This document discusses research comparing Medicaid enrollment counts from the American Community Survey (ACS) and Centers for Medicare and Medicaid Services (CMS) administrative data before and after the implementation of the Affordable Care Act. It presents data showing larger increases in enrollment and larger differences between ACS and CMS counts in states that expanded Medicaid compared to non-expansion states. Tables and figures analyze enrollment changes from 2013 to 2014 and differences between ACS and CMS counts for states with the largest and smallest enrollment increases. The findings suggest misreporting of Medicaid coverage in surveys may have increased more in expansion states post-ACA.
Speaker presentation from U.S. News Healthcare of Tomorrow leadership summit, Nov. 17-19, 2019 in Washington, DC. Find out more about this forum at www.usnewshot.com.
Palestra de Rachel David no 3º Fórum Nacional da Saúde Suplementar, realizado pela Federação Nacional de Saúde Suplementar (FenaSaúde), no Sheraton WTC São Paulo Hotel, no dia 6 de outubro de 2017.
InCites for publishers Frankfurt Book Fair 2015Ian Potter
An overview of the Thomson Reuters InCites BenchMarking & Analytics package with a range of indicators in addition to the journal impact fact and its use by publishers to analyse journal and list performance.
Speaker presentation from U.S. News Healthcare of Tomorrow leadership summit, Nov. 17-19, 2019 in Washington, DC. Find out more about this forum at www.usnewshot.com.
Palestra de Rachel David no 3º Fórum Nacional da Saúde Suplementar, realizado pela Federação Nacional de Saúde Suplementar (FenaSaúde), no Sheraton WTC São Paulo Hotel, no dia 6 de outubro de 2017.
InCites for publishers Frankfurt Book Fair 2015Ian Potter
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The U.S. Nursing Workforce Trends in Supply and Education 3 .docxchristalgrieg
The U.S. Nursing Workforce: Trends in Supply and Education 3
Section 1
The Registered Nurse and
Licensed Practical Nurse Workforce
An analysis of recent trends in the nursing workforce is important to anticipate future
supply growth and identify likely changes in educational and demographic composition.
Information on the size of the U.S. nursing workforce and its distribution across states and
in rural and urban areas is presented. Growth in the workforce over time is measured against
growth in the general population. Next, key trends in educational attainment, racial/ethnic
composition, and gender are highlighted. The section concludes with an analysis of trends in
the setting and work hours of the nursing workforce.
Two sources of data from the U.S. Census Bureau were used to examine the current supply
of registered nurses (RNs) and licensed practical nurses (LPNs), as well as changes in the
workforce that have occurred during the past decade: the American Community Survey (ACS)
three-year combined file for 2008 to 2010 and the Census 2000 Long Form 5-percent sample.
(See “About the Data” below.)
Owing to the household sampling strategy of these Census surveys, all results presented
in this section are for the nursing workforce—those individuals who report their current
occupation as nursing and who currently have or are seeking a job. It is not possible to count,
with either data source, the number of individuals educated or licensed as nurses who are
working in another field or are out of the workforce entirely. Another important note is that
advanced practice registered nurses are included in results for RNs. The Census data sources
used here do not separate them.
The U.S. Nursing Workforce: Trends in Supply and Education4
About the Data
The ACS 2008 to 2010 three-year file and Census 2000 Long Form
5-percent sample offer nearly identical question wording and an
established set of techniques for comparing results over time.
The sources also offer large sample sizes: more than 110,000 RNs
and 31,000 LPNs are included within the 2000 5-percent sample,
while nearly 90,000 RNs and more than 21,000 LPNs are included
in the ACS 2008 to 2010 three-year file. This means that estimates
derived from these sources are highly precise and, in most cases,
can be made at both state and national levels.
