Research Project to Understand the Medicaid Undercount: The University of Minnesota’s State Health Access Center, the Centers for Medicare and Medicaid Services, the Department of Health and Human Services Assistant Secretary for Planning and Evaluation, The National Center for Health Statistics, and the U.S Census Bureau Phase II Research Results: Examining Discrepancies between the National Medicaid Statistical Information System (MSIS) and the Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) Final March 12, 2008 Note: This paper was made possible by grant 052084 from the Robert Wood Johnson Foundation to the State Health Access Data Assistance Center (Michael Davern, PI) with additional support supplied by the Office of the Assistant Secretary for Planning and Evaluation (ASPE), the Center's for Medicare and Medicare Services (CMS), and the U.S. Census Bureau. This paper has undergone a limited review by all the participating organizations in accordance to existing agreements among these organizations. The views expressed are those of the author(s) and not necessarily those of ASPE, CMS, or the US Census Bureau.
Transcript
Research Project to Understand the Medicaid Undercount: The University of Minnesota’s State Health Access Center, the Centers for Medicare and Medicaid Services, the Department of Health and Human Services Assistant Secretary for Planning and Evaluation, The National Center for Health Statistics, and the U.S Census Bureau
Phase II Research Results: Examining Discrepancies between the National Medicaid
Statistical Information System (MSIS) and the Current Population Survey (CPS) Annual Social and Economic
Supplement (ASEC)
Final March 12, 2008
Note: This paper was made possible by grant 052084 from the Robert Wood Johnson Foundation to the State Health Access Data Assistance Center (Michael Davern, PI) with additional support supplied by the Office of the Assistant Secretary for Planning and Evaluation (ASPE), the Center's for Medicare and Medicare Services (CMS), and the U.S. Census Bureau. This paper has undergone a limited review by all the participating organizations in accordance to existing agreements among these organizations. The views expressed are those of the author(s) and not necessarily those of ASPE, CMS, or the US Census Bureau.
Contents
Executive Summary................................................................................................... ii
I. INTRODUCTION.............................................................................................................1
II. OBJECTIVE AND SCOPE................................................................................................1
III. METHODOLOGY AND QUESTIONS ANSWERED............................................................2
IV. RESULTS OF ANALYSIS...............................................................................................11
V. CONCLUSION ..............................................................................................................16
VI. LIMITATIONS..............................................................................................................16
I. Description of Four Project Phases........................................................................18 II. Key Decisions Leading to Phase II Research Design............................................18 III. Files and Methods Used.........................................................................................18 IV. Meta Data in Phase II.............................................................................................18 V. Detailed Tables and Documentation......................................................................18
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Executive Summary
Survey estimates of public health insurance program enrollment tend to be lower than those compiled from administrative record data. This discordance is particularly apparent for Medicaid and this has become known as the “Medicaid undercount”. Many causes have been postulated for the undercount with varying potential implications for policy research and resulting policy recommendations. The crude Medicaid undercount in the Current Population Survey’s Annual Social and Economic Supplement (CPS ASEC), the most prominently used survey for policy research that measures health insurance coverage, was about 32 percent for both 2000 and 2001.1 In order to investigate reasons for the undercount, a team of researchers designed the analysis described in this report.
For this analysis, Centers for Medicare & Medicaid Services (CMS) provided the Census Bureau with a Social Security Number (SSN)-identified version of its Medicaid Statistical Information System (MSIS) files for 2000, 2001, and 2002. Following appropriate person-identity confirmation, record linkage, data security, and personal privacy protection procedures, Census staff joined the corresponding individual-level MSIS information to the Census internal CPS files for 2001 and 2002 at the person level.
By analyzing the resulting data files, we were able to identify two general causes of the Medicaid undercount. The first relates to difficulties aligning the concept of which persons are enrolled on MSIS and CPS. And the second relates to problems existing in the CPS survey data.
Problems Aligning the Concept of Coverage Between the MSIS and CPS ASEC: To make the concept of insurance and Medicaid coverage consistent across the MSIS and the CPS, we removed all MSIS enrollees who received only partial coverage (e.g., those receiving just emergency or family planning related services). We also removed enrollees who were on Medicaid in the previous year but died before the period of CPS fielding, and duplicate person records (e.g., usually due to receipt of Medicaid by the same person in two different states in a given calendar year). Finally, we removed all State Children's Health Insurance Program (SCHIP) enrollees from the MSIS count as SCHIP falls under the auspices of Medicaid only in some states and within those states sometimes inconsistently, and we presume SCHIP-participating families often are unaware of the distinction. After these adjustments, our analysis file had 40.5 million Medicaid enrollees in 2001, down from a 48.6 million in the full MSIS file. Corresponding figures for 2000 were 38.2 million and 45.0 million.
1 Based on CPS estimates of the number of people with Medicaid and MSIS administrative data counts tabulated in the second phase of our research project. Our revised MSIS estimates for 2000 indicated that 38.2 million people had full benefits Medicaid compared with 26.1 million estimated by the CPS. In 2001 our revised MSIS estimates indicated that 40.5 million people were enrolled in full benefits Medicaid versus 27.7 million in the CPS.
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Sources of the Discrepancy Attributed to the Survey Data: Most of the remaining undercount appears to be explained by response error. We explored response error using those survey reportees for whom we had actual health insurance coverage responses (i.e., excluding imputed and allocated responses). Among the linked cases between the CPS and MSIS (i.e., when enrollment is indicated on MSIS for a CPS participating household member), we computed that 41 percent of these enrollees were not reported having Medicaid. Further computation led us to conclude that such response errors in the CPS are the major cause of the Medicaid undercount.
Also, these response errors appear to occur non-randomly. People with longer and more recent Medicaid enrollment (including those still enrolled in the CPS during the first four months of the year of the survey fielding—which is the one immediately subsequent to the one being asked about on the survey—were reported on better. Those enrolled later in the reference period (closer to the time of the survey), those enrolled at the time of the survey (which should not be relevant if respondents correctly interpret the CPS Medicaid coverage questions), and those enrolled for more days in the calendar year were more likely to be reported having Medicaid. Response errors also appear related to income and age. Respondents for enrolled children were more likely to report Medicaid coverage for them than those for adult enrollees. Enrollees in families with lower incomes were more likely reported on Medicaid (and less likely reported on some other type of coverage) and enrollees with higher income were less likely reported on Medicaid (but were more likely to be reported on some other type of coverage). Also enrollees receiving medical services provided by Medicaid in the periods under analysis (calendar years 2000 and 2001, separately) were more often reported enrolled than those who did not receive services. Finally, enrollees in some states were more likely reported so and less likely reported being uninsured (e.g., Massachusetts) than persons in other states (e.g., Louisiana).
Limitations of Our Study: This report presents intermediate results from ongoing research. Although we did reweight to CPS data to partially adjust for the non-representativeness of the linkable CPS sample (i.e., those with PIKs), some bias undoubtedly remains. For example, the reweighted sub-sample of linkable cases makes no correction for missing PIKs in the administrative data. More research should be conducted on this 6 percent of the MSIS full benefits Medicaid enrollee cases to determine the role they play in the Medicaid undercount.
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I. Introduction
This paper describes the results of the second phase of a four-phase research project of University of Minnesota’s State Health Access Data Assistance Center (SHADAC), Centers for Medicare and Medicaid Services (CMS), Assistant Secretary for Planning and Evaluation (ASPE), National Center for Health Statistics (NCHS), and the US Census Bureau. The research is designed to explain why discrepancies exist between survey estimates of enrollment in Medicaid and the number of enrollees reported in state and national administrative data.
The research done for this project includes both national and state-level analysis. National files include the Medicaid Statistical Information System (MSIS), the Medicaid Analytic eXtract (MAX), and the Medicare Enrollment Database (EDB). Survey files include the Current Population Survey (CPS) and the National Health Interview Survey (NHIS)2. Additionally, the following states have been invited to participate in this study: Florida, Maryland, California, Pennsylvania, New Jersey, Louisiana, and Minnesota. Participating states will provide data from their Medicaid and State Children's Health Insurance Program (SCHIP) enrollment files to CMS, and CMS will, in turn, provide these data to the U.S. Census Bureau.
Understanding differences between enrollment data and survey data will benefit the Census Bureau and other participating agencies by suggesting possible improvement to CPS and other surveys. It will also engender a better understanding of existing CPS insurance data that provide a more accurate view of Medicaid and other insurance coverage for U.S. residents. As such, this research will enable a revised computation of the number of U.S. residents without health insurance. We consider the results presented in this paper to form only a basis—a jumping-off point—for making such an analysis. Without a sophisticated strategy to reassign surveyed persons categorized by CPS as uninsured but established by this study to have Medicaid coverage that considers the effect of having non-randomly missing data and also the offsetting effect of false positive reporting, such a computation would likely be significantly inaccurate. We expect additional work released by team members to speak directly to this issue.
II. Objective and Scope
The objective of Phase II is to investigate the size and source of the discrepancy between estimates derived from the former Current Population Survey (CPS) March Supplement (now known as the Annual Social and Economic Supplement or ASEC) and counts of enrollees derived from MSIS. The input for this research is the validated MSIS and MAX files for calendar year (CY) 2000 and 2001 matched respectively to the 2001 and 2002 Current Population Survey March Supplements (ASEC), and the Census Bureau’s Master Address File Auxiliary Reference File (MAF-ARF) and Person Characteristics File (PCF). We also use MSIS enrollment data for the first four months subsequent to each survey’s reference period (which is
2 Description of these files can be found in Appendix III. 1
the calendar year immediately prior to the year of survey administration) because we conjecture that current and recent enrollment status (though not germane to the CPS questions about Medicaid coverage as worded) helps explain respondent reporting of Medicaid coverage.
To address explanations for discrepancies between CPS and enrollment reported in MSIS, we produced summary statistics intended to suggest or discredit plausible explanatory factors for it. We constructed a series of logistic models to evaluate these factors in a multivariate setting. Additionally, we provided a summary data file for team members to corroborate and extend our analysis. Phase II Metadata can be found in Appendix IV and detailed tables in Appendix V. The Appendix V tables appear each in two presentations: the first using the original CPS survey weights and the second using adjusted weights developed by a re-weighting process described in Appendix III, which also describes the research files and other methods used to produce the results.
III. Methodology and Questions Answered
File Processing to Create the Research File 1. Validate MSIS records using a modified version of the Census Bureau’s Person
Identification Validation System (PVS). The validation technique compares the date-of-birth and sex shown on the MSIS record to the date-of-birth and sex shown for that SSN on the Social Security Administration’s Numident file. The process works under the assumption that if the MSIS SSN were incorrect, it would be highly unlikely for the MSIS and Numident date-of-birth and sex to be similar. For validated records, convert the SSN to an anonymous Protected Identity Key (PIK) to protect the security of the personal information.
2. Use the MAF-ARF, which contains PIKs and Master Address File Identifiers (MAFIDs, each representing a specific place of residence) to determine persons who may have been out of the CPS universe because they lived in institutional group-quarters.
3. For each person in MSIS, determine the months during which that person was enrolled in Medicaid and output a record showing this to the MSIS Summarized Enrollment History File (MSEHF), which has a single record for each validated SSN on MSIS and a single record for each MSIS client account without a validated SSN.
4. Process CPS records through the PVS, which includes verification and search procedures, to assign a PIK.
5. Account for the CPS cases that are un-linkable because the (represented person’s) SSN is unknown or unverifiable. Create a new set of CPS weights by dropping these un-linkable cases and re-assigning their weight proportionally to records within the same re-weighting strata that do have identifying data. While the re-weighting strata are developed in a way meant to minimize bias in derived estimates, re-weighting would
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cause completely no bias only if person-identification data are missing-at-random3: that is to say, if the missing-ness of the identification data is statistically independent, within each re-weighting stratum, of any characteristic being measured. In the real world, this is unlikely to be true, and so, to the degree that the measured characteristics vary according to the missing-ness of the identity data, re-weighting could introduce bias into the generated estimates just as similar post-stratification adjustments made to all Census Bureau demographic households surveys can. Nevertheless, we believe that re-weighting is a way to project the results from the identified CPS reportees4 to the entire CPS frame.
6. Process the MAX data for the analysis year by validating the SSN (by comparison to matching MSIS record) and replacing it with a PIK.
7. Link MSEHF to CPS, the Person Characteristics File (PCF), and the processed MAX file, joining on PIK. Produce tabulations shown in Tables 1 and 2 (Appendix IV). Produce an analysis file with a single record for each person in CPS. Use this analysis file to produce tabulations for Tables 3 and 4 (Appendix IV) and to perform the regression analysis.
Assessing the feasibility of using record linkage to identify survey errors causing the discrepancy between the CPS March Supplement and the national MSIS
Q1: What is the status of the raw match between CPS observations and MSIS records?
Prior to accounting for universe differences and duplicate records, how many CPS and MSIS records have person-identifying data (PIK substituting for SSN) so we can determine the record’s type of match outcome and therefore use it in the analysis of the count estimate discrepancy? How does the analytical universe differ after we use adjusted weights to account for being unable to correctly determine type of match outcome for CPS records lacking identifying information?
We tally raw un-weighted and weighted counts of the number of CPS and MSIS records by type of match outcome. Counts are tallied overall and by selected characteristics. We use CPS demographic characteristics, poverty level, and health insurance coverage responses for CPS only and CPS-to-MSIS matched records. For MSIS only, we use PCF (or when PCF characteristics are unavailable, MSIS) demographic characteristics, and type of benefits. These tallies are presented in Appendix V, Table 1, which provides an overview of the match process.
3 Little, R. J. A., Rubin D.B., Statistical Analysis with Missing Data. 2nd Edition.Wiley, 2002. 4 In this document, “reportee” refers to all household members of reporting households; “respondent” refers only to the household members (one for each household) that took part in the survey interviews.
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Assessing the scope of the survey undercount
Q2: What is the size of the discrepancy between CPS and MSIS?
How does the CPS estimate of enrollees compare to the MSIS count of enrollees? How does it compare after making adjustments to account for universe differences? What is the distribution of the discrepancy between MSIS counts and CPS estimates by demographic category? How does this distribution vary among residents of different states?
We make the raw MSIS count of Medicaid enrollees by totaling the number of client accounts excluding persons known to be deceased prior to March of the corresponding survey year, and we make the CPS estimate by weighting each member of the households in CPS by the final survey weight and summing.
However, before comparing the MSIS count to the CPS estimate, we account for the differences in what each measure covers. Direct comparability is inappropriate for several reasons:
� Differences in the definition of enrollment - The raw MSIS count includes individuals in the State Children's Health Insurance
Program (SCHIP) if it is run through Medicaid (an arrangement called “Medicaid-expansion SCHIP”) and it only sometimes does include individuals in SCHIP if run separately from Medicaid (an arrangement called “stand-alone SCHIP”). States may offer one or both of these types of plans.
- In contrast, the CPS estimate made from the variable MCAID5 does always include individuals who are reported to have SCHIP coverage, regardless of their state of residence and type of SCHIP program. Our preferred measure of Medicaid coverage, (which is an augmented version of the CPS variable CAID6
(called subsequently Augmented-CAID7)) does not count Medicaid persons identified covered through SCHIP but not explicitly identified as enrolled in Medicaid8.
5 MCAID is set to show Medicaid coverage for a reportee if the respondent indicates (for the reportee) coverage on Medicaid or SCHIP when first asked (in response to direct questions about each possible type of coverage), indicates Medicaid, SCHIP, Other Public Coverage, or Other Coverage in response to being asked about additional coverage (subsequent to answering initial questions about each type), or indicates Medicaid, SCHIP, or Other Public Coverage in response to a verification question asked about each household member who had not been reported (earlier in the health insurance question sequence) having any coverage. The Census Bureau uses MCAID in computing published CPS estimates of prior year Medicaid enrollees. 6 CAID is set to show Medicaid coverage for a reportee if respondent indicates coverage on Medicaid in response to several direct questions (prior to being asked about any other coverage or verification of non-coverage) about Medicaid enrollment: whether any household members had Medicaid coverage, and if so, who in household had it.7 Augmented-CAID includes all reportees CAID shows enrolled and, in addition, reportees indicated with Medicaid coverage in response to questions asked about additional coverage or in response to a verification question asked about each household member who had not been reported having any coverage. 8 Many times SCHIP and Medicaid share the exact same program name (e.g., Hoosier Healthwise in Indiana) and as a result are inseparable in the self-reported health insurance data.
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- The raw MSIS count includes individuals receiving partial benefits (i.e., coverage only for selected services). In contrast, it is unclear if some respondents in the survey understand “coverage” as meaning having received at least some medical care provided by Medicaid. See Appendix II for details on how we decided to define coverage.
� Differences in the definition of universe
- The raw MSIS count includes residents of institutional group quarters. In contrast, the CPS estimates do not account for them because they are not part of the CPS sampling universe.
� Differences in the definition of the unit of measure
- The raw MSIS count is a measure of the total number of Medicaid client accounts and so individuals who have multiple client accounts (sometimes within the same state and sometimes in multiple states) are counted more than once. In contrast, the CPS estimates are a measure of the total number of individual enrollees.
For these reasons we adjusted the raw MSIS count to make the measures more comparable. Appendix V, Table 2 shows a progression of adjusted MSIS counts, working from the one least comparable to the one most comparable to CPS estimates. Each subsequent column represents an exclusion being made to work towards a universe more directly comparable and the exclusions are cumulative:
� “MSIS Total A” excludes only persons known dead prior to March of the survey year (For MSIS 2000-CPS/ASEC 2001, 853,000 dead persons were excluded; for MSIS 2001-CPS/ASEC-2002, 906,000 dead persons were excluded) from the raw counts of client accounts.
� With “MSIS Total B” SCHIP clients are excluded from the counts. � With “MSIS Total C” partial benefit clients are excluded from the counts. � With “MSIS Total D” clients likely to reside in institutional group quarters are excluded
from the counts.
Our methodology to exclude persons in group quarters reviews other administrative data files and excludes individuals at addresses we know to be of institutions. This methodology has several known shortcomings:
1. We cannot determine the identity (PIK substituting for SSN) of about 10% of enrollees shown on MSIS and therefore cannot look for institutional addresses for these persons.
2. Many persons (31.2% for 2000 and 29.2% for 2001) who are identified (by PIK) nevertheless cannot be located in our alternative administrative data.
3. Many residents of institutions are recorded in administrative records at previous addresses or at addresses of persons responsible for their affairs.
4. We cannot identify all institutional addresses as such.
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Because of these shortcomings, we believe this exclusion is of limited efficacy in identifying residents of institutional group quarters. Our intention is to more thoroughly attempt to account for these persons in our Phase III analysis.
� With “MSIS Total E” duplicative client accounts are excluded, and this count is of unique individuals as best as we can determine9.
We believe that “MSIS Total E” is the most similar to the estimate of Medicaid enrollees coming from CPS. Nonetheless, we did make a final exclusion: with “MSIS Total F” we exclude cases with missing person-identifying information to simplify reckoning of the source of discrepancy.
CPS data offer several different ways to compute estimates of Medicaid coverage, depending on the data users’ needs. We consider the discrepancy with MSIS in terms of three CPS estimates10:
� The first estimate [shown in Table 2 as “CPS Total A”] is a weighted tally of the MCAID variable. This is the variable that Census uses to generate Medicaid enrollee estimates. It is derived from a re-coding of several health insurance questions and categorizes persons identified as enrolled in Medicaid, SCHIP, other public coverage, and in some cases, simply “Other Coverage” as Medicaid enrollees. The estimate from MCAID can be considered a ceiling estimate for the number of Medicaid enrollees.
