS; Dotted lines indicate ACS.
‘11-’12
Change
CPS +0.7
ACS -0.5*
CPS +0.4
ACS +0.8*
CPS -0.5*
ACS -0.3*
* Within-survey change from 2011 to 2012 is statistically significant at the 90 percent confidence interval.
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Under 18
19 to 25
18 to 64
Under 65
65 and over
0
5
10
15
20
25
30
35
2008 2009 2010 2011 2012
Percent
Solid lines indicate CPS; Dotted lines indicate ACS.
‘11-’12
Change
CPS -0.5
ACS -1.6*
CPS -0.2
ACS -0.3*
CPS -0.3
ACS -0.3*
CPS -0.5*
ACS -0.3*
CPS -0.2
ACS −
* Within-survey change from 2011 to 2012 is statistically significant at the 90 percent confidence interval.
− Represents or rounds to zero.
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White
alone
Black
alone
Hispanic
0
5
10
15
20
25
30
35
2008 2009 2010 2011 2012
Percent
Solid lines indicate CPS; Dotted lines indicate ACS.
‘11-’12
Change
CPS -1.0*
ACS -0.8*
CPS -0.5
ACS -0.4*
CPS -0.2
ACS -0.3*
* Within-survey change from 2011 to 2012 is statistically significant at the 90 percent confidence interval.
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Source: U.S. Census Bureau ACS Brief
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Source: U.S. Census Bureau ACS Brief
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• 2 new detailed health insurance coverage tables for
young adults 19-25 (B27022 & B27023)
• Young adults added to table S2701 – total uninsured
19-25
• 113th Congressional Districts available
• First release based on 2010 Census definitions for
Public Use Microdata Areas (PUMAs), Urban Areas,
and Urban/Rural
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• Public Use Microdata Samples (PUMS) available fall
2013
• 1% public use microdata sample (1% of population)
• The smallest identifiable geographic unit is the PUMA,
containing at least 100,000 persons
• PUMAs are generally groups of counties or parts of counties,
but there are exceptions
• PUMAs do not cross state boundaries
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• 2010-2012 3-year estimates for areas with
population >20,000
• American FactFinder release: October 24
• PUMS: TBD
• 2008-2012 5-year estimates for all geographic areas
• American FactFinder release: December 5
• PUMS: TBD
• First 5-year file with health insurance coverage
estimates
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• 2012 CPS data will be available soon
• SHADAC-Enhanced CPS will be available soon
• ACS data files will be released about 1-2 weeks after
available from the Census Bureau
• SHADAC Health Insurance Unit (HIU) and Federal
Poverty Guidelines (FPG) variables for 2012 CPS
and ACS will be available soon
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http://www.ipums.org
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• Updating with:
• 2012 CPS
• 2012 SHADAC-
Enhanced CPS
• 2012 ACS
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http://www.shadac.org/datacenter
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• Health insurance coverage (Pascale, 2013 JSM)
• Improved all year coverage measure
• Add point-in-time coverage measure
• New questions to measure exchange participation
• New questions on employer offered health insurance
coverage
• Income (Semega and Welniak, 2013 JSM)
• Improve data quality, take better advantage of an
automated instrument, reflect changing retirement
environment, improve clarification and reporting of asset
income
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SAHIE
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http://www.census.gov/did/www/sahie/
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Source: U.S. Census Bureau
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Source: U.S. Census Bureau
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• Updated health insurance page
• http://www.census.gov/hhes/www/hlthins/index.html
• American FactFinder summary tables
• http://factfinder2.census.gov
• “Mitigating the Loss of Private Insurance with Public
Coverage for Under-65 Population: 2008 to 2012”
(ACS Brief)
• http://www.census.gov/prod/2013pubs/acsbr12-11.pdf
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• Updated SAHIE page
• http://www.census.gov/did/www/sahie
• Guidance on when to use different data sources
• http://www.census.gov/hhes/www/hlthins/about/index.html
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• “Comparing Federal Government Surveys that Count
the Uninsured”
• http://shadac.org/publications/comparingfedsurveys2013
• “Small Area Health Insurance Estimates from the
Census Bureau: 2008 and 2009” (Brief #26)
• http://www.shadac.org/files/shadac/publications/SHADAC
_Brief26.pdf
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• ACS tables from American FactFinder showing
change in health insurance coverage for states and
counties
• http://shadac.org/acscomparisontables2013
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www.shadac.org
@shadac
Direct inquires to
Joanna Turner, turn0053@umn.edu
or shadac@umn.edu