The ACS 2008 to 2010 three-year file was selected over a single-
year file in order to improve the precision of state and national
estimates. Unlike the Census 2000 data, which represent a
point in time, the ACS three-year file represents an average
of the three-year time period. It is inappropriate to refer to
this estimate as representing 2009. Throughout this section,
we refer to this as the “current” nurse supply because it was
the most up-to-date three-year file available at the time of our
analysis.
For most estimates, relative standard errors (RSEs) are quite small.
Becau ...
Accountability For the Care We ProvideCentralPAHEF
On March 3, 2016 at Highmark Blue Shield there were healthcare executives gathered for the Healthcare Executive Forum of Central PA's quarterly event. This American College of Healthcare Executive's event was worth 1.5 face to face credits. We focused on the issues and preparation for changing healthcare landscapes. Three speakers shared their experience, which was bountiful. These speakers are Moderator: Terry Madonna, Director of the Center for Politics and Public Affairs, Franklin and Marshall College; Speakers: Gerald Walsh, VP, Provider Contracting and Relations, Highmark; Thomas Northrop, NorHealth Management Group, CEO; Michael Consuelos, SVP, Clinical Integration at The Hospital & Healthsystem Association of Pennsylvania. Visit our website for full biographies and more at www.centralpa.ache.org.
Sheet1AnnéeDateRoyal Hotel OccupancyADR Royal HotelRoyal Hotel Rev.docxedgar6wallace88877
Sheet1AnnéeDateRoyal Hotel OccupancyADR Royal HotelRoyal Hotel RevParSTR OccupancySTR ADRSTR RevParEcart Ecart Ecart Rooms2102014Jan-201460%265.45159.2768%294.07200.92-8%-28.62-41.65Feb-201461%268.41163.4666%277.44182.57-5%-9.03-19.11Mar-201464%281.96181.0268%280.16191.89-4%1.80-10.88Apr-201463%274.09172.9569%288.12198.83-6%-14.03-25.88May-201463%272.50170.8679%325.23256.76-16%-52.73-85.90Jun-201465%279.85181.3480%333.09265.22-15%-53.24-83.87Jul-201466%281.74186.2381%300.94243.25-15%-19.20-57.02Aug-201465%277.04178.9788%385.63338.51-23%-108.59-159.54Sep-201466%286.15187.7191%488.98443.94-25%-202.83-256.23Oct-201469%300.38206.3687%403.46350.26-18%-103.08-143.90Nov-201466%285.99187.3283%338.20279.13-17%-52.21-91.80Dec-201467%293.30197.3980%312.04248.31-12%-18.74-50.922015Jan-201569%300.46207.6271%300.98213.89-2%-0.52-6.27Feb-201570%306.08214.8770%311.90217.620%-5.82-2.75Mar-201574%321.31238.4174%286.80213.65-0%34.5124.76Apr-201574%319.47235.7775%319.77240.41-1%-0.30-4.64May-201573%316.56230.7779%337.01267.43-6%-20.45-36.66Jun-201575%328.30247.5478%336.64262.60-3%-8.34-15.07Jul-201577%336.57257.4883%354.86295.83-7%-18.29-38.35Aug-201574%326.96241.3087%409.61354.88-13%-82.65-113.58Sep-201574%329.35244.7186%478.38411.35-12%-149.03-166.64Oct-201578%345.19267.8785%408.49346.86-7%-63.30-79.00Nov-201572%324.90234.9070%322.31224.763%2.5910.15Dec-201574%334.62245.9573%334.76243.981%-0.141.972016Jan-201674%343.26255.0460%304.76183.7714%38.5071.27Feb-201675%348.92260.9963%329.49208.3812%19.4352.61Mar-201678%368.48286.6867%309.09206.9911%59.3979.69Apr-201677%370.92286.3579%399.71314.49-1%-28.79-28.14May-201675%366.44276.3070%332.28231.096%34.1645.20Jun-201678%379.92294.4471%336.62237.537%43.3056.90Jul-201678%385.24299.3375%363.59274.422%21.6524.92Aug-201673%366.68268.0465%356.56230.598%10.1237.45Sep-201674%371.67273.9282%491.75405.47-9%-120.08-131.55Oct-201676%