� The second estimate [shown in Table 2 as “CPS Total B”] is a weighted tally of the Augmented-CAID11 variable. Augmented-CAID is set to show Medicaid coverage
9 Dual state reportees are counted only once and are not assigned a state for the state-level tallies. To retain reconcilability of our CPS-generated estimates and control totals with published values, we have not removed these children from being included in the tables included with this report. We do not believe that any potential adjustment that could have been made to account for these children would materially impact conclusions drawn from the analysis presented in this paper. 10 It should be noted that, in some instances, respondents reported as “Medicaid enrolled in the reference year” children born subsequent to the reference year but prior to the survey interview. Certainly, these children could not have actually been enrolled in Medicaid during the reference year since they were not yet born, and therefore these are false positive reports. The original-weighted tally of these children is as follows:
Survey Year Reference Year CPS Column A CPS Column B CPS Column C 2001 2000 173,000 161,000 44,700 2002 2001 165,000 153,000 54,700
11 One significant difference between the Augmented-CAID variable (tallied in CPS Column B) and the MCAID variable (tallied in CPS Column A) is that MCAID variable is set (indicating Medicaid coverage) through the CPS coding procedure when a respondent indicates a child is enrolled in a State Children's Health Insurance Program (SCHIP), whereas this is not the case for the Augmented-CAID variable. In fact, some SCHIP programs, called Medicaid-expansion SCHIPs, are part of Medicaid, but others, called stand-alone SCHIPs, are not. Sometimes the CPS questionnaire fills are the exact same for SCHIP and Medicaid programs and sometimes not. Not all stand-alone SCHIP programs have a separate fill and not all Medicaid-expansion SCHIP programs share the same program name. Some states have one or the other of these types of programs, but some also have both, so not only is it quite likely that some respondents are uncertain about the Medicaid status of their children enrolled in these programs, but it is not straight-forward for analysts to determine if a CPS response indicating coverage in SCHIP should be identified as indicating Medicaid coverage as well. This is a limitation of our analysis, and should be considered when reviewing the tabulations in this report, particularly for persons under 18 years of age. It also suggests that neither MCAID (and Table 2, CPS Column A) nor Augmented-CAID (and Table 2, CPS Column B)
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whenever a reportee is explicitly described as having had Medicaid coverage or can be expected to have been so described if the respondent properly completed the health insurance question battery (in this case the response is said to be edited or imputed). The estimate from Augmented-CAID can be considered a floor estimate for the number of Medicaid enrollees.
� The third estimate [shown in Table 2 as “CPS Total C”] is a weighted tally of Augmented-CAID but only for explicit responses. Persons with Augmented-CAID set from an edit or imputation are specifically excluded from this tally so the tally should not be considered a valid estimate of the number of Medicaid enrollees. Instead it should be used to evaluate the degree to which the values under “CPS Total B” are derived from explicit reporting.
Assessing the cause of the count-estimate discrepancy
Q3: How did CPS respondents report health insurance status for individuals who are known Medicaid enrollees?
For individuals shown in MSIS to have had Medicaid coverage, how do their CPS Medicaid reports differ overall and categorically by various demographic characteristics, Medicaid enrollment patterns, other program participation, medical service utilization, and relationship to reference person12? How do these vary among enrollees whose Medicaid enrollment status was reported, edited, or imputed, and between enrollees with full benefits or any benefits?
From linked MSIS/CPS/MAX records, we generate Table 3 (Appendix V). Table 3 is presented in eight versions to show how reporting varies by source of health insurance data (reporting, imputation, or editing) and weighting schemes (using original weights or modified weights developed from the re-weighting process):
can be assumed to be better aligned conceptually with actual coverage in Medicaid, and likely there is some type of in-between classification and corresponding estimate that would be better.12 The reference person is the first person identified by the respondent as having their name on the title or lease of the residence.
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Table 3 Table 3 Version: Page #
Enrollees with Full Benefits:
A. Full Benefit Enrollees ...............................................................................1 - 3 B. Full Benefit Enrollees Whose CPS Insurance Status Was Edited ............4 - 6 C. Full Benefit Enrollees Whose CPS Insurance Status Was Imputed .........7 - 9 D. Full Benefit Enrollees Whose CPS Insurance Status Was Reported......10 - 12
Enrollees with Any Benefits:
E. All Enrollees ...........................................................................................13 - 15 F. All Enrollees Whose CPS Insurance Status Was Edited ........................16 - 18 G. All Enrollees Whose CPS Insurance Status Was Imputed .....................19 - 21 H. All Enrollees Whose CPS Insurance Status Was Reported ....................22 - 24
Q4: How did CPS respondents report health insurance status for individuals who are not known Medicaid enrollees?
For CPS reportees not known to be Medicaid enrollees (primarily if no matching MSIS record is found, but also if MSIS record found shows no Medicaid enrollment—for example, if the represented person is enrolled only under a stand-alone SCHIP), how does Medicaid enrollment reporting differ overall and categorically by various demographic factors, other program participation, and relationship to the reference person? How do these vary among reportees whose Medicaid enrollment status is reported, edited, or imputed and between matchable reportees (those with known SSN) and unmatchable reportees (those without known SSN)?
From CPS records unmatched to MSIS or matched to MSIS but not showing enrollment, we generate Table 4 in Appendix V. For the original weight presentation, we present Table 4 in eight versions. For the re-weighted presentation, since unmatchable reportees are assigned a zero weight, the versions for unmatchable reportees are suppressed because otherwise they would be filled with zeros. The remaining versions are identified identically to those in original weight presentation, but page numbering is altered.
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Orig. Wgt. Re-weighted Presentation Presentation
Table 4 Version: Page # Page #
Unmatchable Reportees:
A. All Unmatchable Reportees ...............................................1 – 2................ N/A B. Whose CPS Insurance Status Was Edited .........................3 – 4................ N/A C. Whose CPS Insurance Status Was Imputed.......................5 – 6................ N/A D. CPS Insurance Status Was Reported .................................7 – 8................ N/A
Matchable CPS Reportees not Known Receiving Medicaid:
E. All Reportees Not Known Receiving Medicaid ...............9 – 10...............1 – 2 F. Whose CPS Insurance Status Was Edited .......................11 – 12..............3 – 4 G. Whose CPS Insurance Status Was Imputed.....................13 – 14..............5 – 6 H. Whose CPS Insurance Status Was Reported ...................15 – 16..............7 – 8
Q5: What does multivariate modeling tell us about the relative strength of factors related to the odds of a discrepancy between CPS and MSIS?
What factors affect the odds a known enrollee is misreported as not having Medicaid coverage? What factors affect the odds a known non-enrollee is misreported as having Medicaid coverage? What factors affect the odds a known enrollee is misreported as having been uninsured? What factors affect the odds a person reported as not having coverage was found to be an enrollee? What factors affect the odds a person reported as having coverage was found to be an enrollee?
We specified a series of logistic regressions to model the odds of response error in reporting about Medicaid coverage in the CPS and to impute actual Medicaid enrollment status from CPS data:
Model 1a (n=38,400) Modeling Reported Not on Medicaid for Known Full Benefit Enrollees
Model 1a is a behavioral model of the event that the CPS respondent explicitly reported no Medicaid coverage (Augmented-CAID is not set) for an enrollee. The universe is CPS reportee whose insurance status was explicitly reported (i.e., not imputed or edited) and for whom MSIS shows received full Medicaid benefits during the survey reference period.
Model 1b (n=266,000) Modeling Reported on Medicaid for Reportees Whose Enrollment Count Not Be Confirmed in MSIS
Model 1b is a behavioral model of the event that the CPS respondent explicitly reported Medicaid coverage (Augmented-CAID is set) for a non-enrollee. The universe is CPS reportees with an explicit survey report about Medicaid and a PIK but no matching record found in MSIS. While this model is intended to explain the occurrence of false positive
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Medicaid reporting, it is important to note, that false positive reporting is only one reason why we could not confirm enrollment for these persons; this universe also includes persons whom we could not confirm enrolled because the MSIS records showing their enrollment are un-linkable (i.e., the SSN on those records were missing, wrong, or unverifiable). It is also possible that these persons had some other government sponsored health insurance coverage, such as from a stand-alone SCHIP, which are not actually part of the Medicaid program, but work in a similar way. For this reason, results from this model are more suggestive than conclusive about factors related to false positive reporting.
Model 2 (n=38,400) Modeling Reported Not Insured for Known Full Benefit Enrollees
Model 2 is a behavioral model of the event that the CPS respondent explicitly reported no insurance coverage (Medicaid or other types) for an enrollee. The universe is CPS reportees whose insurance status was explicitly reported (i.e., not imputed or edited) and for whom MSIS shows received full Medicaid benefits during the survey reference period. This model is identical in set-up to Model 1a, except the dependent variable is reported with no insurance rather that reported with no Medicaid coverage.
Model 3a (n=311,000) Modeling Enrolled with Full Benefits for Persons CPS Designated as Not Enrolled
Model 3a is an imputational model of the event that persons with no CPS designation (explicit, edited or imputed) of Medicaid coverage are found in MSIS to have received full Medicaid benefits. The universe is CPS reportees with Augmented-CAID not set.
Model 3b (n=35,200) Modeling Enrolled with Full Benefits for Persons CPS Designated as Enrolled
Model 3b is an imputational model of the event that persons with a CPS designation (explicit, edited, or imputed) of Medicaid coverage (Augmented-CAID is set) are found in MSIS to have received full Medicaid benefits. The universe is CPS reportees with a CPS designation of Medicaid coverage.
Covariates (showing file source and models used in) entered into the equations are:
• Age (Source: CPS; in Models 1a, 1b, 2, 3a, and 3b) • Enrolled in Survey Month (Source: MSIS; in Models 1a and 2) • Health Insurance Category Designated in CPS (Source: CPS; in Models 3a and 3b) • Intensity of Coverage (Source: MSIS; in Models 1a and 2) • Last Month of Coverage (Source MSIS; in Models 1a and 2) • Male (Source: CPS; in Models 1a, 1b, 2, 3a, and 3b) • Medicare Crossover (Source: MAX; in Models 1a and 2) • Private Insurance (Source: MAX; in Models 1a and 2) • Race/Hispanicity (Source: CPS; in Models 1a, 1b, 2, 3a, and 3b) • Ratio to Poverty Level (Source: CPS; in Models 1a, 1b, 2, 3a, and 3b) • Relationship to Survey Reference Person (Source CPS; in Models 1a, 1b, 2, 3a, and
3b) • Service (Source: MAX; in Models 1a and 2)
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• Source of CPS Insurance Data (Source: CPS; in Models 3a, and 3b) • SSI Recipient (Source: MSIS; in Models 1a and 2) • State (Source: CPS, MSIS; in Models 1b, 2, 3a, and 3b) • TANF (Source: MAX; in Models 1a and 2) • Zero Family Income Reported (Source: CPS; in Models 1a, 1b, 2, 3a, and 3b)
See Appendix III for complete variable specification.
IV. Results of Analysis
Note that results are analyzed in terms of enrollment during calendar year 2000 as reported in CPS/ASEC-200113. We believe that results for the subsequent year largely are consistent and can be explained in terms of the same factors.
Question 1:
Sample loss is a serious problem. Without creating new weights to account for invalid or missing SSNs, we would not be able to calculate a legitimate estimate of the undercount. More than one-fifth of the CPS sample cannot be used in the match analysis because respondents refused to provide an SSN for them or provided one that cannot be validated. There are 218,000 reportees (representing 279.5 million persons) for CPS/ASEC-2001. For 16,100 (representing 20.2 million persons), the SSN provided is invalid and for 28,200 (representing 45.5 million persons), the respondent did not provide one or allow a look-up. For this reason, we generated a second set of statistical tables that assign the weight of the unmatchable CPS sample to the matchable sample in a way intended to limit biases caused by re-weighting.
Question 2:
For CY 2000, the gross CPS underestimate of Medicaid enrollees is either 34.4%14 (if CPS MCAID variable is used) or 42.2%15 (if the Augmented-CAID variable is used). These rates are computed using a total count of 45,050,000 uniquely identified clients in the CY 2000 MSIS file (without a known date of death prior to March 2001). Direct comparability is obscured for several reasons discussed above (Under Section III, Q2). To make the MSIS count more
13 For this discussion, we present an analysis strictly of the count-estimate discrepancy that occurred in the 2001 CPS-ASEC sample, compared to MSIS reported Medicaid enrollment for calendar year 2000. As such, the results are not intended to provide guidance on how this count-estimate discrepancy would distribute had alternative samples been selected, and for this reason, the statistics are provided as point estimates without corresponding confidence intervals. Nevertheless, such confidence intervals can be estimated by following the guidance provided in this document: http://www.census.gov/hhes/www/income/p60_231sa.pdf (see page 7). 14 1 – [29,550,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, CPS Total A) / 45,050,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, MSIS Total A)]. 15 1 – [26,050,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, CPS Total B) / 45,050,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, MSIS Total A)].
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comparable to the CPS Medicaid enrollment estimates; adjustments are made as follows for MSIS 2000:
1. Remove from count clients enrolled under SCHIP: reducing the MSIS count to 43,650,000 (Table 2, CY 2000, Original Weight, U.S. Total, Total, MSIS Total B).
2. Remove clients not receiving full benefits: reducing the MSIS count to 39,750,000 (Table 2, CY 2000, Original Weight, U.S. Total, Total, MSIS Total C).
3. Removing clients residing in group-quarters: reducing the MSIS count to 39,600,000 (Table 2, CY 2000, Original Weight, U.S. Total, Total, MSIS Total D).
4. Removing duplicate client accounts: reducing the count to 38,150,000 (Table 2, CY 2000, Original Weight, U.S. Total, Total, MSIS Total E).
Using this count, we find that CPS underestimates Medicaid enrollment by either 22.6%16
with MCAID or 31.7%17 with Augmented-CAID. An additional value of 36,200,000 (Table 2, CY 2000, Original Weight, U.S. Total, Total, MSIS Total F), excludes UN-identified clients from the previous. This simplifies reckoning the source of discrepancy by excluding non-linkable MSIS clients from consideration. By correspondingly excluding unlinked CPS reportees as well as those with edited or imputed responses for Augmented-CAID, the Augmented-CAID count is reduced to 18,600,000 (Table 2, CY 2000, Original Weight, U.S. Total, Total, CPS Total C).
16 1 - 29,550,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, CPS Total A) / 38,150,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, MSIS Total E). 17 1 - 26,050,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, CPS Total B) / 38,150,000 (CY 2000, Table 2, Original Weight, U.S. Total, Total, MSIS Total E).
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Excluding non-matchable MSIS records and non-matched CPS records, the discrepancy between the MSIS count and the Augmented-CAID estimate is 36.2 M18 – 19.119 M = 17.1 M. Of this, 33.420 M – 19.1 M = 14.3 M is due to the misclassification of Medicaid enrollment status among known Medicaid enrollees. This accounting is non-authoritative, but shows that the predominating factor associated with the discrepancy is the CPS misclassification of Medicaid enrollment status. We can disaggregate the misclassification among known Medicaid enrollees as follows:
Total Enrollment Status Discrepancy............................14.3 M
Because imputation is meant to match reality at the aggregate level and not the individual level, the discrepancy attributable to imputation is to be expected and is offset by persons imputed to be enrolled, but not enrolled, which may be as high as 2.6 M23 Also, because imputation is modeled solely from CPS interview responses, the discrepancy likely results directly from respondent misreports.
This failure to correctly report Medicaid for known enrolled reportees causes CPS to overestimate the number of U.S. residents with no insurance. Since these misreported reportees are counted (on a weighted basis) as non-insured rather than Medicaid-insured, an improved estimate of non-insured residents would re-classify them out of the uninsured category. In addition to the enrolled reportees we know are misclassified by CPS, there likely are enrollees whom we cannot identify as misclassified because we do not know their identity (that is PIK, replacing SSN) so cannot see that they too had been enrolled. But, it is also reasonable to expect that there are reportees who are classified as insured when they are not, which partially offsets the underestimation caused by those for whom Medicaid coverage is not reported. An improved estimate of uninsured persons would need to take into proper account all these factors. The team will release such an accounting subsequently to this report.
18 CY 2000, Table 2, Original Weight, U.S. Total, Total, MSIS Total F. 1913,350,000 (CY 2000, Table 3, Re-Weighted, Version A, Total Weighted Count, Persons Reporting Medicaid Only) + 5,740,000 (CY 2000, Table 3, Re-Weighted, Version A, Total Weighted Count, Persons Reporting Medicaid and Other Coverage). 20 CY 2000, Table 3, Re-Weighted, Version A, Total Weighted Count, Total. 21 26,750,000 (CY 2000, Table 3, Re-Weighted, Version D, Total Weighted Count, Total) - 11,700,000 (CY 2000, Table 3, Re-Weighted, Version D, Total Weighted Count, Persons Reporting Medicaid Only) – 4,020,000 (CY 2000, Table 3, Re-Weighted, Version D, Total Weighted Count, Persons Reporting Medicaid and Other Coverage). 22 5,140,000 (CY 2000, Table 3, Re-Weighted, Version C, Total Weighted Count, Total) – 880,000 (CY 2000, Table 3, Re-Weighted, Version C, Total Weighted Count, Persons Reporting Medicaid Only) – 920,000 (CY 2000, Table 3, Re-Weighted, Version C, Total Weighted Count, Persons Reporting Medicaid and Other Coverage). 23 960,000 (CY 2000, Table 4, Re-Weighted, Version G, Total Weighted Count, Persons Reporting Medicaid Only) + 1,600,000 (CY 2000, Table 4, Re-Weighted, Version G, Total Weighted Count, Persons Reporting Medicaid and Other Coverage).
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Question 3:
Table 3, CY 2000 Expanded Sample, Re-Weighted, Version D (in Appendix IV) shows that misreporting increases as poverty, recentness of enrollment, and length of enrollment diminish. The chart below shows a clear trend relating reported enrollment and poverty level:
Percentage Reported Enrolled Among Known CY 2000 Medicaid Enrollees Receiving Full Benefits
0
20
40
60
80
0 - 49% 50 - 74% 75 - 99% 100 -124%
125 -149%
150 -174%
175 -199%
200%+
Ratio to Poverty Level
Perc
enta
ge R
epor
ted
Enro
lled
Figure 1. CY 2000 Medicaid Enrollees Receiving Full Benefits – Ratio to Poverty Level
Also, we see marked trends showing that enrollment is better reported the earlier that enrollment was initiated, or if the person is no longer enrolled, the later enrollment was terminated:
Percentage Reported Enrolled Among Known CY 2000 Medicaid Enrollees Receiving Full Benefits
0
20
40
60
80
1 2 3 4
CY 2000 Quarter
Perc
enta
ge R
epor
ted
Enro
lled
Not Enrolled When Surveyed (As of) Enrolled When Surveyed (Since)
Figure 2. CY 2000 Medicaid Enrollees Receiving Full Benefits – By Quarter
Related to the above trend, there appears to be a relationship between the number of days that a person was enrolled in Medicaid and the correct reporting of that enrollment for CPS:
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Percentage Reported Enrolled Among Known CY 2000 Medicaid Enrollees Receiving Full Benefits
0
20
40
60
80
< 61 61 - 180 > 180
Days Enrolled CY 2000
Perc
enta
ge R
epor
ted
Enro
lled
Enrolled in Survey Year Not Enrolled in Survey Year
Figure 3. CY 2000 Medicaid Enrollees Receiving Full Benefits – Days Enrolled in CY 2000
Also notable is that enrollment is better reported for persons enrolled in the year the survey was administered compared to reportees who were no longer enrolled.
Another blatant result emerging from review of Table 3 is that the correct reporting rate of enrollees in a fee-for-service plan receiving medical services in calendar year 2000 is 61.1%, but for those not receiving medical services it is 27.2%. Similar differences are seen for persons enrolled in managed care:
Percentage Reported Enrolled Among Known CY 2000 Medicaid Enrollees
0
20
40
60
80
No Managed Care Some Managed Care*
Type of Coverage
Perc
enta
ge R
epor
ted
Enro
lled
Medical Service Not Noted (*Not all Managed Care Services are Captured in MAX)
Medical Service Received
Figure 4. CY 2000 Medicaid Enrollees – Coverage Type
To attempt to isolate the effect of the factors the tables above show are important in the bivariate setting, we perform multivariate analyses and report the results below
Question 5:
The results from the regression analysis are presented in Appendix V, Table 5.
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V. Conclusion
Our research shows the CPS underestimates are mainly a reporting error problem: Reportees on Medicaid during the reference period are often reported as not having been covered by it. Some even report being uninsured but the majority of the misclassified cases report some other type of coverage just not Medicaid. Our regression analysis shows that the major predictors of coverage are length of time, recency and poverty level.
Our research is limited by the fact that we were not able to attempt a link with all the MSIS cases due to missing identifiers on about 10% of the records. We could also not attempt to link all of the CPS cases due to missing identifiers (26% or so). Additional work is being done to see (through modeling) how our results reported here would be different if we had linking data for all data records. Also, we are conducting an investigation into how the universes from the CPS and MSIS match up with respect to institutional group quarters (Phase III of this project). With Phase IV, we plan to compare the results from the CPS to the NHIS.
VI. Limitations
Our ability to draw conclusions is limited by the quality of our input files, particularly MSIS, the success and accuracy of the algorithms (within the Person Identity Validation System—PVS) used to identify people on MSIS and CPS, and CPS sample error.
In Phase I of this study we investigated the quality of the MSIS file. The MSIS has some known quality limitations: incomplete and incorrect person identification (using the SSN field), person duplication (within and among states), and, from the perspective of our analysis, the inclusion of institutionalized persons, who are out of scope for the Current Population Survey. We have attempted to mitigate these factors in this analysis, but to a certain degree they impact results of the analysis presented here.
This issue of non-identification is serious and occurs also on CPS data and we will discuss this subsequently in this section (two paragraphs down). Duplication on MSIS is largely manageable by counting only once for persons with multiple client accounts, when the duplication is apparent (that is, the records have a common PIK, which replaces SSN). To the degree that we cannot perform this un-duplication because we do not recognize that several client accounts belong to the same person, our count of MSIS enrollees will be somewhat overstated. Also tending to cause an overstatement is the inclusion of institutionalized Medicaid enrollees within the MSIS file. We have sought to mitigate this issue through a procedure that looks to see if addresses available for MSIS enrollees on alternative available administrative record data are for institutions. However, we believe that this procedure was largely inadequate (see the discussion in Section III under Q2) and will attempt a better accounting for these CPS-out-of-scope persons in the Phase III analysis.
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In addition to the known MSIS quality factors, the accuracy of MSIS in describing the enrollment status of Medicaid enrollees is critical to the validity of this analysis. To some degree we were able to review the quality of the MSIS in this regard in the Phase I analysis by looking at the quality of its geographic and dual-eligibility coding. These suggest that MSIS enrollment data are of high quality. However any inaccuracies in MSIS enrollment data will propagate to our generated statistics.
We believe that our person-identification routines (which seek to identify each person record with a unique PIK) perform with little error because the quality of their results have been continually evaluated over several years of use with varying types of data. Nevertheless, the lack of complete link-identification data (SSN re-coded as PIK) on both the CPS and MSIS mean that statistics derived from the status of the match of these files need to be carefully interpreted. Non-identified CPS reportees cannot have their enrollment status confirmed or established by reference to MSIS. For this reason, prior to re-weighting, non-identified CPS records are not useful for analyzing the accuracy of CPS reported Medicaid enrollment status, and the identified CPS records do not represent the whole CPS frame: non-institutionalized U.S. residents. Re-weighting corrects for this incomplete representation by shifting weight from the non-identified to identified reportees, but this introduces bias to match-derived statistics to the (unknown) degree that the missing-at-random assumption does not hold within the re-weighting strata. Non-identification within MSIS means that persons reported Medicaid-enrolled to CPS but not confirmed so by the match, may potentially be actual enrollees, and should not be assumed necessarily to be false positives.
Like all estimates derived from sample, ours are subject to the uncertainty engendered by the sampling: that is, the sample error. We do not present measures of possible sample error within the tables. Instead, we reference the Census Bureau’s standard procedure for estimating error through generalized variance functions: http://www.census.gov/hhes/www/income/p60_231sa.pdf (see particularly, page 7). These functions give their users an idea about the level of error associated with each statistic but on a statistic-by-statistic basis may be substantially inaccurate.
We should also point out that the logistic regression techniques we used are in application as much an art as a science, and therefore it is likely that with additional effort or expertise that they can be improved upon. Still we think they are useful for identifying factors associated with reporting accuracy and for predicting enrollment status from survey results.
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VII. Appendices:
I. Description of Four Project Phases II. Key Decisions Leading to Phase II Research Design III. Files and Methods Used IV. Meta Data in Phase II V. Detailed Tables and Documentation
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APPENDIX I: Project Background
In 2004, Dr. Mike Davern from the State Health Access Data Assistance Center (SHADAC), University of Minnesota was funded by the Robert Wood Johnson Foundation to match enrollment data from seven states to the Current Population Survey (CPS) to study why the large discrepancy exists between CPS estimates and Medicaid enrollment counts. During the summer of 2004, Dr. Davern approached Census Bureau and Center for Medicare and Medicaid Services (CMS) officials about participating in the study. Realizing the amount of time that it would take to acquire the state data, Census officials offered the idea of conducting a national match first using a file they had already acquired: Medicaid Statistical Information System (MSIS) file. Census officials further suggested that a precursor to the national study could be a simple quality check on both the MSIS and the Medicare Enrollment Database (MEDB) files, which was in scope of current agreements and systems of records notices with CMS.
The Federal Health and Human Services Department (HHS) Office of the Assistance Secretary for Planning and Evaluation (ASPE) and SHADAC provided additional funding for the process. This money allowed for the national match and provided an opportunity to analyze the National Health Interview Survey (NHIS) and therefore bring its sponser, the National Center for Health Statistics (NCHS), into the study. Note that since NHIS asks a point-in-time question about Medicaid enrollment versus the CPS’s “Have you been on Medicaid anytime in the calendar year?,” the impact of timing (both for the reference period and its relationship to the moment of survey fielding) can be examined by comparison of results. Hence, the SNACC Team emerged, which is an acronym for the first initial of each of the participating agencies. After the first face-to-face meeting on the project, the SNACC team agreed to break the study into four distinct, but related, phases:
Phase І: Merging the National Level CMS Databases
In Phase I, we create a national database of health-insurance enrollment and evaluate the quality of the information it contains. We create the database by merging the CMS Medicaid Statistical Information System (MSIS) file with the CMS Medicare Database (MEDB) file (see Appendix III for an explanation of the research and supporting files). We evaluate the quality of the database by assessing our ability to accurately merge the input files and by comparing the characteristics of the individuals in the database to expectations based on Medicaid eligibility rules and characteristics of the U.S. population. (For more information, please see Phase I Research Results: Overview of Medicare and Medicaid Files, February 2007.)
Phase II: Matching the MSIS to the Current Population Survey (CPS)
In Phase II, we match data from MSIS and the Current Population Survey (CPS) according to a unique person-identifier (the Protected Identity Key or PIK, which replaces Social Security Number or SSN to protect reportee privacy). We supplement the matched records with information from the Medicaid Analytic eXtract (MAX), the Person Characteristic File (PCF), and the Master Address File Auxiliary Reference File (MAF-ARF) and examine why there are discrepancies between MSIS records of enrollment and CPS reports of Medicaid coverage (See hypotheses outlined below).
1
Phase III: Matching the State Frame and Person MSIS data to the CPS
In Phase III, we use data from the seven acquired state Medicaid file extracts, CPS, MAX, and the Census Bureau Master Address File (MAF) to enhance the comparison of MSIS enrollment data to CPS health insurance data developed in Phase II. The Census Bureau worked with CMS to negotiate the acquisition of the state Medicaid files that are intended to enhance the capability of finding matches with CPS person records because they include person names and addresses (in contrast with MSIS, which does not include these data elements). We analyze how better MSIS record person-identification and determination of out-of-CPS-frame status can impact Phase II results.
Phase IV: Matching the MSIS to the National Health Interview Survey (NHIS)
In Phase IV, we repeat the Phase II process, replacing the CPS data with NHIS data. In addition to providing explanations for discrepancies between the national NHIS and MSIS, comparisons to Phase II results will allow the examination of how survey design and implementation affect the quality of the resulting survey data and the estimates derived from them.
Hypotheses about the Discrepancy between Survey Estimates and Administrative Counts
In preparation for Phase II, III, and IV analyses, the team prepared a list of twelve hypotheses explaining the Medicaid enrollment count-survey estimate discrepancies and outlined some possible approaches to evaluating them:
1. Individuals enrolled in Medicaid who were residing in institutional group quarters were not designed to be included in the survey universe. However, they are included in the Medicaid administrative data. Unfortunately, it is not possible to identify all Medicaid enrollees living in group quarters by using the Medicaid administrative data so we cannot directly account for this universe difference. The best approach to evaluating this hypothesis would be to use MAX to identify persons who received Long Term Care (LTC) services (since they mostly receive such care in group facilities) and use the count as a measure of the magnitude of this factor.
2. Individuals enrolled in Medicaid who do not have a usual residence were not designed to be included in the survey universe. Unfortunately, it is not possible to determine the usualness of an enrollees residence from their Medicaid administrative data so we cannot directly account for this universe difference. However, these individuals often receive correspondence at local social services offices, soup kitchens or other places so one approach to evaluating this hypothesis would be to run a frequency distribution to determine if many unrelated individuals are attributed to specific addresses.
3. Some individuals are enrolled in Medicaid for a very short period of time (catastrophic health event and related costs made them eligible – or they were resident aliens) so
2
respondents may not consider this coverage. Unfortunately, there is some conceptual question whether these individuals should be considered as “covered” by health insurance. One approach to evaluating the role of this conceptual confusion in the discrepancy between reports and actual receipt of benefits would be to evaluate survey reports after classifying individuals by length of time enrolled.
4. Some groups of Medicaid enrollees have restrictions on the Medicaid benefits they receive regardless of length of enrollment (for example, some dual Medicaid and Medicare enrollees who do not receive the full scope of Medicaid benefits, non-citizens who receive only emergency services, etc.) so respondents for enrollees in these restricted groups may not consider this coverage. However, as in #3 above, there is a conceptual question whether these individuals should be considered as “covered” by health insurance. One approach to evaluating this hypothesis would be to examine reports after classifying enrollees by type of Medicaid benefit they receive.
5. Some Medicaid enrollees are in pre-paid plans (e.g. HMOs - Health Maintenance Organizations, PHPs - Prepaid Health Plans, etc.) so respondents reporting about such enrollees may incorrectly report no coverage because they do not realize that Medicaid is the health insurance that pays for the enrollee’s services. One approach would be to examine reports after classifying individuals by their type of Medicaid plan.
6. Medicaid is a state-based delivery system so enrollees may be counted more than once if they are enrolled in multiple states or multiple counties in the same state (e.g., because of moving during the year). There are also documented instances where states have changed identification numbers for selected individuals or all state enrollees. While these situations could cause double (or more) counting in administrative data systems, MAX processing attempts to minimize multiple counting within an individual state. However, because MAX and its source, MSIS, are organized into state-specific data sets, there are likely to be some enrollees and beneficiaries represented duplicatively across states. CMS began an examination of the extent of multiple counting across states in 2006 so one approach would be to evaluate what CMS results imply about the discrepancy between CPS estimates and Medicaid enrollment counts.
7. Some Medicaid enrollees did not receive Medicaid-provided medical services during the survey reference period so respondents reporting about such enrollees may incorrectly report no coverage because they may not realize or believe that the enrollee was nonetheless covered by Medicaid. One approach to evaluating this hypothesis would be to classify individuals by multiple categories (not eligible, eligible and not enrolled, enrolled and not receiving benefits, enrolled and receiving benefits). However, it is not possible to identify persons eligible and not enrolled in the Medicaid administrative data (because the system captures only those individuals who are actually enrolled) so under this approach it is necessary to use other sources (e.g. the Urban Institute Trim3 model) to estimate persons eligible and not enrolled. Also, the Census Bureau’s 2001 Supplementary Survey (SS01) can be used to provide evidence of those eligible and not enrolled. This is outside the scope of this research but could be addressed in subsequent studies.
3
8. Medicaid eligibility is not assigned to an entire household (it is case-based or individual-based) so Census Bureau survey households containing multiple families or non-family members are most at risk for incorrect proxy responses. Even when a family and household have a one-to-one correspondence, if the survey respondent is not the applicant for Medicaid, there may be errors. One approach to evaluating this hypothesis is to examine reports after classifying individuals by relationship types.
9. Some Medicaid enrollees have co-insurance or personal or family liability for some share of the cost of their health care so respondents reporting about them may incorrectly report no coverage because they did not realize or believe that the enrollee was nonetheless covered by Medicaid. One approach would be to review Medicaid data elements that identify individuals with a Medicare deductible and/or coinsurance and that identify individuals with other insurance (this is known in Medicaid as third-party liability).
10. Some respondents may not distinguish the difference between types of health insurance (because they never knew the difference or in the survey they fail to apply the cognitive effort needed to distinguish the difference) so they may, for example, mistake Medicare or stand-alone SCHIP for Medicaid and vice-versa. One approach to evaluating this hypothesis would be to check survey results after classifying enrollees by dual eligible status and stand-alone SCHIP enrollment status.
11. Respondents may systematically make recall errors reporting about individuals who did not receive medical services from Medicaid or were not enrolled in the month in which they were surveyed.1 One approach would be to check survey results after classifying enrollees by their Medicaid experience in the month of the survey.
Survey procedures may present biases for poorer populations, including the coverage of the survey frame (derived from the Master Address File or MAF) or non-response weighting. One approach to checking the MAF would be to match all Medicaid address records to the MAF to determine what proportion of Medicaid cases were out of the survey universe and study how those cases may differ from those that were correctly included in the survey estimate.
High-Level Research Requirements
• Identify the size of the discrepancy between MSIS enrollment counts and CPS enrollment estimates.
• Provide information and demographics (including family income as a percentage of the poverty threshold) on the false negatives (those who are enrolled in Medicaid but respond “no” on the CPS).
1 Kim Mah of The Bureau Of The Census has analyzed possible response biases in CPS between Medicaid enrollees and non-enrollees. This analysis shows that any such response bias is relatively small. She will present the results of this analysis at the 2007 Joint Statistical Meetings.
4
• Provide information and demographics (including family income as a percentage of the poverty threshold) on the unconfirmed persons reported enrolled (those who are reported enrolled in Medicaid on CPS but for whom confirmation by linkage to an MSIS record does not exist). Note, only some of these persons are false positives. Others may be unconfirmable due to incomplete linking data (that is PIK, replacing SSN) on MSIS.
• Provide information on factors that are contributing to both sources of mis-alignment. • Provide some measure of “time since covered” or “intensity of coverage.” • Provide information on what types of coverage false negatives are receiving, since they
are not reporting Medicaid coverage.
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Appendix II: Key Decisions about Phase II Analyses
The actual implementation of the decisions described here is detailed in Appendix V.
Restricted Benefits Flag (Monthly)
Decision: Consider an individual to be enrolled in Medicaid with Full Benefits if he/she is a code 1 (full benefits) or code 4 (pregnancy).
Rationale: On the MSIS, clients can be coded in 6 different ways. Code values 1=full benefits, 2=alien, 3=dual enrollee, 4=pregnancy, 5= other, and 6 = (family planning). Codes 2, 3, and 6 are clearly without "meaningful insurance coverage". Initially, although there may be some uncertainty as to exactly what coverage persons with code value = 4 (pregnancy) and 5 (other) may have received, the initial recommendation was to include them as persons without "meaningful insurance coverage". However, based on subsequent research conducted by ASPE officials, the team decided to include code 4 (pregnancy) as having full benefits. The table below illustrates the heavy usage of pregnancy services in New Jersey.
Appendix Table 1. Percentage of Enrollees Receiving A Service in New Jersey
Decision: Include persons in Medicaid-expansion SCHIP programs as Medicaid enrollees. Exclude persons who are in stand-alone SCHIP programs.
Rationale: Enrollment in SCHIP is identified monthly using this variable. A Medicaid-expansion SCHIP enrollee should also have Medicaid eligibility in the month. An enrollee in a non-Medicaid stand-alone SCHIP program should not have Medicaid eligibility in the month. Instructions to states about reporting of SCHIP in MSIS may create confusion. States are told to report all Medicaid-expansion SCHIP enrollees and their services through MSIS. States have the option to report non-Medicaid stand-alone enrollees in MSIS. Some do, some don't, and some report enrollment for some non-Medicaid stand-alone enrollees and not others. States are told not to report services for non-Medicaid stand-alone SCHIP enrollees in MSIS.
Eligibility
Decision: A person is considered eligible for Medicaid if he or she has been on Medicaid for at least one day.
Rationale: The CPS asks the respondent, “Have you received Medicaid in the last year?” There is no agreed upon length of time that a person must be on Medicaid in order to be considered “covered.” For that reason, we decided that one day of enrollment constitutes being eligible, which may result in high false negative rates as people on for only one day may not consider themselves as having had Medicaid. Some of this should surface when we look at days of eligibility and its relationship to a correct response.
Persons Enrolled in Medicaid Who Receive No Benefits
Decision: Use the MAX Person Summary File to classify enrolled individuals as receiving benefits (that is, medical services) or not receiving benefits.
Rationale: CMS experience with Medicaid enrollment has revealed that 15-20% of enrollees never use any services in a year. This is an average across Medicaid eligibility groups (e.g. adults, children, aged, disabled). We have not examined the question thoroughly for several years, but results were somewhat counterintuitive in that the highest percentage of non-users was medically needy children. The finding makes sense in the context of Medicaid enrollment being case-based. For example, a Section 1931 (AFDC rules) women with five dependent children may receive enrollment as a medically needy case. However, she may not take the children for well-child care. It is possible that the only child who receives care is the sick one that caused her to seek Medicaid eligibility. Survey respondents may not consider themselves to have health insurance (e.g. Medicaid coverage) if they were enrolled and but did not receive benefits.
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Basis of Eligibility - BOE (Monthly) and Maintenance Assistance Status - MAS (Monthly)
Decision: Use the MAS value = 1 (receiving cash or eligible to) in conjunction with BOE code values =1 (aged) or 2 (blind/disabled) to identify persons receiving SSI cash payments. The TANF flag=2 (individual received TANF benefits) will be used to identify persons receiving TANF benefits. (The 2000 MSIS that the Census Bureau received did not contain the TANF flag.)
Rationale: Individuals whose eligibility is based on receiving cash are more likely to know that they are on Medicaid and to respond correctly to the CPS. This can be tested with the variables on MAX in which BOE and MAS are combined into a single data element. Some states did not populate the field so we used whether the person’s record contained the 1931 indicator because the 1931 and TANF eligible roughly represent the same group.
Out of Scope Persons
Decision: Using MAX, move those MSIS persons who are either living in institutional Group Quarters (e.g., prisons, nursing homes) or who have no usual residence from the universe to be studied.
Rationale: Individuals enrolled in Medicaid that were residing in institutional group quarters are not included in the survey universe so are not matchable. Likewise, persons enrolled in Medicaid and have no usual residence are also not included in the survey universe so are not matchable. Hence, removing these two subpopulations is important to aligning the MSIS and CPS universes to ensure meaningful comparisons and inferences. However, because our address data are not complete, we will revisit this issue in Phase III when we have state MSIS data that includes complete addresses.