386.01294.9177%381.89295.50-1%4.12-0.59Nov-201672%364.67262.9369%325.71225.273%38.9637.66Dec-201674%373.34274.4069%332.99230.464%40.3543.952017Jan-201765%389.02252.8661%324.24198.154%64.7854.72Feb-201766%390.45258.4869%349.58239.57-2%40.8718.91Mar-201769%389.78269.7364%297.66190.395%92.1279.34Apr-201768%381.81257.7267%310.87209.680%70.9448.05May-201767%382.30256.9175%338.52253.51-8%43.783.39Jun-201769%381.30264.6268%324.15220.341%57.1544.28Jul-201771%381.33269.2280%363.39289.93-9%17.94-20.71Aug-201769%380.47262.5276%347.33262.78-7%33.14-0.26Sep-201770%383.12268.5785%509.22432.44-15%-126.10-163.88Oct-201773%384.33282.1077%393.24304.19-4%-8.91-22.09Nov-201769%383.06265.8471%312.99222.38-2%70.0743.47Dec-201772%383.38274.5075%338.39253.54-3%44.9920.962018Jan-201863%382.10241.4961%308.69188.722%73.4152.77Feb-201864%382.67243.3862%357.09222.701%25.5820.68Mar-201867%382.53255.1564%297.12189.423%85.4165.73Apr-201866%382.79253.4171%319.18227.33-5%63.6126.08May-201865%382.44247.8267%333.26223.25-2%49.1824.57Jun-201868%383.97259.9576%344.24260.47-8%39.73-0.52Jul-201869%382.89264.1986%352.76301.78-17%30.13-37.58.
Alan Clayton-Matthews and Alicia Sasser Modestino of The
Dukakis Center for Urban & Regional Policy presented on the Massachusetts Economy for recent graduates
The inaugural NACAS Benchmarking Study is an importnt study conducted by NACAS for its members. The survey collects key trending and financial information on auxiliary services across college campuses. This report is designed to allow college service leaders to easily compare their auxiliary services offerings with their industry peers.
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Obamacare in Pictures: Visualizing the Effects of the Patient Protection and ...The Heritage Foundation
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Orr's model vi projection of cases to 4 16-2020 created 04-03-2020James Orr
This is the latest weekly update of my projection of Coronavirus Cases over the next fourteen days. Projection two weeks ago was too low (assumed control of spread). Projection on week ago assumed no change in Growth Rate % of cases per day. This version used trend in Growth Rate % cases per day to extrapolate reducing Growth Rate per day over the next 14 days. This should be much more accurate if continued progress in "social distancing" occurs.
The U.S. Nursing Labor Market Report 2014Identified
This slideshare provides a summary of research on the U.S. nursing labor market. Designed to assist employers in understanding the market influences affecting recruitment, it also highlights some of the drivers employers are using to attract and retain top nursing talent.
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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).
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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.
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Adding complexity to an already difficult task monitoring the impact of the affordable care act (ACA) on the misreporting of medicaid coverage
1. Brett Fried
Minnesota Health Services Research Conference
March 1, 2016
ADDING COMPLEXITY TO AN ALREADY
DIFFICULT TASK: MONITORING THE
IMPACT OF THE AFFORDABLE CARE
ACT (ACA) ON THE MISREPORTING OF
MEDICAID COVERAGE
3/2/2016
2. Acknowledgments
3/2/2016 2
Funding for this work is supported by the Robert Wood
Johnson Foundation.