Persons Enrolled in Medicaid in More than One State
Decision: Persons with duplicate records in MSIS are only counted once at the national level. In state-level tallies, these persons are counted once, under State is Unknown.
Rationale: Un-duplicating MSIS records and removing duplicates is important to aligning the MSIS and CPS universes to ensure meaningful comparisons and inferences.
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APPENDIX III: Description of Files and Methods in Phase II
Research Files
Medicaid Statistical Information System (MSIS)
The Medicaid Statistical Information System (MSIS) is the basic source of state-submitted eligibility and claims data on the Medicaid population, their characteristics, utilization, and payments. Beginning with Fiscal Year 1999, the Balanced Budget Act (BBA) of 1997 requires states to submit all their eligibility and claims data to CMS on a quarterly basis through the MSIS.
Medicaid Analytic eXtract File (MAX)
The MAX – formerly known as State Medicaid Research Files (SMRFs) – are a set of person-level data files on Medicaid eligibility, service utilization, and payments. The MAX data are extracted from the MSIS. The MAX development process combines MSIS initial claims, interim claims, voids, and adjustments for a given service into this final action event. Unlike fiscal-based MSIS quarterly files, MAX is an annual calendar year file.
Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC)
The CPS ASEC is an annual survey of approximately 78,0002 households nationwide. The ASEC, formerly known as the March Supplement to the Current Population Survey is a basic source for health insurance coverage data. The population represented is the civilian non-institutional population living in the United States. Most of the data from the CPS ASEC were collected in March (with some data collected in February and April).
In September 2000, the CPS began an expansion of its sample to accommodate increased funding provided by the State Children's Health Insurance Program (SCHIP). Although focused primarily on the ASEC sample, the SCHIP funding provided for an approximately 20 percent increase in the basic CPS sample. This expansion, which occurred in 31 small states and the District of Columbia, was completed in November 2000. Over the next several months, both the BLS and the Census Bureau monitored the impact of this expansion on the CPS labor force estimates, and the BLS decided to begin using the expanded sample in its official CPS estimates in July 2001. Since the focus of this expansion was on estimates of children's health insurance coverage, the CPS ASEC sample was also increased by bringing back three rotation groups of households from the summer of the previous year also asking the ASEC in the rotation groups in February and in April that are not part of the ASEC sample for the month of March. Interviewing in these rotation groups is limited to all minority households and White households with children under 18.
2 This number includes about 18,000 vacant housing units and nonresponding households.
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Support Files
Person Characteristics File
The Person Characteristics File (PCF) is a Census Bureau file that holds basic person-level descriptive data for all persons who have a Social Security Number (SSN). For each represented person, PCF holds summarized Social Security Administration (SSA) Numident data, consisting of a single record. In addition, the PCF holds a modeled race, ethnicity and gender for these same persons as well as Census 2000 reported race and ethnicity when available.
Master Address File Auxiliary Reference File
The Master Address File Auxiliary Reference File (MAF-ARF) is an annually-compiled Census Bureau file with only two fields: Master Address File Identifier (MAFID) and Protected Identification Key (PIK). The MAFID is the identity key for a Census Bureau’s Master Address File (MAF) record and each represents a specific address. The PIK is a unique person-identifying code that replaces the Social Security Number to protect represented-persons’ privacy. Each MAF-ARF records reflects that the person represented by the PIK is shown in the Census Administrative records collection associated (through residence or some other means) to the address represented by the MAFID.
Research Methods
Person Identification Validation System
The Person-Identification or ID Validation System (PVS) provides a fully automated production capability at the Census Bureau for Social Security Number (SSN) verification, search, and assignment. Once an SSN is either verified or searched for and assigned, the record is considered validated. The Administrative Records staff manages the PVS. The PVS enables SSN verification, search, and assignment for regularly repeating demographic surveys such as the CPS and SIPP, as well as for other demographic or administrative files. The PVS also expands data linkage capabilities for merging survey and administrative data sets.
The PVS uses probabilistic matching to verify SSNs contained within an incoming file against those contained within the Census Numident. The processing consists of a verification phase followed by a two-step search phase. For the verification phase, SSNs are matched using several types of demographic data, including names, dates of birth and gender. Specific weights are set to define acceptable matches. Any records not verified through this phase – or without an incoming SSN – are sent forward to the search phase of the system. (Note: In conformance with Census Bureau privacy policy, the PVS does not process any record for which the respondent has refused to provide an SSN. Also, due to technical constraints, the PVS does not process records where the first name and surname are missing.)
The search phase of the PVS, also based on probabilistic matching, comprises a geokey (address-based) search, followed by a name search. The geokey search consists of logically grouping or "blocking" the data using the geokey, and then progressively relaxing the geographic criteria
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while undertaking five passes through a matching routine to achieve agreement on demographic data as cited for the verification phase. Unmatched records remaining after the geokey search fall to the name search, where they undergo a similar demographic matching process but without the use of the geokey.
The final output file of the PVS (created after completion of the verification and the search phases) contains: all records with verified or searched and assigned SSNs; all records where the SSN could not be verified or searched and assigned or where multiple and, therefore, inconclusive SSNs were found; and, all original records withheld from the PVS process due to refusals or wholly blank names. A record is considered validated when it successfully completes either the verification or the search and assign phase. Only validated records can be used in record linkage.
Adjusting the weights in the CPS to account for people missing SSN
Many sampled persons in the CPS are missing SSN because the respondent refused to provide it, or we were unable to identify it using the Person-ID Validation System. For this reason, we adjust the weights of persons for whom we have the SSN to account for those missing it, and remove the missings from the data file. The re-weighted data represent the whole survey frame.
The procedure is similar to the non-response weighting adjustment the Census Bureau and other survey researchers use. Appendix III Table 2 illustrates a non-response weighting adjustment by age and sex in a hypothetical survey of 1,000,000 persons (with known age and sex characteristics) and a sampling rate of 1 in 1,000. The number of sampled persons by age and sex is in Column 2. In the CPS, the population controls are by age, race, and sex for each state. Column 3 contains the number of sampled persons in each group responding to the survey. Response varies by group. For example, young males have an especially low response rate, as listed in Column 4.
The base weight of each sampled person, 1,000, is the inverse of the sampling rate. The procedure adjusts the base weight in Column 5 by the inverse of each group’s response rate (Column 6) to produce the new weight in Column 7. Essentially, respondents with certain characteristics cover those with the same characteristics who didn’t respond.
Note that multiplying the base weight of each group times the number of sampled persons and summing the products gives the number of people in the population, 1,000,000. Performing the same calculation with the new weight and the number of responses produces the same number, 1,000,000.
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Appendix Table 2. Example of a Non-response Weighting Adjustment
1 2 3 4 5 6 7
Age/Sex Sampled Response Rate Adjustment Group Persons Responses (Percent) Base Weight Factor New Weight
Note: Groups are Young, Middle, Old; Male, Female. Sampling rate is 1 in 1,000 of 1,000,000-person population.
We use a similar procedure to adjust the weights of people in the CPS. Here, we are adjusting for missing SSN instead of missing response. For the CPS weighting adjustment, we calculate an adjustment factor in the same manner as the above example, by groups based on the variables most important to the research at hand, namely, age, relative poverty, health insurance status, and whether health insurance status was imputed.
Age A 0-5 B 6-17 C 18-64 D 65 and up
Relative Poverty A 0% to 99% B 100% to 199% C 200% and up
Health Insurance Status 1 Medicaid 2 Other public only 3 Private only or other public/private 4 [not used] 5 Uninsured
Imputation of Health Insurance Status I Imputed N Nonimputed
Note that in the above example, knowing the population’s age and sex characteristics allows us to calculate adjustment factors for groups. In the CPS, we create groups based on persons’ characteristics known because the Census Bureau collected (or imputed) the information in the survey.
Some of the groups created by crossing all of these variables were very small. We therefore collapsed them into other cells in order to bring the count (in each cell after the collapsing procedure) to at least 50. Specifically, in all age/poverty groups with imputed health insurance
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status, we combined Other public only with Medicaid. For the Uninsured, 65 and up group, we combined the poverty categories, and we combined the imputation categories.
After calculating the adjustment factors for the groups, we apply the appropriate factor to each sampled person’s CPS weight, which the Census Bureau has already calculated for each person based on many characteristics. The adjustment factors, each the inverse of the SSN existence rate in the group, are in Appendix Table 3
Health of Health number of persons with Age Relative Insurance Insurance Cell persons SSN Percent with Adjustment
Group Poverty Status Status Count (thousands) (thousands) SSN Factor A A 1 N 1,900 2,331 1,984 85.1 1.17 A A 2 N 150 191 156 81.4 1.23 A A 3 I 100 136 101 74.7 1.34 A A 3 N 500 584 486 83.3 1.20 A A 5 I 150 197 125 63.3 1.58 A A 5 N 550 710 520 73.2 1.37 A A 6 I 200 247 181 73.4 1.36 A B 1 N 1,300 1,428 1,266 88.7 1.13 A B 2 N 250 289 255 88.1 1.13 A B 3 I 250 274 228 83.2 1.20 A B 3 N 2,050 2,223 2,022 91.0 1.10 A B 5 I 100 158 116 73.3 1.36 A B 5 N 550 656 515 78.6 1.27 A B 6 I 150 211 163 77.3 1.29 A C 1 N 600 671 592 88.2 1.13 A C 2 N 150 176 162 92.0 1.09 A C 3 I 900 1,034 823 79.6 1.26 A C 3 N 9,900 10,521 9,890 94.0 1.06 A C 5 I 200 264 204 77.0 1.30 A C 5 N 600 677 561 82.8 1.21 A C 6 I 200 252 187 74.1 1.35 B A 1 N 3,100 3,465 2,887 83.3 1.20 B A 2 N 400 396 336 84.9 1.18 B A 3 I 250 238 177 74.2 1.35 B A 3 N 1,250 1,362 1,111 81.6 1.23 B A 5 I 300 381 224 58.9 1.70 B A 5 N 1,300 1,509 1,049 69.5 1.44 B A 6 I 350 412 289 70.2 1.42 B B 1 N 1,900 2,007 1,729 86.2 1.16 B B 2 N 500 542 484 89.2 1.12 B B 3 I 650 669 513 76.7 1.30 B B 3 N 4,350 4,581 4,058 88.6 1.13 B B 5 I 300 378 269 71.2 1.40 B B 5 N 1,400 1,535 1,174 76.5 1.31 B B 6 I 350 393 284 72.3 1.38 B C 1 N 900 869 761 87.6 1.14
Health of Health number of persons with Age Relative Insurance Insurance Cell persons SSN Percent with Adjustment
Group Poverty Status Status Count (thousands) (thousands) SSN Factor B C 2 N 300 300 266 88.7 1.13 B C 3 I 2,750 3,133 2,429 77.5 1.29 B C 3 N 24,300 24,176 22,085 91.4 1.09 B C 5 I 550 670 497 74.1 1.35 B C 5 N 1,400 1,482 1,198 80.8 1.24 B C 6 I 500 586 447 76.2 1.31 C A 1 N 3,050 3,976 3,135 78.9 1.27 C A 2 N 400 586 439 74.9 1.33 C A 3 I 600 869 434 49.9 2.00 C A 3 N 2,750 3,678 2,666 72.5 1.38 C A 5 I 750 1,073 517 48.2 2.07 C A 5 N 4,250 5,784 3,753 64.9 1.54 C A 6 I 500 706 389 55.1 1.82 C B 1 N 2,000 2,565 2,026 79.0 1.27 C B 2 N 500 707 525 74.2 1.35 C B 3 I 1,400 1,907 1,117 58.6 1.71 C B 3 N 9,100 11,394 8,918 78.3 1.28 C B 5 I 1,000 1,420 717 50.5 1.98 C B 5 N 5,450 7,118 4,765 66.9 1.49 C B 6 I 400 546 282 51.7 1.94 C C 1 N 1,250 1,676 1,270 75.8 1.32 C C 2 N 500 705 505 71.5 1.40 C C 3 I 9,450 13,558 7,478 55.2 1.81 C C 3 N 74,700 98,807 78,266 79.2 1.26 C C 5 I 2,700 3,999 2,056 51.4 1.94 C C 5 N 8,150 11,541 7,710 66.8 1.50 C C 6 I 650 1,023 548 53.5 1.87 D A 1 N 600 788 570 72.3 1.38 D A 2 N 750 1,109 717 64.6 1.55 D A 3 I 200 276 120 43.4 2.31 D A 3 N 500 740 521 70.4 1.42 D A 6 I 200 321 131 40.8 2.45 D B 1 N 650 963 680 70.6 1.42 D B 2 N 1,800 2,907 1,965 67.6 1.48 D B 3 I 400 648 326 50.3 1.99 D B 3 N 2,400 4,075 3,001 73.6 1.36 D B 6 I 350 601 278 46.3 2.16 D C 1 N 550 805 565 70.2 1.42 D C 2 N 2,400 3,949 2,837 71.8 1.39 D C 3 I 1,000 1,635 827 50.6 1.98 D C 3 N 7,900 13,258 10,173 76.7 1.30 D C 6 I 750 1,239 646 52.1 1.92 D D 5 Z 200 251 133 52.9 1.89
Total 218,000 279,517 213,808 76.5 Note: Health Insurance Status value 6 includes values 1 and 2. Imputation Status value Z includes values I and N.
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Regression Analysis Variable Specification
Response Variables:
Full Benefits (in Models 3a and 3b) A dichotomous dependent variable from MSIS indicating that the CPS person is in the MSIS database as having received full Medicaid benefits during the reference period.
Reported Enrolled (in Models 1a and 1b) A dependent dichotomous variable from CPS indicating that the respondent explicitly reported Medicaid coverage (Augmented-CAID set) for the survey person.
Uninsured (in Model 2) A dichotomous dependent variable from CPS indicating that the CPS person was explicitly reported as having no health insurance.
Covariates:
Age (in Models 1a, 1b, 2, 3a, and 3b) An independent ordinal variable recoded into six categories from the CPS age variable. The odds ratio is the effect of being in a given category relative to average.
Enrolled in Survey Month (in Models 1a and 2) An independent dummy variable from MSIS indicating that the person received Medicaid with full benefits (excluding SCHIP coverage) in the month they were surveyed. The reference category is persons who had Medicaid during the reference period but not in the month of the survey.
Health Insurance Category Designated in CPS (in Model 3a) An independent nominal variable from CPS representing the category of health insurance designated for the person. Since the universe in model 3a is only persons CPS designated as not having Medicaid, in 3a this variable distinguishes between the following categories (odds ratios are relative to average): 1. Only Another Public Insurance Program 2. Only Private Insurance 3. Other Public and Private Insurance 4. Uninsured
Health Insurance Category Designated in CPS (in Model 3b) An independent dummy variable from CPS representing the category of health insurance designated for the person. Since the universe in model 3b is only persons CPS designated as having Medicaid (with or without some other coverage), in 3b this variable distinguishes those designated as having “Only Medicaid” from those designated as having “Medicaid and Some Other Coverage,” which is here made to be the reference category
Intensity of Coverage (in Models 1a and 2)
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An independent continuous variable from MSIS representing the number of days covered with full benefits (excluding SCHIP coverage) as a percentage of the number of days from January 1 to the last day of the last month of coverage with full benefits (excluding SCHIP coverage) in the reference period. For example if a person had coverage for 100 days and their last month of coverage in CY 2000 was June, then their intensity of coverage for the CY 2000 reference period is 100 / 181 = 0.552. The odds ratio is the effect of having continuous coverage from January 1st to the last day of their last month of coverage compared to having no coverage (which is only possible as a theoretical construct – because in this case, having no days of coverage, they would not have been a Medicaid enrollee) during this period.
Last Month of Coverage (in Models 1a and 2) An independent ordinal variable from MSIS corresponding to the number of the last month in which the person had Medicaid coverage for full benefits (excluding SCHIP coverage) during the reference period. For example, if a person’s last month of coverage during the reference period was June, this variable will have the value 6. The odds ratio is the effect of having coverage one month more recently.
Male (in Models 1a, 1b, 2, 3a, and 3b) An independent dummy variable indicating that the CPS person is male. Females are the reference category.
Medicare Crossover (in Models 1a and 2) An independent dummy variable from MAX indicating that the person had both Medicare and full Medicaid coverage during at least one month of the reference period. In Models 1a and 2, people with full Medicaid coverage but no Medicare during the reference period are the reference category.
Private Insurance (in Models 1a and 2) An independent dummy variable from MAX indicating that the person had private insurance at the same time the person had Medicaid in at least one month during the reference period. Enrollees with no indication of private insurance are the reference category.
Race/Hispanicity (in Models 1a, 1b, 2, 3a, and 3b) An independent nominal variable constructed from the CPS items for race and ethnic origin. Categories include: Hispanic of any race, non-Hispanic black, non-Hispanic American Indian/Aleut Eskimo, non-Hispanic Asian or Pacific Islander and non-Hispanic white. Odds ratios are the effect of being in a given category relative to the average.
Ratio to Poverty Level (in Models 1a, 1b, 2, 3a, and 3b) An ordinal independent variable representing the ratio of the CPS person’s family income to the federal poverty level. There are eight categories ranging from 0-49 percent of the poverty level (for the person’s family size) to greater than 200 percent of the level. Odds ratios are the effect of being in a given category relative to average.
Relationship to Survey Reference Person (in Models 1a, 1b, 2, 3a, and 3b)
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An ordinal independent variable from CPS indicating the person’s relationship to the survey reference person (usually the respondent). Categories include: Child, Self, Parent, Spouse, and Other. Odds ratios are the effect for the given category relative to average.
Service (in Models 1a and 2) An independent nominal variable from MAX representing enrollee experience receiving Medicaid services. The five categories indicate both whether the Medicaid enrollee had any coverage through a managed care program and whether there is a record of the person receiving a medical service. Note that states do not have to collect or send CMS information about services provided to enrollees in pre-paid plans so having no record for a person in managed care is not necessarily an indication that the person did not receive medical service. Categories include the following:
1. Not on managed care and no medical services received 2. Not on managed care and medical services received 3. In managed care and medical services noted 4. In managed care and medical services not noted 5. Unknown (MAX record not available for this person)
Source of CPS Insurance Data (in Models 3a and 3b) An independent nominal variable from CPS indicating how the person’s Medicaid status was reported. Categories include edited, imputed, and explicitly reported. Note that there can be no edited category in Model 3a because it models the event that persons with no CPS indication of Medicaid coverage are found in MSIS but CPS edits only change responses to coverage indicated.
SSI Recipient (in Models 1a and 2) An independent dummy variable from MSIS indicating that the person received Supplementary Security Income (SSI) in at least one month during the reference period. Enrollees who are not SSI recipients are the reference category.
State (in Models 1a, 1b, 2, 3a, and 3b) A nominal independent variable from CPS or MSIS for state of residence. For each CPS person, if a matching record is found for him or her in MSIS, this variable comes from MSIS, otherwise it comes from CPS. Note if MSIS shows more than one state of residence for a person, that person is assigned a value Unknown for this variable. Odds ratios are the effect of being in a given state relative to average.
TANF (in Models 1a and 2) An independent dummy variable from MAX indicating that the person’s eligibility for Medicaid is based on qualification under Section 1931 (which were the rules for eligibility under AFDC when AFDC was still operative). Note that a person may be in TANF but eligible for Medicaid for some other reason. We use this item instead of the MAX item indicating that person is in TANF because some states do not provide this information but all states provide information on the basis of eligibility. Persons who are eligible for reasons other than under Section 1931 are the reference category.
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Zero Family Income Reported (in Models 1a, 1b, 2, 3a, and 3b) An independent dummy variable indicating that the CPS shows the person’s family with zero income. CPS persons with positive family income are the reference category.
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APPENDIX IV: Meta Data in Phase II
In this section names of variables on input files are shown in this FONT, names of T derived variables are shown in this FONT, and constants are shown in this font.
SSN Validation:
We validate MSIS SSNs against the Census Numident to minimize the chance that linked MSIS-CPS records do not represent the same person. The validation procedure compares date-of-birth and sex on the MSIS record to those values on the Numident record indexed by the same SSN. The MSIS SSN is considered valid if any of the following occurs:
� The date of birth on both is the same. � The difference in year-of-birth is one year or less, month-of-birth is the same, day-of-
birth is the same, and sex is the same. � Year-of-birth is the same, sex is the same, and month-of-birth and day-of-birth are the
same after transposition (example: MSIS DOB: 08/10/1961, August 10, 1961, is validated by Numident DOB: 10/08/1961, October 8, 1961, as long as sex is the same).
SSN Rationalization:
We performed a rationalization procedure because in some cases, MSIS records sharing the same MSIS-Identification-Number have different personal identity data: SSN, DATE-OF-BIRTH, and SEX. The rationalization procedure insures that the data on each record having the same MSIS-IDENTIFICATION-NUMBER are set to the probable correct values. The probable correct values are determined as the values on the record having best validation result (that is, validated SSN records come before non-validated SSN records) and secondly the earliest calendar month. Rationalization was performed separately for each year’s set of MSIS data.
MSIS Summarization:
We summarized MSIS records (after validation and rationalization processing) so that we would have only one record for each person and variables in a form appropriate for our analyses. For records with validated SSNs, all records (applicable to a given calendar year) with the same SSN value are summarized to produce a single record. For records without a validated SSN, all records (applicable to a given calendar year) with the same combination of State and MSIS-IDENTIFICATION-NUMBER are summarized to produce a single record. The summarization developed the following variables describing the represented person and their Medicaid enrollment status:
� Valid SSN Status (VALID_SSN_STATUS) From modified Census PVS validation
1 – Yes 2 – No
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� Enrolled in Medicaid with Full Benefits (FULL_BEN) For at least one month of reference year, RESTRICTED-BENEFITS-FLAG in (1, 4) and DAYS-OF-ELIGIBILITY > 0 and SCHIP-CODE = 1)
1 – Yes 2 – No
� Enrolled in Medicaid with Any Benefits (ANY_BEN) For at least one month, DAYS-OF-ELIGIBILITY > 0 and SCHIP-CODE = 1 or 2
1 – Yes 2 – No
� Days Enrolled with Full Benefits by month and entire reference year January Æ ELIG_DAYS_FULL_1
February Æ ELIG_DAYS_FULL_2 … …
December Æ ELIG_DAYS_FULL_12 January (of subsequent year) Æ FBDE13 February (of subsequent year) Æ FBDE14 March (of subsequent year) Æ FBDE15 April (of subsequent year) Æ FBDE16 Entire reference year Æ TOT_DAYS_ANY
For each month if RESTRICTED-BENEFITS-FLAG = 1 or 4 and SCHIP-CODE = 1 minimum of DAYS-OF-ELIGIBILITY and days-in-calendar-month; otherwise 0. For reference year, sum of values for combining months.
� Days Enrolled with Any Benefits by month and entire reference year January Æ ELIG_DAYS_ANY_1
February Æ ELIG_DAYS_ANY_2 … …
December Æ ELIG_DAYS_ANY_12 January (of subsequent year) Æ ABDE13 February (of subsequent year) Æ ABDE14 March (of subsequent year) Æ ABDE15 April (of subsequent year) Æ ABDE16 Entire reference year Æ TOT_DAYS_ANY
For each month (and corresponding variable), if RESTRICTED-BENEFITS-FLAG = 1 or 4 and SCHIP-CODE = 1, minimum of DAYS-OF-ELIGIBILITY and days-in-calendar-month; otherwise 0.
� Benefit Type (BEN_TYPE) Hierarchy (Use the highest, that is nearest to 1, code ever seen for that MSIS-IDENTIFICATION-NUMBER during CY 2000):
1 – Full Benefits (DAYS-OF-ELIGIBILITY > 0 and RESTRICTED-BENEFITS FLAG = 1 or 4 and SCHIP-CODE = 1)
2 – Partial Benefits (DAYS-OF-ELIGIBILITY > 0 and SCHIP-CODE = 1) 3 – SCHIP (Medicaid-expansion) (Days-of-Eligibility > 0 and
� SSI-Cash (SSI_CASH) For any month, MAINTENANCE-ASSISTANCE-STATUS = 1 and BASIS-OF-ELIGIBILITY = 1 or 2
1 – Yes 2 – No
� Race (M_RACE) From RACE-ETHNICITY-CODE
1 Æ -W- White 2 Æ -B- Black 3 Æ -I- American Indian or Alaskan Native 4 Æ -A- Asian or Pacific Islander 6 Æ -A- Asian or Pacific Islander - Æ -*- More than one code for SSN: characterized as “Race Unknown”
� Ethnicity (M_HISP) From RACE-ETHNICITY-CODE is ever 5 or 7 then M_HISP Æ -Y- (Yes, Hispanic). Otherwise, M_HISP Æ space-filled: in this case, person is characterized as “Ethnicity Unknown”.
CPS Coding:
We coded the following CPS variables so we would have CPS information in a form appropriate for our analyses:
� CPS Health Insurance Category (CPS_HI) Hierarchy:
If CAID = 1 or OTHSTYP1 = 02 or OTHSTYP2 = 02 or OTHSTYP3 = 02 or OTHSTYP4 = 02 or OTHSTYP5 = 02 or OTHSTYP6 = 02 or AHITYP1 = 02 or AHITYP2 = 02 or AHITYP3 = 02 or AHITYP4 = 02 or AHITYP5 = 02 or AHITYP6 = 02 then
If MCARE = 1 or CHAMP = 1 or COV_HI = 1 or OTYP_{1 - 6} or ATYP_{1 - 6} = 1 or 3 - 15 CPS_HI Å 1 (Medicaid Only)
Otherwise CPS_HI Å 2 (Medicaid with Other Insurance)
Otherwise if (MCAID = 1 or MCARE = 1) and CHAMP = 2 and COV_HI = 2 CPS_HI Å 3 (Other Public Only)
Otherwise if (COV_HI = 1 or CHAMP = 1) and MCAID = 2 and MCARE = 2 CPS_HI Å 4 (Other Private Only)
Otherwise if (MCAID = 1 or MCARE = 1) and (COV_HI = 1 or CHAMP = 1) CPS_HI Å 5 (Other Public and Private)
Otherwise if CHAMP = 2 and MCAID = 2 and MCARE = 2 and COV_HI = 2 CPS_HI Å 6 (Uninsured)
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� CPS (Health Insurance) Data Source (CPS_DS) Hierarchy: If FL_665 = 2 or 3 or I_CAID = 1 or I_OTH = 1 or IAHITYP = 1 CPS_DS Å I (Imputed)
Otherwise if I_CAID = 2 CPS_DS Å E (Edited)
Otherwise CPS_DS Å R (Reported)
� CPS TANF Enrollment Status (CPS_TANF) If FINC_PAW = 1 CPS_TANF Å Y
Otherwise CPS_TANF Å N
� CPS SSI Enrollment Status (CPS_SSI)
If SSI_YN = 1 then CPS_SSI = Y CPS_SSI Å Y
Otherwise CPS_SSI Å N
Determining Out-of-Scope Persons:
CPS considers persons living in institutional group quarters (those group quarters that are formally authorized to provide supervised care or custody to residents, such as correctional institutions, nursing homes and juvenile institutions, etc. out-of scope. To make MSIS record counts in Table 2 more comparable to CPS estimates, a decision was made that certain MSIS represented persons were likely to have been residents of institutional group quarters during the reference year. This determination was made by reference to that year’s version of the Census Master Address File-Auxiliary Reference File (MAF-ARF). MAF-ARF shows, by person, all MAF-identified addresses within the Census collection of administrative records. The MAF-ARF is indexed by PIK (which is an identity-protected re-coding of SSN). For each identified MSIS person (those with a validated SSN), all MAF-ARF records indexed by that PIK were reviewed to see which are institutional group quarters. MAF records with MAF variable GQTYPE
in these ranges were noted as institutional group quarters:
Based on this review, for each person in MAF-ARF (represented by a unique PIK) an institutional group quarters flag (IGQ_FLAG) was set as follows:
� Some MAF-ARF addresses for this PIK are institutional group quarters: IGQ_FLAG Å B
� All MAF-ARF addresses for this PIK are institutional group quarters: IGQ_FLAG Å Y � No MAF-ARF addresses for this PIK are institutional group quarters or no MAF-ARF
addresses were found for this person: IGQ_FLAG Å blank. The value of the IGQ_FLAG is used in Table 2 to subset (for Columns 4, 5, and 6) MSIS records to be counted (see Table 2 discussions, below). Other than its use here in Table 2, IGQ_FLAG is not referenced in the production of Phase II tables.
1. If the person is on CPS (whether or not they are seen on MSIS), characteristics come from CPS: PUBIRTHY, A_RACE, A_SEX, A_ORIGIN.
2. Otherwise if we determined the person’s identity (that is, the SSN has been validated), characteristics come from Person Characteristic File (PCF)
3. Otherwise (for MSIS records without a validated SSN), characteristics come from MSIS.
Age is determined as {Reference Year} – {Year- of-Birth}, which is the age as of December 31 of the reference year. Age categorization directly follows, with these exceptions:
• If age comes from CPS and PUBIRTHY is not between 1880 and {Reference Year}, inclusively, then age category is set to Unknown.
• Otherwise if age is computed to be less than 0 then age category is set to Unknown.
If Race and Ethnicity come from PCF, then these values come either directly from Census 2000, Hundred Percent Detail File, IMPUTED-RACE and HISPANIC-ORIGIN-CODE – if the Census 2000 record for this person can be found; otherwise it comes from a race and ethnicity model that is used to impute these values.
Generating Tables for the Phase II Report:
Note that for each table included in the Phase II report there are two presentations: � Using original CPS weights. � Using adjusted weights coming from a re-weighting process. Weight on un-identifiable
CPS records (that is, records for which the SSN is unknown or un-validated) is shifted on to identifiable CPS records in a way that attempts to preserve the percentage of distributions of the various characteristics (particularly CPS_HI).
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Table 1:
Basis of Counting:
� MSIS: Unduplicated (by MSIS ID) MSIS file: All records. � CPS: 2001 (linked to MSIS for calendar year 2000) uses expanded sample, 2002 (linked
to MSIS for calendar year 2001) uses full sample: - For original weight presentation, weighting is by MARSUPWT. - For re-weighted presentation, weighting is by ADJWGT (developed in the re-
weighting process).
Columns:
Column 1 (CPS Not Valid SSN), Column 2 (CPS Valid SSN Not Matched), Column 3 (CPS Refused to Provide SSN) and Column 6 (Valid SSN and Matched) together include all CPS records being used for linkage. Each CPS record is tallied under one and only one column. If a CPS record has a validated SSN value, and that value also occurs (and is validated) in the MSIS file, that record is tallied under column 6. Otherwise, if PUSSN_FLG = R (indicating refusal to provide SSN) then a record is tallied under column 3. Otherwise if the SSN value has been validated, the record is tallied under column 2 and if not under column 1. For each of these columns (1, 2, 3, 6), when a weighted presentation is being made, it is the weights themselves that are being tallied: either MARSUPWT or ADJWGT.
Column 4 (MSIS Not Valid SSN), Column 5 (MSIS Valid SSN) together with Column 6 (Valid SSN and Matched) together tabulate all MSIS records, with each MSIS record falling under one and only one column. This is a count of MSIS records (for the reference calendar year, only) after person un-duplication. For this reason, persons (that we know are) represented as more than one client are counted only once, not once for each client account. Since MSIS records are self-representing, each can be considered to have a weight of (1); however, for weighted presentations, each record counted under Column 6 are weighted by the appropriate (original or adjusted) CPS weight of the matching CPS record.
Column 7 (%CPS Persons Matched) is Column 6 / (Column 2 + Column 6), and Column 8 (%MSIS Persons Matched) is Column 6 / (Column 5 + Column 6).
Rows:
� Age is determined as described above (in the Characterizing Joint Demographics section); age range follows directly.
� Race is determined as described above. Because “Unknown Race” occurs only in MSIS, only MSIS records with SSN value unverified can have this code.
� Sex is determined as described above. � Poverty Level is determined directly from CPS variable POVLL. For this reason, it is only
available for records that have CPS as a source.
24
� CPS Insurance Type is determined directly from CPS_HI (see description of the generation of this variable in MSIS summarization discussion above). For this reason, it is only available for records that have CPS as a source.
� MSIS Insurance Type is determined directly from BEN_TYPE (see description of the generation of this variable in MSIS summarization discussion above).
Table 2:
Table 2 represents a set of counts from MSIS and a set of counts from CPS presented side-by-side. For MSIS counts, persons with a date-of-death on the Person Characteristics File (PCF) prior to March of corresponding survey year are excluded from tabulation. The joint occurrence of records from both files representing the same persons is not relevant to the production of this table. Columns 1 to 6 (MSIS Total A – MSIS Total F) are counts directly from the summarized (person-unduplicated) MSIS. Columns 7 to 9 (CPS Total A – CPS Total C) are (weighted) counts directly from CPS. Note that since CPS asks respondents about health insurance status for the year previous (termed the reference year), the CPS survey year version is one year ahead of the MSIS summarized data shown on the same page.
Columns:
Column 1 (MSIS Total A) counts MSIS client accounts persons known to be deceased prior to March of the corresponding survey year. Moving to the right, each subsequent column counts a subset of the client accounts counted in the column immediately to the left. The exclusions are made as follows:
� Column 1 (MSIS Total A): Excludes only persons with a date-of-death on PCF prior to March of survey year; represents a count of unique client account (which is the same as unique State/MSIS-Identification-Number).
� Column 2 (MSIS Total B): Excludes clients where BEN_TYPE ≠ 1 or 2. � Column 3 (MSIS Total C): Excludes clients where BEN_TYPE ≠ 1. � Column 4 (MSIS Total D): Excludes clients where BEN_TYPE ≠ 1 or IGQ_FLAG ≠ ‘ ’. � Column 5 (MSIS Total E): Excludes clients where BEN_TYPE ≠ 1 or IGQ_FLAG ≠ ‘ ’
and duplicate clients (sharing the same SSN as other clients). So it is a count of unique persons (excepting unidentifiable duplicate client accounts, because they do not share the same verified SSN value, for the same person) with BEN_TYPE ≠ 1 or IGQ_FLAG ≠ ‘ ’.
� Column 6 (MSIS Total F): Excludes clients where BEN_TYPE ≠ 1 or IGQ_FLAG ≠ ‘ ’ and duplicative clients (sharing the same SSN with other clients) and clients with non-verified SSNs. So it is a count of unique identified persons (that is persons for whom we have a record with verified SSN value) with BEN_TYPE = 1.
25
Columns 7 – 9 (CPS Total A – CPS Total C) are weighted counts of CPS person records. The weight used for the original weight presentations is MARSUPWT. For re-weighted presentations, the weight is ADJWGT, a weight created in the re-weighting process.
� Column 7 (CPS Total A): This is the weighted sum of MCAID, which should closely match (re-weighting may cause a slight discrepancy) the CPS estimate of Medicaid enrollment.
� Column 8 (CPS Total B): This is the weighted sum of AUGMENTED-CAID. AUGMENTED-CAID is set (equal to 1 – showing Medicaid enrollment in previous calendar year) whenever CAID is set (to show Medicaid enrollment). In addition it is set if the reportee is described explicitly as a Medicaid enrollee in response to a question about other types of health insurance or in response to a verification question asked about reportees who were not shown having any insurance earlier in the question sequence about their health coverage. In terms of coding from CPS variables:
AUGMENTED-CAIDÅ 1 if CAID = 1 or OTHSTYP1 = 02 or OTHSTYP2 = 02 or OTHSTYP3 = 02 or OTHSTYP4 = 02 or OTHSTYP5 = 02 or OTHSTYP6 = 02 or AHITYP1 = 02 or AHITYP2 = 02 or AHITYP3 = 02 or AHITYP4 = 02 or AHITYP5 = 02 or AHITYP6 = 02 otherwise AUGMENTED-CAID Å 0
� Column 9 (CPS Total C): This is the weighted sum of AUGMENTED-CAID (described immediately above) that includes only CPS records with CPS_DS = R.
Rows:
� Age is determined as described above; age range follows directly. � Race is determined as described above. Because “Unknown Race” occurs only in MSIS,
only MSIS records with SSN value unverified can have this code. � Sex is determined as described above. � Ethnicity is determined as described above.
Table 3:
Table 3 is a tabulation of CPS individual respondent records that have been linked (by Protected Identity Key, which substitutes SSN) to summarized MSIS person records that show actual Medicaid enrollment: TOT_DAYS_ANY > 0. Table 3 is organized into eight versions:
26
Version Page #
Enrollees With Full Benefits:
A. Full Benefit Enrollees ..................................................................................1 - 3 B. Full Benefit Enrollees Whose CPS Insurance Status Was Edited ...............4 - 6 C. Full Benefit Enrollees Whose CPS Insurance Status Was Imputed ............7 - 9 D. Full Benefit Enrollees Whose CPS Insurance Status Was Reported.........10 - 12
Enrollees With Any Benefits:
E. All Enrollees ............................................................................................. 13 – 15 F. All Enrollees Whose CPS Insurance Status Was Edited ...........................16 - 18 G. All Enrollees Whose CPS Insurance Status Was Imputed ........................19 - 21 H. All Enrollees Whose CPS Insurance Status Was Reported .......................22 - 24
Note that the first four versions (A – D) tabulate CPS respondent records showing at least one day of Medicaid enrollment with full benefits (TOT_DAYS_FULL > 0). Version A is a tabulation of all such qualifying records. Version B is a tabulation of qualifying records that have CPS Medicaid enrollment status edited (CPS_DS = E). Version C is a tabulation of records that have enrollment status imputed (CPS_DS = I). Version D is a tabulation of records that have enrollment status reported explicitly (CPS_DS = R).
The second four versions (E – H) are identical to the first four except, rather that including only CPS records linked to an MSIS record showing full benefits, it includes all CPS records showing any type of Medicaid enrollment (that is having TOT_DAYS_ANY > 0). Version E is a tabulation of all such qualifying records. Version F is a tabulation of qualifying records that have CPS Medicaid enrollment status edited (CPS_DS = E). Version G is a tabulation of records that have enrollment status imputed (CPS_DS = I). Version H is a tabulation of records that have enrollment status reported explicitly (CPS_DS = R).
Columns:
Columns 1 – 6 tabulate CPS records by CPS_HI, so that… Data column 1: CPS_HI = 1 Data column 2: CPS_HI = 2
… …
Column 7 totals Columns 1 – 6. Each data column also has a parenthetical percentage value that is that cells main tabulation value into the Column 7 row total.
Rows:
Age category, race, sex, and ethnicity are determined identically to Tables 1 and 2. CPS SSI recipiency status and CPS TANF recipiency status are determined by CPS_SSI and CPS_TANF (as described in CPS Coding discussion). MSIS SSI recipiency status is determined by SSI_CASH (as described in the MSIS Summarization discussion). Medicaid benefit type is
27
determined by BEN_TYPE (1 - ‘Full Benefits’, 2 - ‘Partial not CHIP’, 3 - ‘Medicaid-expansion CHIP’, see MSIS Coding discussion). Poverty level comes directly from the CPS variable POVLL.
“Relationship to Respondent” is determined by the CPS variable A_RRP. Note that the category 5 is split into “Non-Adult Children” (age 17 or less on December 31 of reference year, see Joint Demographic Characterization discussion on age determination above) and “Adult Children” (age 18 or greater on December 31 of reference year see Joint Demographic Characterization on age determination above).