Other Contributors:
Michel Boudreaux (University of Maryland), Kathleen Call,
Elizabeth Lukanen & Giovann Alarcon (SHADAC)
3. Background
3/2/2016 3
Administrative data on public assistance programs are not
sufficient for policy making
• Often not timely
• No population denominator
• Incomplete, lower quality or no covariates
Population surveys fill these gaps
• Yet they universally undercount Medicaid enrollment
(Call et al 2008, 2012, Boudreaux 2015)
4. Research focus
Compare Medicaid counts pre and post ACA
• Use accessible timely data that is used by state
analysts, policymakers and the public
• Check for levels of differences across states
• Check for patterns of differences in states
3/2/2016 4
5. Research Question
Has there been an increase in differences
between survey data and administrative data of
Medicaid enrollment data in some states?
3/2/2016 5
6. Survey Data Source: American
Community Survey (ACS)
• Large, continuous, multi-mode survey (mail, telephone, in-
person and internet) of the US population residing in
housing units and group quarters
• Added health insurance question in 2008
• One simple multi-part question on health insurance type
• Unique data source due to its size
• Subgroup analysis (small demographic groups and low
levels of geography)
• Chose this source because so commonly used for state-
level analysis
• Previous research shows false negative error rate
compares favorably with the NHIS and CPS (Boudreaux
2015)
3/2/2016 6
7. ACS Health Insurance
Question
3/2/2016 7
“Is this person CURRENTLY covered by any of the
following types of health insurance or health coverage
plans?
d. Medicaid, Medical Assistance, or any kind of
government-assistance plan for those with low
incomes or a disability?”
8. Data used from ACS
From prepopulated publicly available tables from the
Census.
Universe: Civilian Non-Institutional Population
3/2/2016 8
9. Administrative Data Source: Centers
for Medicare and Medicaid Services
Enrollment Definition
• A point-in-time count (like ACS)
• Medicaid and CHIP (like ACS)
• Only those eligible for comprehensive benefits (like
ACS)
• Includes those with retroactive eligibility (not like ACS)
• Universe: All individuals in the population (not like
ACS)
3/2/2016 9
10. Compare ACS and CMS Medicaid
enrollment estimates
Change between 2013 and 2014
• National
• Top and Bottom Ten States
• Expansion and Non-Expansion
3/2/2016 10
11. Table 1. ACS & CMS Medicaid Enrollment Increase in
the TOP Ten States from 2013 to 2014
Top ten states with the largest increases in enrollment according to CMS
3/2/2016 11
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period.
ACS CMS
2014 2013 % diff
Rank
ACS 2014 2013 % diff
Rank
CMS
U.S. 59,390,221 54,761,806 8% NA 66,102,081 57,794,096 14% NA
Minnesota 894,631 779,201 15% 11 1,068,305 873,040 22% 12
Top Ten 7,589,644 6,192,146 23% NA 8,642,487 5,882,920 47% NA
1. Kentucky 1,030,312 790,497 30% 3 1,048,285 606,805 73% 1
2. Oregon 897,812 662,038 36% 1 997,762 626,356 59% 2
3. Nevada 460,893 350,778 31% 2 527,929 332,560 59% 3
4. New Mexico 569,340 504,346 13% 13 705,128 457,678 54% 4
5. West Virginia 455,637 357,427 27% 4 519,672 354,544 47% 5
6. Colorado 923,438 749,060 23% 5 1,106,134 783,420 41% 6
7. Arkansas 698,344 626,626 11% 15 784,335 556,851 41% 7
8. Washington 1,301,760 1,075,157 21% 7 1,542,789 1,117,576 38% 8
9. Rhode Island 225,341 183,978 22% 6 259,183 190,833 36% 9
10. Maryland 1,026,767 892,239 15% 10 1,151,270 856,297 34% 10
12. Table 2. ACS & CMS Medicaid Enrollment Increase in
the BOTTOM Ten States from 2013 to 2014
Bottom ten states with the smallest increases in enrollment according to CMS
3/2/2016 12
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period.