MAX Managed-Care/Medical-Service Received (or Noted) is determined as follows:
Managed care enrollment is determined by review of the MAX fields MEDICAID-MANAGED-CARE-COMBINATION (separate fields exist for each month of reference year):
If MANAGED-CARE-COMBINATION ever has value ≠ ‘ ’ (space-filled), 00, 99 or 16 then represented person is said to have had some managed care coverage during reference year.
Received service is determined by review of the MAX field RECIPIENT-INDICATOR:
In some cases, we cannot locate a MAX record for a person represented in MSIS. In this case, tabulations are made to the row “No MAX data available.”
Table 4:
Table 4 is a tabulation of CPS individual respondent records for persons for whom Medicaid enrollment cannot be established. In most cases, the CPS records for these persons will have no corresponding MSIS record (that is, an MSIS record for the same PIK or same SSN). In some cases, there may be a corresponding MSIS record, but this record does not show that person having received Medicaid benefits in the reference year. This may occur if the person is enrolled in a stand-alone SCHIP or there is some other quirk in the way states provide their person data to CMS. Table 3 and Table 4 are complementary: all CPS records are tabulated in one or the other, but none are tabulated in both.
Table 4 is presented in eight versions. The first four versions (A – D) tabulate unmatchable CPS records (because the respondent refused to provide the SSN, PUSSN_FLG = R, or the provided SSN could not be validated by Census). The second four versions (E – H) tabulate matchable CPS
28
records (because a validated SSN resides on the record). Because the re-weighting process shifts the entire weight on un-matchable records to matchable records, in re-weighted presentations, Versions A, B, C, and D are suppressed; otherwise all cells for these versions would be filled with zero values. As with Table 3, in each set of four versions, all qualifying records are tabulated in the first version (A or E) and in one and only one of the remaining three based on the value of CPS_DS. So, Table 4 is organized as:
Original Wgt.Reweighted Presentation Presentation
Version Page # Page #
Unmatchable Respondents:
A. All Unmatchable Respondents...........................................1 – 2 N/A B. Whose CPS Insurance Status Was Edited .........................3 – 4 N/A C. Whose CPS Insurance Status Was Imputed.......................5 – 6 N/A D. CPS Insurance Status Was Reported .................................7 – 8 N/A
Matchable CPS Respondents not Known Receiving Medicaid:
E. All Respondents Not Known Receiving Medicaid...........9 – 10 1 – 2 F. Whose CPS Insurance Status Was Edited .......................11 – 12 3 – 4 G. Whose CPS Insurance Status Was Imputed.....................13 – 14 5 – 6 H. Whose CPS Insurance Status Was Reported ...................15 – 16 7 – 8
For Table 4, rows and columns tabulations are determined identically to Table 3, except, certain rows that for Table 3 are tabulated based on values in corresponding MSIS records are suppressed, as the tabulations in them would be essentially meaningless, otherwise.
29
Appendix V: Detailed Tables
30
1
Phase II, Table 1: Overview of CPS to MSIS Record Linking Process
Unweighted Presentation
CY 2000 Expanded Sample, Original Weight
Selected Characteristics
CPS
Not Valid SSN
CPS
Valid SSN Not
Matched
CPS Refused
to Provide
SSN
MSIS
Not Valid
SSN
MSIS
Valid SSN But Not
Matched
Valid SSN and
Matched
% CPS Persons
Matched
% MSIS Persons
Matched
Total 16,100 150,000 28,200 4,550,000 39,850,000 23,700 13.6% 0.059%
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 39
2
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 40
3
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
Virginia 684,000 652,000 611,000 608,000 580,000 539,000 460,000 420,000 300,000
Washington 908,000 908,000 902,000 901,000 900,000 861,000 660,000 520,000 340,000
West Virginia 326,000 325,000 315,000 314,000 314,000 293,000 220,000 200,000 140,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 41
4
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 42
5
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
State=California
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 8,080,000 8,050,000 5,630,000 5,620,000 5,580,000 5,320,000 4,640,000 4,260,000 3,020,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 43
6
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
State=Florida
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,120,000 2,080,000 1,920,000 1,910,000 1,910,000 1,850,000 1,680,000 1,340,000 920,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 44
7
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
State=New York
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 3,260,000 3,260,000 3,210,000 3,190,000 3,150,000 2,770,000 2,720,000 2,360,000 1,680,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 45
8
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Original Weight
State=Texas
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,620,000 2,590,000 2,410,000 2,400,000 2,400,000 2,280,000 1,840,000 1,580,000 1,100,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 46
1
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Re-Weighted
State=U.S. Total
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 45,050,000 43,650,000 39,750,000 39,600,000 38,150,000 36,200,000 29,700,000 26,150,000 18,700,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 47
2
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Re-Weighted
State=California
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 8,080,000 8,050,000 5,630,000 5,620,000 5,580,000 5,320,000 4,120,000 3,780,000 2,680,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 48
3
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Re-Weighted
State=Florida
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,120,000 2,080,000 1,920,000 1,910,000 1,910,000 1,850,000 1,680,000 1,320,000 920,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 49
4
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Re-Weighted
State=New York
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 3,260,000 3,260,000 3,210,000 3,190,000 3,150,000 2,770,000 2,580,000 2,220,000 1,540,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 50
5
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2000 Expanded Sample, Re-Weighted
State=Texas
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,620,000 2,590,000 2,410,000 2,400,000 2,400,000 2,280,000 1,960,000 1,680,000 1,140,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 51
1
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Original Weight
Version=A: CPS-MSIS Matched Records, Receiving Full Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 7,480,000 (37.5%) 3,820,000 (19.1%) 1,520,000 (7.6%) 3,740,000 (18.7%) 380,000 (1.9%) 3,040,000 (15.2%) 19,950,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 300,000 (19.2%) 200,000 (12.8%) 100,000 (6.4%) 540,000 (34.6%) 40,000 (2.6%) 400,000 (25.6%) 1,560,000
MAX No Mngd. Care, Med. Service Received 2,600,000 (37.8%) 1,640,000 (23.8%) 580,000 (8.4%) 940,000 (13.7%) 140,000 (2.0%) 980,000 (14.2%) 6,880,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,280,000 (33.3%) 520,000 (13.5%) 240,000 (6.3%) 1,080,000 (28.1%) 60,000 (1.6%) 660,000 (17.2%) 3,840,000
MAX Some Mngd. Care, Med. Service Noted 6,660,000 (49.9%) 1,980,000 (14.8%) 720,000 (5.4%) 2,020,000 (15.1%) 160,000 (1.2%) 1,800,000 (13.5%) 13,350,000
No MAX Data Available 60,000 (33.3%) 20,000 (11.1%) 0 (0.0%) 60,000 (33.3%) 0 (0.0%) 40,000 (22.2%) 180,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 8,680,000 (49.3%) 3,380,000 (19.2%) 1,140,000 (6.5%) 2,180,000 (12.4%) 260,000 (1.5%) 1,980,000 (11.3%) 17,600,000
Began Receiving Q2 Prev. Year 500,000 (39.7%) 200,000 (15.9%) 80,000 (6.3%) 260,000 (20.6%) 20,000 (1.6%) 200,000 (15.9%) 1,260,000
Began Receiving Q3 Prev. Year 460,000 (38.3%) 200,000 (16.7%) 100,000 (8.3%) 220,000 (18.3%) 20,000 (1.7%) 200,000 (16.7%) 1,200,000
Began Receiving Q4 Prev. Year 420,000 (31.3%) 180,000 (13.4%) 80,000 (6.0%) 320,000 (23.9%) 40,000 (3.0%) 320,000 (23.9%) 1,340,000
Eligible for < 61 Days of Previous Year 140,000 (29.2%) 40,000 (8.3%) 40,000 (8.3%) 100,000 (20.8%) 20,000 (4.2%) 160,000 (33.3%) 480,000
Eligible for 61 to 180 Days of Prev. Year 780,000 (35.8%) 340,000 (15.6%) 140,000 (6.4%) 460,000 (21.1%) 40,000 (1.8%) 440,000 (20.2%) 2,180,000
Eligible for > 180 Days of Prev. Year 9,160,000 (48.9%) 3,560,000 (19.0%) 1,220,000 (6.5%) 2,400,000 (12.8%) 280,000 (1.5%) 2,100,000 (11.2%) 18,750,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 120,000 (11.8%) 80,000 (7.8%) 60,000 (5.9%) 460,000 (45.1%) 20,000 (2.0%) 280,000 (27.5%) 1,020,000
Last Received Q2 Prev. Year 160,000 (15.7%) 80,000 (7.8%) 80,000 (7.8%) 440,000 (43.1%) 20,000 (2.0%) 280,000 (27.5%) 1,020,000
Last Received Q3 Prev. Year 240,000 (19.7%) 120,000 (9.8%) 80,000 (6.6%) 420,000 (34.4%) 20,000 (1.6%) 320,000 (26.2%) 1,220,000
Last Received Q4 Prev. Year 320,000 (27.1%) 140,000 (11.9%) 60,000 (5.1%) 340,000 (28.8%) 20,000 (1.7%) 300,000 (25.4%) 1,180,000
Eligible for < 61 Days of Previous Year 100,000 (12.5%) 60,000 (7.5%) 40,000 (5.0%) 360,000 (45.0%) 20,000 (2.5%) 240,000 (30.0%) 800,000
Eligible for 61 to 180 Days of Prev. Year 200,000 (14.7%) 120,000 (8.8%) 80,000 (5.9%) 560,000 (41.2%) 20,000 (1.5%) 340,000 (25.0%) 1,360,000
Eligible for > 180 Days of Prev. Year 540,000 (23.5%) 240,000 (10.4%) 140,000 (6.1%) 740,000 (32.2%) 40,000 (1.7%) 600,000 (26.1%) 2,300,000
*Due to rounding, total values may not equal column or row sums. 54
4
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Original Weight
Version=B: CPS-MSIS Matched Records, Receiving Full Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 6,680,000 (40.2%) 2,880,000 (17.3%) 1,380,000 (8.3%) 2,860,000 (17.2%) 300,000 (1.8%) 2,480,000 (14.9%) 16,600,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 240,000 (19.0%) 120,000 (9.5%) 80,000 (6.3%) 460,000 (36.5%) 20,000 (1.6%) 340,000 (27.0%) 1,260,000
MAX No Mngd. Care, Med. Service Received 2,280,000 (39.7%) 1,300,000 (22.6%) 500,000 (8.7%) 680,000 (11.8%) 100,000 (1.7%) 840,000 (14.6%) 5,740,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,080,000 (35.5%) 240,000 (7.9%) 240,000 (7.9%) 880,000 (28.9%) 60,000 (2.0%) 520,000 (17.1%) 3,040,000
MAX Some Mngd. Care, Med. Service Noted 6,040,000 (53.9%) 1,460,000 (13.0%) 680,000 (6.1%) 1,500,000 (13.4%) 140,000 (1.3%) 1,380,000 (12.3%) 11,200,000
No MAX Data Available 60,000 (37.5%) 20,000 (12.5%) 0 (0.0%) 40,000 (25.0%) 0 (0.0%) 40,000 (25.0%) 160,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 7,860,000 (54.2%) 2,440,000 (16.8%) 1,040,000 (7.2%) 1,520,000 (10.5%) 180,000 (1.2%) 1,460,000 (10.1%) 14,500,000
Began Receiving Q2 Prev. Year 460,000 (43.4%) 140,000 (13.2%) 80,000 (7.5%) 180,000 (17.0%) 20,000 (1.9%) 160,000 (15.1%) 1,060,000
Began Receiving Q3 Prev. Year 400,000 (40.8%) 140,000 (14.3%) 100,000 (10.2%) 160,000 (16.3%) 20,000 (2.0%) 180,000 (18.4%) 980,000
Began Receiving Q4 Prev. Year 340,000 (30.9%) 120,000 (10.9%) 60,000 (5.5%) 280,000 (25.5%) 20,000 (1.8%) 280,000 (25.5%) 1,100,000
Eligible for < 61 Days of Previous Year 100,000 (26.3%) 20,000 (5.3%) 40,000 (10.5%) 100,000 (26.3%) 20,000 (5.3%) 120,000 (31.6%) 380,000
Eligible for 61 to 180 Days of Prev. Year 680,000 (37.0%) 240,000 (13.0%) 120,000 (6.5%) 360,000 (19.6%) 20,000 (1.1%) 400,000 (21.7%) 1,840,000
Eligible for > 180 Days of Prev. Year 8,260,000 (53.5%) 2,580,000 (16.7%) 1,120,000 (7.2%) 1,680,000 (10.9%) 220,000 (1.4%) 1,560,000 (10.1%) 15,450,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 80,000 (9.3%) 40,000 (4.7%) 40,000 (4.7%) 420,000 (48.8%) 20,000 (2.3%) 240,000 (27.9%) 860,000
Last Received Q2 Prev. Year 120,000 (14.0%) 60,000 (7.0%) 60,000 (7.0%) 360,000 (41.9%) 20,000 (2.3%) 260,000 (30.2%) 860,000
Last Received Q3 Prev. Year 180,000 (17.6%) 100,000 (9.8%) 80,000 (7.8%) 360,000 (35.3%) 20,000 (2.0%) 280,000 (27.5%) 1,020,000
Last Received Q4 Prev. Year 260,000 (26.5%) 100,000 (10.2%) 40,000 (4.1%) 300,000 (30.6%) 20,000 (2.0%) 260,000 (26.5%) 980,000
Eligible for < 61 Days of Previous Year 60,000 (9.1%) 40,000 (6.1%) 40,000 (6.1%) 320,000 (48.5%) 20,000 (3.0%) 200,000 (30.3%) 660,000
Eligible for 61 to 180 Days of Prev. Year 140,000 (12.3%) 80,000 (7.0%) 80,000 (7.0%) 480,000 (42.1%) 20,000 (1.8%) 320,000 (28.1%) 1,140,000
Eligible for > 180 Days of Prev. Year 440,000 (22.9%) 180,000 (9.4%) 140,000 (7.3%) 620,000 (32.3%) 40,000 (2.1%) 520,000 (27.1%) 1,920,000
*Due to rounding, total values may not equal column or row sums. 63
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Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Original Weight
Version=E: CPS-MSIS Matched Records, Receiving Any Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 7,720,000 (36.0%) 4,060,000 (18.9%) 1,820,000 (8.5%) 4,040,000 (18.8%) 480,000 (2.2%) 3,320,000 (15.5%) 21,450,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 340,000 (16.3%) 260,000 (12.5%) 220,000 (10.6%) 660,000 (31.7%) 100,000 (4.8%) 500,000 (24.0%) 2,080,000
MAX No Mngd. Care, Med. Service Received 2,660,000 (36.2%) 1,740,000 (23.7%) 700,000 (9.5%) 1,000,000 (13.6%) 160,000 (2.2%) 1,080,000 (14.7%) 7,340,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,300,000 (32.7%) 520,000 (13.1%) 260,000 (6.5%) 1,120,000 (28.1%) 80,000 (2.0%) 700,000 (17.6%) 3,980,000
MAX Some Mngd. Care, Med. Service Noted 6,780,000 (49.5%) 2,040,000 (14.9%) 760,000 (5.5%) 2,100,000 (15.3%) 160,000 (1.2%) 1,860,000 (13.6%) 13,700,000
No MAX Data Available 60,000 (30.0%) 20,000 (10.0%) 0 (0.0%) 60,000 (30.0%) 0 (0.0%) 40,000 (20.0%) 200,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 9,060,000 (47.4%) 3,660,000 (19.2%) 1,420,000 (7.4%) 2,420,000 (12.7%) 340,000 (1.8%) 2,200,000 (11.5%) 19,100,000
Began Receiving Q2 Prev. Year 520,000 (39.4%) 200,000 (15.2%) 100,000 (7.6%) 260,000 (19.7%) 40,000 (3.0%) 200,000 (15.2%) 1,320,000
Began Receiving Q3 Prev. Year 440,000 (34.9%) 200,000 (15.9%) 120,000 (9.5%) 240,000 (19.0%) 40,000 (3.2%) 220,000 (17.5%) 1,260,000
Began Receiving Q4 Prev. Year 420,000 (29.6%) 160,000 (11.3%) 80,000 (5.6%) 360,000 (25.4%) 40,000 (2.8%) 340,000 (23.9%) 1,420,000
Eligible for < 61 Days of Previous Year 140,000 (26.9%) 40,000 (7.7%) 40,000 (7.7%) 120,000 (23.1%) 20,000 (3.8%) 160,000 (30.8%) 520,000
Eligible for 61 to 180 Days of Prev. Year 740,000 (32.7%) 340,000 (15.0%) 160,000 (7.1%) 500,000 (22.1%) 40,000 (1.8%) 480,000 (21.2%) 2,260,000
Eligible for > 180 Days of Prev. Year 9,560,000 (47.1%) 3,860,000 (19.0%) 1,520,000 (7.5%) 2,660,000 (13.1%) 380,000 (1.9%) 2,320,000 (11.4%) 20,300,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 100,000 (10.0%) 60,000 (6.0%) 60,000 (6.0%) 460,000 (46.0%) 20,000 (2.0%) 280,000 (28.0%) 1,000,000
Last Received Q2 Prev. Year 140,000 (13.5%) 100,000 (9.6%) 80,000 (7.7%) 420,000 (40.4%) 20,000 (1.9%) 280,000 (26.9%) 1,040,000
Last Received Q3 Prev. Year 200,000 (17.9%) 80,000 (7.1%) 60,000 (5.4%) 420,000 (37.5%) 20,000 (1.8%) 320,000 (28.6%) 1,120,000
Last Received Q4 Prev. Year 260,000 (23.6%) 120,000 (10.9%) 40,000 (3.6%) 340,000 (30.9%) 20,000 (1.8%) 300,000 (27.3%) 1,100,000
Eligible for < 61 Days of Previous Year 80,000 (10.3%) 40,000 (5.1%) 40,000 (5.1%) 340,000 (43.6%) 20,000 (2.6%) 260,000 (33.3%) 780,000
Eligible for 61 to 180 Days of Prev. Year 180,000 (13.6%) 120,000 (9.1%) 80,000 (6.1%) 580,000 (43.9%) 20,000 (1.5%) 340,000 (25.8%) 1,320,000
Eligible for > 180 Days of Prev. Year 460,000 (21.3%) 200,000 (9.3%) 120,000 (5.6%) 740,000 (34.3%) 40,000 (1.9%) 600,000 (27.8%) 2,160,000
*Due to rounding, total values may not equal column or row sums. 66
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Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Original Weight
Version=F: CPS-MSIS Matched Records, Receiving Any Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 6,880,000 (38.5%) 3,060,000 (17.1%) 1,660,000 (9.3%) 3,120,000 (17.5%) 380,000 (2.1%) 2,720,000 (15.2%) 17,850,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 260,000 (15.3%) 160,000 (9.4%) 200,000 (11.8%) 560,000 (32.9%) 80,000 (4.7%) 420,000 (24.7%) 1,700,000
MAX No Mngd. Care, Med. Service Received 2,360,000 (38.6%) 1,380,000 (22.5%) 600,000 (9.8%) 740,000 (12.1%) 120,000 (2.0%) 920,000 (15.0%) 6,120,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,100,000 (34.8%) 260,000 (8.2%) 260,000 (8.2%) 940,000 (29.7%) 60,000 (1.9%) 560,000 (17.7%) 3,160,000
MAX Some Mngd. Care, Med. Service Noted 6,140,000 (53.4%) 1,500,000 (13.0%) 720,000 (6.3%) 1,560,000 (13.6%) 140,000 (1.2%) 1,440,000 (12.5%) 11,500,000
No MAX Data Available 60,000 (37.5%) 20,000 (12.5%) 0 (0.0%) 40,000 (25.0%) 0 (0.0%) 40,000 (25.0%) 160,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 8,200,000 (51.9%) 2,680,000 (17.0%) 1,280,000 (8.1%) 1,720,000 (10.9%) 240,000 (1.5%) 1,640,000 (10.4%) 15,800,000
Began Receiving Q2 Prev. Year 460,000 (41.1%) 160,000 (14.3%) 100,000 (8.9%) 200,000 (17.9%) 40,000 (3.6%) 180,000 (16.1%) 1,120,000
Began Receiving Q3 Prev. Year 380,000 (37.3%) 140,000 (13.7%) 100,000 (9.8%) 160,000 (15.7%) 20,000 (2.0%) 180,000 (17.6%) 1,020,000
Began Receiving Q4 Prev. Year 340,000 (29.3%) 120,000 (10.3%) 80,000 (6.9%) 320,000 (27.6%) 40,000 (3.4%) 300,000 (25.9%) 1,160,000
Eligible for < 61 Days of Previous Year 100,000 (23.8%) 20,000 (4.8%) 40,000 (9.5%) 120,000 (28.6%) 20,000 (4.8%) 120,000 (28.6%) 420,000
Eligible for 61 to 180 Days of Prev. Year 640,000 (34.0%) 240,000 (12.8%) 160,000 (8.5%) 400,000 (21.3%) 40,000 (2.1%) 420,000 (22.3%) 1,880,000
Eligible for > 180 Days of Prev. Year 8,640,000 (51.4%) 2,820,000 (16.8%) 1,380,000 (8.2%) 1,880,000 (11.2%) 300,000 (1.8%) 1,760,000 (10.5%) 16,800,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 60,000 (7.3%) 20,000 (2.4%) 40,000 (4.9%) 420,000 (51.2%) 20,000 (2.4%) 260,000 (31.7%) 820,000
Last Received Q2 Prev. Year 100,000 (11.1%) 60,000 (6.7%) 80,000 (8.9%) 360,000 (40.0%) 20,000 (2.2%) 260,000 (28.9%) 900,000
Last Received Q3 Prev. Year 140,000 (14.9%) 60,000 (6.4%) 60,000 (6.4%) 360,000 (38.3%) 20,000 (2.1%) 280,000 (29.8%) 940,000
Last Received Q4 Prev. Year 220,000 (23.9%) 100,000 (10.9%) 40,000 (4.3%) 300,000 (32.6%) 20,000 (2.2%) 260,000 (28.3%) 920,000
Eligible for < 61 Days of Previous Year 60,000 (9.4%) 20,000 (3.1%) 40,000 (6.3%) 300,000 (46.9%) 20,000 (3.1%) 220,000 (34.4%) 640,000
Eligible for 61 to 180 Days of Prev. Year 120,000 (10.7%) 80,000 (7.1%) 80,000 (7.1%) 500,000 (44.6%) 20,000 (1.8%) 320,000 (28.6%) 1,120,000
Eligible for > 180 Days of Prev. Year 360,000 (20.0%) 140,000 (7.8%) 120,000 (6.7%) 620,000 (34.4%) 40,000 (2.2%) 520,000 (28.9%) 1,800,000
*Due to rounding, total values may not equal column or row sums. 75
1
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Re-Weighted
Version=A: CPS-MSIS Matched Records, Receiving Full Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 9,180,000 (35.4%) 5,060,000 (19.5%) 2,040,000 (7.9%) 4,700,000 (18.1%) 500,000 (1.9%) 4,500,000 (17.3%) 25,950,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 380,000 (18.4%) 240,000 (11.7%) 120,000 (5.8%) 680,000 (33.0%) 40,000 (1.9%) 600,000 (29.1%) 2,060,000
MAX No Mngd. Care, Med. Service Received 3,220,000 (35.2%) 2,200,000 (24.1%) 860,000 (9.4%) 1,200,000 (13.1%) 200,000 (2.2%) 1,480,000 (16.2%) 9,140,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,560,000 (31.7%) 680,000 (13.8%) 300,000 (6.1%) 1,320,000 (26.8%) 80,000 (1.6%) 980,000 (19.9%) 4,920,000
MAX Some Mngd. Care, Med. Service Noted 8,140,000 (47.7%) 2,580,000 (15.1%) 920,000 (5.4%) 2,560,000 (15.0%) 220,000 (1.3%) 2,660,000 (15.6%) 17,050,000
No MAX Data Available 80,000 (33.3%) 20,000 (8.3%) 20,000 (8.3%) 80,000 (33.3%) 0 (0.0%) 60,000 (25.0%) 240,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 10,650,000 (46.8%) 4,480,000 (19.7%) 1,540,000 (6.8%) 2,780,000 (12.2%) 360,000 (1.6%) 2,960,000 (13.0%) 22,750,000
Began Receiving Q2 Prev. Year 620,000 (38.8%) 260,000 (16.3%) 100,000 (6.3%) 320,000 (20.0%) 20,000 (1.3%) 280,000 (17.5%) 1,600,000
Began Receiving Q3 Prev. Year 560,000 (36.4%) 240,000 (15.6%) 120,000 (7.8%) 280,000 (18.2%) 20,000 (1.3%) 300,000 (19.5%) 1,540,000
Began Receiving Q4 Prev. Year 500,000 (28.7%) 220,000 (12.6%) 100,000 (5.7%) 400,000 (23.0%) 40,000 (2.3%) 480,000 (27.6%) 1,740,000
Eligible for < 61 Days of Previous Year 160,000 (25.0%) 40,000 (6.3%) 40,000 (6.3%) 140,000 (21.9%) 20,000 (3.1%) 240,000 (37.5%) 640,000
Eligible for 61 to 180 Days of Prev. Year 940,000 (33.3%) 440,000 (15.6%) 160,000 (5.7%) 560,000 (19.9%) 40,000 (1.4%) 660,000 (23.4%) 2,820,000
Eligible for > 180 Days of Prev. Year 11,200,000 (46.4%) 4,720,000 (19.5%) 1,660,000 (6.9%) 3,060,000 (12.7%) 380,000 (1.6%) 3,120,000 (12.9%) 24,150,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 160,000 (11.9%) 100,000 (7.5%) 80,000 (6.0%) 580,000 (43.3%) 20,000 (1.5%) 400,000 (29.9%) 1,340,000
Last Received Q2 Prev. Year 180,000 (13.4%) 100,000 (7.5%) 80,000 (6.0%) 540,000 (40.3%) 20,000 (1.5%) 400,000 (29.9%) 1,340,000
Last Received Q3 Prev. Year 300,000 (18.5%) 160,000 (9.9%) 120,000 (7.4%) 540,000 (33.3%) 20,000 (1.2%) 480,000 (29.6%) 1,620,000
Last Received Q4 Prev. Year 380,000 (25.0%) 180,000 (11.8%) 60,000 (3.9%) 420,000 (27.6%) 20,000 (1.3%) 440,000 (28.9%) 1,520,000
Eligible for < 61 Days of Previous Year 120,000 (11.5%) 80,000 (7.7%) 60,000 (5.8%) 440,000 (42.3%) 20,000 (1.9%) 340,000 (32.7%) 1,040,000
Eligible for 61 to 180 Days of Prev. Year 260,000 (14.6%) 160,000 (9.0%) 100,000 (5.6%) 700,000 (39.3%) 40,000 (2.2%) 520,000 (29.2%) 1,780,000
Eligible for > 180 Days of Prev. Year 660,000 (22.0%) 300,000 (10.0%) 200,000 (6.7%) 920,000 (30.7%) 40,000 (1.3%) 880,000 (29.3%) 3,000,000
*Due to rounding, total values may not equal column or row sums. 78
4
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Re-Weighted
Version=B: CPS-MSIS Matched Records, Receiving Full Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 8,080,000 (38.8%) 3,680,000 (17.7%) 1,780,000 (8.6%) 3,380,000 (16.3%) 360,000 (1.7%) 3,540,000 (17.0%) 20,800,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 280,000 (17.5%) 140,000 (8.8%) 100,000 (6.3%) 560,000 (35.0%) 40,000 (2.5%) 480,000 (30.0%) 1,600,000
MAX No Mngd. Care, Med. Service Received 2,780,000 (37.9%) 1,700,000 (23.2%) 680,000 (9.3%) 800,000 (10.9%) 140,000 (1.9%) 1,220,000 (16.6%) 7,340,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,300,000 (34.6%) 300,000 (8.0%) 280,000 (7.4%) 1,060,000 (28.2%) 60,000 (1.6%) 740,000 (19.7%) 3,760,000
MAX Some Mngd. Care, Med. Service Noted 7,280,000 (52.8%) 1,820,000 (13.2%) 840,000 (6.1%) 1,760,000 (12.8%) 160,000 (1.2%) 1,960,000 (14.2%) 13,800,000
No MAX Data Available 60,000 (30.0%) 20,000 (10.0%) 0 (0.0%) 60,000 (30.0%) 0 (0.0%) 40,000 (20.0%) 200,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 9,500,000 (52.5%) 3,140,000 (17.3%) 1,340,000 (7.4%) 1,800,000 (9.9%) 220,000 (1.2%) 2,100,000 (11.6%) 18,100,000
Began Receiving Q2 Prev. Year 540,000 (40.9%) 180,000 (13.6%) 100,000 (7.6%) 220,000 (16.7%) 20,000 (1.5%) 240,000 (18.2%) 1,320,000
Began Receiving Q3 Prev. Year 480,000 (39.3%) 180,000 (14.8%) 120,000 (9.8%) 180,000 (14.8%) 20,000 (1.6%) 240,000 (19.7%) 1,220,000
Began Receiving Q4 Prev. Year 400,000 (28.6%) 160,000 (11.4%) 80,000 (5.7%) 320,000 (22.9%) 40,000 (2.9%) 380,000 (27.1%) 1,400,000
Eligible for < 61 Days of Previous Year 120,000 (25.0%) 20,000 (4.2%) 40,000 (8.3%) 120,000 (25.0%) 20,000 (4.2%) 180,000 (37.5%) 480,000
Eligible for 61 to 180 Days of Prev. Year 800,000 (34.8%) 300,000 (13.0%) 160,000 (7.0%) 420,000 (18.3%) 40,000 (1.7%) 580,000 (25.2%) 2,300,000
Eligible for > 180 Days of Prev. Year 10,000,000 (52.1%) 3,320,000 (17.3%) 1,440,000 (7.5%) 1,980,000 (10.3%) 260,000 (1.4%) 2,220,000 (11.6%) 19,200,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 100,000 (9.3%) 40,000 (3.7%) 60,000 (5.6%) 480,000 (44.4%) 20,000 (1.9%) 340,000 (31.5%) 1,080,000
Last Received Q2 Prev. Year 140,000 (12.7%) 60,000 (5.5%) 80,000 (7.3%) 440,000 (40.0%) 20,000 (1.8%) 360,000 (32.7%) 1,100,000
Last Received Q3 Prev. Year 220,000 (16.9%) 120,000 (9.2%) 100,000 (7.7%) 420,000 (32.3%) 20,000 (1.5%) 420,000 (32.3%) 1,300,000
Last Received Q4 Prev. Year 320,000 (25.4%) 140,000 (11.1%) 60,000 (4.8%) 340,000 (27.0%) 20,000 (1.6%) 360,000 (28.6%) 1,260,000
Eligible for < 61 Days of Previous Year 80,000 (9.5%) 40,000 (4.8%) 40,000 (4.8%) 380,000 (45.2%) 20,000 (2.4%) 280,000 (33.3%) 840,000
Eligible for 61 to 180 Days of Prev. Year 180,000 (12.5%) 100,000 (6.9%) 100,000 (6.9%) 580,000 (40.3%) 20,000 (1.4%) 460,000 (31.9%) 1,440,000
Eligible for > 180 Days of Prev. Year 520,000 (21.3%) 220,000 (9.0%) 160,000 (6.6%) 740,000 (30.3%) 40,000 (1.6%) 740,000 (30.3%) 2,440,000
*Due to rounding, total values may not equal column or row sums. 87
13
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Re-Weighted
Version=E: CPS-MSIS Matched Records, Receiving Any Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 9,480,000 (33.9%) 5,360,000 (19.2%) 2,460,000 (8.8%) 5,080,000 (18.2%) 660,000 (2.4%) 4,920,000 (17.6%) 27,950,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 420,000 (15.0%) 340,000 (12.1%) 320,000 (11.4%) 820,000 (29.3%) 140,000 (5.0%) 760,000 (27.1%) 2,800,000
MAX No Mngd. Care, Med. Service Received 3,300,000 (33.7%) 2,340,000 (23.9%) 1,020,000 (10.4%) 1,280,000 (13.1%) 240,000 (2.5%) 1,600,000 (16.4%) 9,780,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,580,000 (31.0%) 680,000 (13.3%) 340,000 (6.7%) 1,380,000 (27.1%) 100,000 (2.0%) 1,020,000 (20.0%) 5,100,000
MAX Some Mngd. Care, Med. Service Noted 8,280,000 (47.3%) 2,660,000 (15.2%) 960,000 (5.5%) 2,640,000 (15.1%) 220,000 (1.3%) 2,740,000 (15.7%) 17,500,000
No MAX Data Available 80,000 (30.8%) 40,000 (15.4%) 20,000 (7.7%) 80,000 (30.8%) 0 (0.0%) 60,000 (23.1%) 260,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 11,100,000 (44.8%) 4,880,000 (19.7%) 1,940,000 (7.8%) 3,080,000 (12.4%) 460,000 (1.9%) 3,280,000 (13.3%) 24,750,000
Began Receiving Q2 Prev. Year 620,000 (36.5%) 260,000 (15.3%) 120,000 (7.1%) 340,000 (20.0%) 40,000 (2.4%) 300,000 (17.6%) 1,700,000
Began Receiving Q3 Prev. Year 540,000 (33.3%) 260,000 (16.0%) 140,000 (8.6%) 320,000 (19.8%) 40,000 (2.5%) 320,000 (19.8%) 1,620,000
Began Receiving Q4 Prev. Year 500,000 (27.2%) 220,000 (12.0%) 120,000 (6.5%) 440,000 (23.9%) 40,000 (2.2%) 520,000 (28.3%) 1,840,000
Eligible for < 61 Days of Previous Year 160,000 (23.5%) 40,000 (5.9%) 40,000 (5.9%) 160,000 (23.5%) 20,000 (2.9%) 240,000 (35.3%) 680,000
Eligible for 61 to 180 Days of Prev. Year 900,000 (30.8%) 440,000 (15.1%) 220,000 (7.5%) 640,000 (21.9%) 60,000 (2.1%) 700,000 (24.0%) 2,920,000
Eligible for > 180 Days of Prev. Year 11,700,000 (44.5%) 5,120,000 (19.5%) 2,080,000 (7.9%) 3,380,000 (12.9%) 520,000 (2.0%) 3,480,000 (13.2%) 26,300,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 140,000 (10.8%) 80,000 (6.2%) 80,000 (6.2%) 580,000 (44.6%) 20,000 (1.5%) 420,000 (32.3%) 1,300,000
Last Received Q2 Prev. Year 180,000 (13.2%) 120,000 (8.8%) 100,000 (7.4%) 520,000 (38.2%) 20,000 (1.5%) 420,000 (30.9%) 1,360,000
Last Received Q3 Prev. Year 260,000 (17.6%) 100,000 (6.8%) 80,000 (5.4%) 540,000 (36.5%) 20,000 (1.4%) 480,000 (32.4%) 1,480,000
Last Received Q4 Prev. Year 340,000 (23.9%) 160,000 (11.3%) 60,000 (4.2%) 420,000 (29.6%) 20,000 (1.4%) 440,000 (31.0%) 1,420,000
Eligible for < 61 Days of Previous Year 100,000 (9.8%) 40,000 (3.9%) 60,000 (5.9%) 420,000 (41.2%) 20,000 (2.0%) 380,000 (37.3%) 1,020,000
Eligible for 61 to 180 Days of Prev. Year 240,000 (14.0%) 140,000 (8.1%) 100,000 (5.8%) 720,000 (41.9%) 40,000 (2.3%) 500,000 (29.1%) 1,720,000
Eligible for > 180 Days of Prev. Year 560,000 (19.9%) 260,000 (9.2%) 160,000 (5.7%) 900,000 (31.9%) 40,000 (1.4%) 880,000 (31.2%) 2,820,000
*Due to rounding, total values may not equal column or row sums. 90
16
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Re-Weighted
Version=F: CPS-MSIS Matched Records, Receiving Any Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 8,320,000 (37.0%) 3,920,000 (17.4%) 2,160,000 (9.6%) 3,700,000 (16.4%) 480,000 (2.1%) 3,900,000 (17.3%) 22,500,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 300,000 (13.6%) 220,000 (10.0%) 280,000 (12.7%) 680,000 (30.9%) 120,000 (5.5%) 620,000 (28.2%) 2,200,000
MAX No Mngd. Care, Med. Service Received 2,860,000 (36.3%) 1,820,000 (23.1%) 820,000 (10.4%) 880,000 (11.2%) 160,000 (2.0%) 1,340,000 (17.0%) 7,880,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,320,000 (33.7%) 320,000 (8.2%) 320,000 (8.2%) 1,100,000 (28.1%) 80,000 (2.0%) 780,000 (19.9%) 3,920,000
MAX Some Mngd. Care, Med. Service Noted 7,400,000 (52.1%) 1,880,000 (13.2%) 880,000 (6.2%) 1,840,000 (13.0%) 160,000 (1.1%) 2,020,000 (14.2%) 14,200,000
No MAX Data Available 60,000 (30.0%) 20,000 (10.0%) 0 (0.0%) 60,000 (30.0%) 0 (0.0%) 60,000 (30.0%) 200,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 9,920,000 (50.2%) 3,440,000 (17.4%) 1,680,000 (8.5%) 2,040,000 (10.3%) 300,000 (1.5%) 2,340,000 (11.8%) 19,750,000
Began Receiving Q2 Prev. Year 540,000 (39.1%) 200,000 (14.5%) 120,000 (8.7%) 220,000 (15.9%) 40,000 (2.9%) 260,000 (18.8%) 1,380,000
Began Receiving Q3 Prev. Year 460,000 (35.9%) 180,000 (14.1%) 140,000 (10.9%) 200,000 (15.6%) 40,000 (3.1%) 260,000 (20.3%) 1,280,000
Began Receiving Q4 Prev. Year 400,000 (27.0%) 140,000 (9.5%) 100,000 (6.8%) 380,000 (25.7%) 40,000 (2.7%) 420,000 (28.4%) 1,480,000
Eligible for < 61 Days of Previous Year 120,000 (23.1%) 20,000 (3.8%) 40,000 (7.7%) 140,000 (26.9%) 20,000 (3.8%) 180,000 (34.6%) 520,000
Eligible for 61 to 180 Days of Prev. Year 760,000 (31.9%) 300,000 (12.6%) 200,000 (8.4%) 480,000 (20.2%) 40,000 (1.7%) 620,000 (26.1%) 2,380,000
Eligible for > 180 Days of Prev. Year 10,450,000 (49.9%) 3,640,000 (17.4%) 1,800,000 (8.6%) 2,220,000 (10.6%) 360,000 (1.7%) 2,500,000 (11.9%) 20,950,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 80,000 (7.7%) 40,000 (3.8%) 60,000 (5.8%) 480,000 (46.2%) 20,000 (1.9%) 360,000 (34.6%) 1,040,000
Last Received Q2 Prev. Year 120,000 (10.5%) 80,000 (7.0%) 100,000 (8.8%) 440,000 (38.6%) 20,000 (1.8%) 380,000 (33.3%) 1,140,000
Last Received Q3 Prev. Year 180,000 (15.0%) 80,000 (6.7%) 80,000 (6.7%) 440,000 (36.7%) 20,000 (1.7%) 420,000 (35.0%) 1,200,000
Last Received Q4 Prev. Year 260,000 (22.4%) 120,000 (10.3%) 60,000 (5.2%) 340,000 (29.3%) 20,000 (1.7%) 360,000 (31.0%) 1,160,000
Eligible for < 61 Days of Previous Year 60,000 (7.1%) 20,000 (2.4%) 40,000 (4.8%) 360,000 (42.9%) 20,000 (2.4%) 320,000 (38.1%) 840,000
Eligible for 61 to 180 Days of Prev. Year 140,000 (9.9%) 80,000 (5.6%) 100,000 (7.0%) 600,000 (42.3%) 40,000 (2.8%) 460,000 (32.4%) 1,420,000
Eligible for > 180 Days of Prev. Year 440,000 (19.1%) 180,000 (7.8%) 140,000 (6.1%) 740,000 (32.2%) 40,000 (1.7%) 740,000 (32.2%) 2,300,000
*Due to rounding, total values may not equal column or row sums. 99
1
Phase II, Table 4: Reported Insurance Status of Persons Not Shown Receiving Medicaid in MSIS CY 2000 Expanded Sample, Original Weight
Version=A: Unmatchable CPS Records (Refused or Bad SSN), Receiving No Benefits, All CPS Health Insurance Responses Version Page=1
Selected Characteristics
Persons Report-ing
Medicaid Only
Persons Report-ing
Medicaid and Other
Coverage
Persons Not Report-
ing Medicaid But Other Public Coverage Only
Persons Not Report-
ing Medicaid But Other Private
Coverage Only
Persons Not Report-
ing Medicaid But Other Public
and Private Coverage
Persons Report-ing
as Uninsured Total Total Unweighted Count 2,450 (5.5%) 1,700 (3.8%) 2,550 (5.8%) 24,900 (56.2%) 3,250 (7.3%) 9,450 (21.3%) 44,300
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 132
2
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 133
3
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
Virginia 701,000 649,000 604,000 602,000 576,000 536,000 480,000 400,000 320,000
Washington 964,000 964,000 940,000 939,000 938,000 889,000 660,000 580,000 420,000
West Virginia 324,000 324,000 314,000 313,000 313,000 292,000 260,000 240,000 160,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 134
4
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 135
5
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
State=California
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 8,500,000 8,460,000 5,710,000 5,700,000 5,630,000 5,400,000 4,780,000 4,220,000 3,180,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 136
6
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
State=Florida
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,320,000 2,290,000 2,090,000 2,080,000 2,080,000 2,020,000 1,740,000 1,380,000 1,000,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 137
7
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
State=New York
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 3,590,000 3,590,000 3,530,000 3,510,000 3,460,000 2,870,000 2,860,000 2,460,000 1,680,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 138
8
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Original Weight
State=Texas
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,760,000 2,750,000 2,540,000 2,530,000 2,530,000 2,410,000 2,140,000 1,760,000 1,260,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 139
1
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Re-Weighted
State=U.S. Total
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 48,550,000 46,700,000 42,200,000 42,050,000 40,450,000 38,200,000 31,700,000 27,750,000 20,550,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 140
2
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Re-Weighted
State=California
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 8,500,000 8,460,000 5,710,000 5,700,000 5,630,000 5,400,000 4,180,000 3,680,000 2,780,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 141
3
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Re-Weighted
State=Florida
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,320,000 2,290,000 2,090,000 2,080,000 2,080,000 2,020,000 1,800,000 1,420,000 1,020,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 142
4
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Re-Weighted
State=New York
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 3,590,000 3,590,000 3,530,000 3,510,000 3,460,000 2,870,000 2,580,000 2,200,000 1,520,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 143
5
Phase II, Table 2: Medicaid Population Size, Comparison of MSIS Counts to CPS Estimates CY 2001 Full Sample, Re-Weighted
State=Texas
Selected Characteristics
MSIS Total A
MSIS Total B
MSIS Total C
MSIS Total D
MSIS Total E
MSIS Total F
CPS Total A
CPS Total B
CPS Total C
Total 2,760,000 2,750,000 2,540,000 2,530,000 2,530,000 2,410,000 2,220,000 1,840,000 1,340,000
1. All CPS Estimates are of weighted totals. 2. MSIS Total A is total enrolled in MSIS. 3. MSIS Total B is total MSIS without SCHIP. 4. MSIS Total C is total enrolled for full benefits. 5. MSIS Total D is total enrolled for full benefits, excluding residents of institutional-GQs. 6. MSIS Total E is total enrolled for full benefits, excluding residents of institutional-GQs and duplicative client accounts. 7. MSIS Total F is Total E excluding un-indentified clients: those having records with un-validated SSNs. 8. CPS Total A uses MCAID. 9. CPS Total B uses Augmented-CAID. 10. CPS Total C uses explicitly reported in Medicaid: Augmented-CAID (excluding imputed or edited responses).