ACS CMS
2014 2013 % diff
Rank
ACS 2014 2013 % diff
Rank
CMS
U.S. 59,390,221 54,761,806 8% NA 66,102,081 57,794,096 14% NA
Bottom Ten 7,902,691 7,810,077 1% NA 8,305,768 8,280,296 0% NA
1. Missouri 851,286 879,277 -3% 5 812,785 846,084 -4% 1
2. Nebraska 243,448 239,516 2% 13 238,609 244,600 -2% 2
3. South Carolina 922,282 869,054 6% 25 868,487 889,744 -2% 3
4. Virginia 928,396 895,945 4% 18 937,493 935,434 0% 4
5. Wyoming 71,757 62,780 14% 40 67,858 67,518 1% 5
6. South Dakota 118,349 125,267 -6% 2 116,174 115,501 1% 6
7. Pennsylvania 2,126,553 2,086,242 2% 14 2,417,392 2,386,046 1% 7
8. Louisiana 995,134 986,950 1% 9 1,037,136 1,019,787 2% 8
9. Oklahoma 662,792 666,429 -1% 8 803,577 790,051 2% 9
10. Wisconsin 982,694 998,617 -2% 7 1,006,257 985,531 2% 10
13. Table 3. ACS & CMS Medicaid Enrollment Differences
in the TOP Ten States in 2013 & 2014
Top ten states with the largest increases in enrollment according to CMS
3/2/2016 13
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period for these two states.
2014 2013
ACS CMS diff % diff ACS CMS diff % diff
U.S. 59,390,221 66,102,081 -6,711,860 -10% 54,761,806 57,794,096 -3,032,290 -5%
Minnesota 894,631 1,068,305 -173,674 -16% 779,201 873,040 -93,839 -11%
Top Ten 7,589,644 8,642,487 -1,052,843 -12% 6,192,146 5,882,920 309,226 5%
1. Kentucky 1,030,312 1,048,285 -17,973 -2% 790,497 606,805 183,692 30%
2. Oregon 897,812 997,762 -99,950 -10% 662,038 626,356 35,682 6%
3. Nevada 460,893 527,929 -67,036 -13% 350,778 332,560 18,218 5%
4. New Mexico 569,340 705,128 -135,788 -19% 504,346 457,678 46,668 10%
5. West Virginia 455,637 519,672 -64,035 -12% 357,427 354,544 2,883 1%
6. Colorado 923,438 1,106,134 -182,696 -17% 749,060 783,420 -34,360 -4%
7. Arkansas 698,344 784,335 -85,991 -11% 626,626 556,851 69,775 13%
8. Washington 1,301,760 1,542,789 -241,029 -16% 1,075,157 1,117,576 -42,419 -4%
9. Rhode Island 225,341 259,183 -33,842 -13% 183,978 190,833 -6,855 -4%
10. Maryland 1,026,767 1,151,270 -124,503 -11% 892,239 856,297 35,942 4%
14. Table 4. CMS & ACS Medicaid Enrollment Differences
in the BOTTOM Ten States in 2013 & 2014
Bottom ten states with the smallest increases in enrollment according to CMS
3/2/2016 14
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period.
2014 2013
ACS CMS diff % diff ACS CMS diff % diff
U.S. 59,390,221 66,102,081 -6,711,860 -10% 54,761,806 57,794,096 -3,032,290 -5%
Bottom Ten 7,902,691 8,305,768 -403,077 -5% 7,810,077 8,280,296 -470,219 -6%
1. Missouri 851,286 812,785 38,501 5% 879,277 846,084 33,193 4%
2. Nebraska 243,448 238,609 4,839 2% 239,516 244,600 -5,084 -2%
3. South Carolina 922,282 868,487 53,795 6% 869,054 889,744 -20,690 -2%
4. Virginia 928,396 937,493 -9,097 -1% 895,945 935,434 -39,489 -4%
5. Wyoming 71,757 67,858 3,899 6% 62,780 67,518 -4,738 -7%
6. South Dakota 118,349 116,174 2,175 2% 125,267 115,501 9,766 8%
7. Pennsylvania 2,126,553 2,417,392 -290,839 -12% 2,086,242 2,386,046 -299,804 -13%
8. Louisiana 995,134 1,037,136 -42,002 -4% 986,950 1,019,787 -32,837 -3%
9. Oklahoma 662,792 803,577 -140,785 -18% 666,429 790,051 -123,622 -16%
10. Wisconsin 982,694 1,006,257 -23,563 -2% 998,617 985,531 13,086 1%
15. Table 5. CMS & ACS Medicaid Enrollment in
Expansion & Non-Expansion states in 2013 & 2014
States only included as expansion states if the Medicaid expansion occurred before
2015
3/2/2016 15
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period.
2014 2013
ACS CMS diff %diff ACS CMS diff % diff
U.S. 59,390,221 66,102,081 -6,711,860 -10% 54,761,806 57,794,096 -3,032,290 -5%
Expansion 34,566,180 40,999,907 -6,433,727 -16% 30,613,383 33,852,915 -3,239,532 -10%
Non-Expansion 24,824,041 25,102,174 -278,133 -1% 24,148,423 23,941,181 207,242 1%
16. Figure 1. Are differences between the ACS and CMS in
2014 higher in states that had more new Medicaid
enrollment? (1)
Increase in enrollment is between 2013 and 2014 in the CMS
3/2/2016 16
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period.
KY
NV
NM
OR
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
-10.0% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%
Percentdifferencebetween2014CMSand2014
ACSenrollmet
Percent change in CMS Medicaid enrollment between 2013 and 2014
Percent difference between 2014 ACS and 2014 CMS Medicaid enrollment as
compared to Increase from 2013 and 2014
17. FIGURE2. Are differences between the Adjusted ACS and
CMS in 2014 higher in states that had more new
Medicaid enrollment? (2)
Adjustment made to 2014 ACS to account for difference between 2013 CMS and 2013 ACS Medicaid
enrollment
3/2/2016 17
Source: CMS, Medicaid & CHIP Monthly Applications, Eligibility Determinations, and Enrollment Reports: July 2014 and July- September 2013 available from
Kaiser at http://kff.org/health-reform/state-indicator/total-monthly-medicaid-and-chip-enrollment. ACS, American Factfinder, Table S2701, 1 year
estimates
Note: Excludes both Connecticut and Maine enrollment from totals because no data was available from CMS for the 2013 time period. Adjustment is the
difference between the CMS and ACS 2013 enrollment by state subtracted this from 2014 ACS enrollment.
NM
NV
OR
KY
-20.0%
-10.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
-10.0% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%
Percentdifferencebetween2014CMSand
adjusted2014ACSenrollmet
Percent change in CMS Medicaid enrollment between 2013 and 2014
Percent difference between 2014 Adjusted ACS and 2014 CMS Medicaid
enrollment as compared to increase between 2013 and 2014
18. SUMMARY
In general, states with the largest percent increases in
enrollment also have the largest differences between ACS and
CMS
This could be because
• New Medicaid enrollees are less likely to know they are
enrolled than people who have been enrolled for a longer
period
• New Medicaid enrollees have different characteristics that
are more associated with reporting error
• Retroactive enrollment could be higher in 2014
3/2/2016 18
19. Policy implications
• Potentially overstating uninsurance rates
particularly in states with large changes in
enrollment but by how much?
• Past research has shown that most misreports
are other types of coverage, not uninsurance
• “No wrong door” could mean these errors are
also mostly between coverage types
• Research comparing coverage in states may
be biased because of potential for larger error
associated with states with larger increases in
enrollment
3/2/2016 19
20. Future research
• Run the same analysis for the NHIS and CPS
• Add more years of data going back at least
five years
• Include institutional and active military
population in the ACS using the PUMS file.
• Check differences in characteristics between
new and “old” enrollees using the PUMS file
• Link the administrative and survey data when
linkable data becomes available
3/2/2016 20