Due to rounding, total values may not equal column or row sums. 144
1
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Original Weight
Version=A: CPS-MSIS Matched Records, Receiving Full Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 8,580,000 (39.2%) 3,960,000 (18.1%) 1,760,000 (8.0%) 3,860,000 (17.6%) 440,000 (2.0%) 3,300,000 (15.1%) 21,900,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 380,000 (21.8%) 220,000 (12.6%) 140,000 (8.0%) 520,000 (29.9%) 40,000 (2.3%) 440,000 (25.3%) 1,740,000
MAX No Mngd. Care, Med. Service Received 3,020,000 (40.5%) 1,680,000 (22.5%) 680,000 (9.1%) 980,000 (13.1%) 160,000 (2.1%) 940,000 (12.6%) 7,460,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,380,000 (35.4%) 460,000 (11.8%) 260,000 (6.7%) 1,020,000 (26.2%) 60,000 (1.5%) 740,000 (19.0%) 3,900,000
MAX Some Mngd. Care, Med. Service Noted 7,220,000 (49.3%) 2,100,000 (14.3%) 900,000 (6.1%) 2,100,000 (14.3%) 200,000 (1.4%) 2,140,000 (14.6%) 14,650,000
No MAX Data Available 100,000 (55.6%) 20,000 (11.1%) 20,000 (11.1%) 20,000 (11.1%) 0 (0.0%) 20,000 (11.1%) 180,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 9,440,000 (49.9%) 3,440,000 (18.2%) 1,320,000 (7.0%) 2,220,000 (11.7%) 280,000 (1.5%) 2,180,000 (11.5%) 18,900,000
Began Receiving Q2 Prev. Year 640,000 (42.1%) 240,000 (15.8%) 120,000 (7.9%) 220,000 (14.5%) 40,000 (2.6%) 240,000 (15.8%) 1,520,000
Began Receiving Q3 Prev. Year 520,000 (36.6%) 220,000 (15.5%) 100,000 (7.0%) 260,000 (18.3%) 40,000 (2.8%) 280,000 (19.7%) 1,420,000
Began Receiving Q4 Prev. Year 480,000 (32.9%) 140,000 (9.6%) 140,000 (9.6%) 360,000 (24.7%) 20,000 (1.4%) 320,000 (21.9%) 1,460,000
Eligible for < 61 Days of Previous Year 180,000 (27.3%) 80,000 (12.1%) 60,000 (9.1%) 180,000 (27.3%) 0 (0.0%) 160,000 (24.2%) 660,000
Eligible for 61 to 180 Days of Prev. Year 760,000 (33.9%) 280,000 (12.5%) 200,000 (8.9%) 460,000 (20.5%) 40,000 (1.8%) 480,000 (21.4%) 2,240,000
Eligible for > 180 Days of Prev. Year 10,100,000 (49.5%) 3,700,000 (18.1%) 1,440,000 (7.1%) 2,420,000 (11.9%) 320,000 (1.6%) 2,400,000 (11.8%) 20,400,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 100,000 (11.4%) 60,000 (6.8%) 60,000 (6.8%) 400,000 (45.5%) 20,000 (2.3%) 240,000 (27.3%) 880,000
Last Received Q2 Prev. Year 140,000 (13.7%) 60,000 (5.9%) 60,000 (5.9%) 400,000 (39.2%) 20,000 (2.0%) 340,000 (33.3%) 1,020,000
Last Received Q3 Prev. Year 540,000 (32.9%) 160,000 (9.8%) 120,000 (7.3%) 400,000 (24.4%) 20,000 (1.2%) 400,000 (24.4%) 1,640,000
Last Received Q4 Prev. Year 260,000 (22.8%) 140,000 (12.3%) 60,000 (5.3%) 380,000 (33.3%) 20,000 (1.8%) 280,000 (24.6%) 1,140,000
Eligible for < 61 Days of Previous Year 80,000 (12.9%) 40,000 (6.5%) 40,000 (6.5%) 280,000 (45.2%) 20,000 (3.2%) 180,000 (29.0%) 620,000
Eligible for 61 to 180 Days of Prev. Year 220,000 (15.7%) 100,000 (7.1%) 80,000 (5.7%) 520,000 (37.1%) 40,000 (2.9%) 440,000 (31.4%) 1,400,000
Eligible for > 180 Days of Prev. Year 740,000 (28.0%) 300,000 (11.4%) 180,000 (6.8%) 760,000 (28.8%) 40,000 (1.5%) 620,000 (23.5%) 2,640,000
*Due to rounding, total values may not equal column or row sums. 147
4
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Original Weight
Version=B: CPS-MSIS Matched Records, Receiving Full Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 7,700,000 (41.8%) 3,040,000 (16.5%) 1,560,000 (8.5%) 3,000,000 (16.3%) 360,000 (2.0%) 2,760,000 (15.0%) 18,400,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 300,000 (21.1%) 140,000 (9.9%) 120,000 (8.5%) 440,000 (31.0%) 40,000 (2.8%) 380,000 (26.8%) 1,420,000
MAX No Mngd. Care, Med. Service Received 2,720,000 (43.3%) 1,340,000 (21.3%) 580,000 (9.2%) 700,000 (11.1%) 120,000 (1.9%) 800,000 (12.7%) 6,280,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,160,000 (36.5%) 260,000 (8.2%) 240,000 (7.5%) 820,000 (25.8%) 40,000 (1.3%) 620,000 (19.5%) 3,180,000
MAX Some Mngd. Care, Med. Service Noted 6,540,000 (52.7%) 1,600,000 (12.9%) 820,000 (6.6%) 1,600,000 (12.9%) 180,000 (1.5%) 1,680,000 (13.5%) 12,400,000
No MAX Data Available 100,000 (62.5%) 20,000 (12.5%) 20,000 (12.5%) 0 (0.0%) 0 (0.0%) 20,000 (12.5%) 160,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 8,500,000 (54.0%) 2,560,000 (16.3%) 1,200,000 (7.6%) 1,600,000 (10.2%) 200,000 (1.3%) 1,660,000 (10.5%) 15,750,000
Began Receiving Q2 Prev. Year 580,000 (44.6%) 200,000 (15.4%) 100,000 (7.7%) 180,000 (13.8%) 40,000 (3.1%) 200,000 (15.4%) 1,300,000
Began Receiving Q3 Prev. Year 460,000 (38.3%) 180,000 (15.0%) 100,000 (8.3%) 220,000 (18.3%) 20,000 (1.7%) 240,000 (20.0%) 1,200,000
Began Receiving Q4 Prev. Year 400,000 (33.3%) 100,000 (8.3%) 120,000 (10.0%) 280,000 (23.3%) 20,000 (1.7%) 280,000 (23.3%) 1,200,000
Eligible for < 61 Days of Previous Year 160,000 (29.6%) 40,000 (7.4%) 40,000 (7.4%) 140,000 (25.9%) 0 (0.0%) 160,000 (29.6%) 540,000
Eligible for 61 to 180 Days of Prev. Year 660,000 (35.1%) 220,000 (11.7%) 180,000 (9.6%) 380,000 (20.2%) 40,000 (2.1%) 400,000 (21.3%) 1,880,000
Eligible for > 180 Days of Prev. Year 9,100,000 (53.4%) 2,800,000 (16.4%) 1,300,000 (7.6%) 1,760,000 (10.3%) 260,000 (1.5%) 1,820,000 (10.7%) 17,050,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 60,000 (8.1%) 60,000 (8.1%) 60,000 (8.1%) 340,000 (45.9%) 20,000 (2.7%) 200,000 (27.0%) 740,000
Last Received Q2 Prev. Year 120,000 (13.6%) 40,000 (4.5%) 60,000 (6.8%) 340,000 (38.6%) 20,000 (2.3%) 300,000 (34.1%) 880,000
Last Received Q3 Prev. Year 460,000 (32.9%) 120,000 (8.6%) 100,000 (7.1%) 320,000 (22.9%) 20,000 (1.4%) 360,000 (25.7%) 1,400,000
Last Received Q4 Prev. Year 220,000 (22.4%) 100,000 (10.2%) 60,000 (6.1%) 320,000 (32.7%) 20,000 (2.0%) 240,000 (24.5%) 980,000
Eligible for < 61 Days of Previous Year 60,000 (11.5%) 20,000 (3.8%) 40,000 (7.7%) 260,000 (50.0%) 20,000 (3.8%) 140,000 (26.9%) 520,000
Eligible for 61 to 180 Days of Prev. Year 180,000 (14.8%) 80,000 (6.6%) 80,000 (6.6%) 460,000 (37.7%) 40,000 (3.3%) 400,000 (32.8%) 1,220,000
Eligible for > 180 Days of Prev. Year 640,000 (28.6%) 220,000 (9.8%) 160,000 (7.1%) 620,000 (27.7%) 40,000 (1.8%) 540,000 (24.1%) 2,240,000
*Due to rounding, total values may not equal column or row sums. 156
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Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Original Weight
Version=E: CPS-MSIS Matched Records, Receiving Any Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 8,900,000 (37.6%) 4,240,000 (17.9%) 2,160,000 (9.1%) 4,180,000 (17.7%) 600,000 (2.5%) 3,580,000 (15.1%) 23,650,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 420,000 (18.3%) 280,000 (12.2%) 340,000 (14.8%) 620,000 (27.0%) 140,000 (6.1%) 520,000 (22.6%) 2,300,000
MAX No Mngd. Care, Med. Service Received 3,140,000 (38.9%) 1,820,000 (22.5%) 820,000 (10.1%) 1,080,000 (13.4%) 180,000 (2.2%) 1,040,000 (12.9%) 8,080,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,420,000 (34.5%) 480,000 (11.7%) 300,000 (7.3%) 1,060,000 (25.7%) 80,000 (1.9%) 780,000 (18.9%) 4,120,000
MAX Some Mngd. Care, Med. Service Noted 7,380,000 (49.0%) 2,160,000 (14.4%) 940,000 (6.2%) 2,180,000 (14.5%) 220,000 (1.5%) 2,180,000 (14.5%) 15,050,000
No MAX Data Available 100,000 (50.0%) 20,000 (10.0%) 20,000 (10.0%) 20,000 (10.0%) 0 (0.0%) 20,000 (10.0%) 200,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 9,920,000 (48.2%) 3,720,000 (18.1%) 1,700,000 (8.3%) 2,460,000 (11.9%) 400,000 (1.9%) 2,400,000 (11.7%) 20,600,000
Began Receiving Q2 Prev. Year 640,000 (40.5%) 240,000 (15.2%) 140,000 (8.9%) 240,000 (15.2%) 60,000 (3.8%) 260,000 (16.5%) 1,580,000
Began Receiving Q3 Prev. Year 520,000 (35.1%) 240,000 (16.2%) 120,000 (8.1%) 280,000 (18.9%) 40,000 (2.7%) 300,000 (20.3%) 1,480,000
Began Receiving Q4 Prev. Year 460,000 (30.3%) 160,000 (10.5%) 140,000 (9.2%) 380,000 (25.0%) 20,000 (1.3%) 340,000 (22.4%) 1,520,000
Eligible for < 61 Days of Previous Year 160,000 (25.0%) 60,000 (9.4%) 60,000 (9.4%) 180,000 (28.1%) 0 (0.0%) 180,000 (28.1%) 640,000
Eligible for 61 to 180 Days of Prev. Year 760,000 (32.8%) 300,000 (12.9%) 220,000 (9.5%) 480,000 (20.7%) 40,000 (1.7%) 520,000 (22.4%) 2,320,000
Eligible for > 180 Days of Prev. Year 10,600,000 (47.7%) 4,000,000 (18.0%) 1,820,000 (8.2%) 2,700,000 (12.2%) 460,000 (2.1%) 2,640,000 (11.9%) 22,200,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 100,000 (11.9%) 60,000 (7.1%) 40,000 (4.8%) 400,000 (47.6%) 20,000 (2.4%) 220,000 (26.2%) 840,000
Last Received Q2 Prev. Year 100,000 (10.2%) 60,000 (6.1%) 60,000 (6.1%) 400,000 (40.8%) 40,000 (4.1%) 320,000 (32.7%) 980,000
Last Received Q3 Prev. Year 500,000 (30.1%) 160,000 (9.6%) 140,000 (8.4%) 440,000 (26.5%) 20,000 (1.2%) 400,000 (24.1%) 1,660,000
Last Received Q4 Prev. Year 220,000 (19.6%) 120,000 (10.7%) 80,000 (7.1%) 380,000 (33.9%) 40,000 (3.6%) 280,000 (25.0%) 1,120,000
Eligible for < 61 Days of Previous Year 60,000 (9.4%) 20,000 (3.1%) 40,000 (6.3%) 300,000 (46.9%) 20,000 (3.1%) 180,000 (28.1%) 640,000
Eligible for 61 to 180 Days of Prev. Year 140,000 (10.8%) 80,000 (6.2%) 80,000 (6.2%) 520,000 (40.0%) 40,000 (3.1%) 420,000 (32.3%) 1,300,000
Eligible for > 180 Days of Prev. Year 700,000 (26.3%) 280,000 (10.5%) 200,000 (7.5%) 780,000 (29.3%) 40,000 (1.5%) 640,000 (24.1%) 2,660,000
*Due to rounding, total values may not equal column or row sums. 159
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Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Original Weight
Version=F: CPS-MSIS Matched Records, Receiving Any Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 7,980,000 (40.0%) 3,280,000 (16.4%) 1,940,000 (9.7%) 3,260,000 (16.3%) 500,000 (2.5%) 3,000,000 (15.0%) 19,950,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 320,000 (16.8%) 180,000 (9.5%) 300,000 (15.8%) 540,000 (28.4%) 120,000 (6.3%) 440,000 (23.2%) 1,900,000
MAX No Mngd. Care, Med. Service Received 2,820,000 (41.3%) 1,480,000 (21.7%) 720,000 (10.6%) 780,000 (11.4%) 140,000 (2.1%) 880,000 (12.9%) 6,820,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,200,000 (35.7%) 300,000 (8.9%) 280,000 (8.3%) 860,000 (25.6%) 60,000 (1.8%) 660,000 (19.6%) 3,360,000
MAX Some Mngd. Care, Med. Service Noted 6,680,000 (52.4%) 1,660,000 (13.0%) 860,000 (6.7%) 1,660,000 (13.0%) 180,000 (1.4%) 1,720,000 (13.5%) 12,750,000
No MAX Data Available 100,000 (55.6%) 20,000 (11.1%) 20,000 (11.1%) 20,000 (11.1%) 0 (0.0%) 20,000 (11.1%) 180,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 8,940,000 (51.8%) 2,820,000 (16.3%) 1,540,000 (8.9%) 1,800,000 (10.4%) 320,000 (1.9%) 1,840,000 (10.7%) 17,250,000
Began Receiving Q2 Prev. Year 580,000 (43.3%) 200,000 (14.9%) 120,000 (9.0%) 180,000 (13.4%) 60,000 (4.5%) 220,000 (16.4%) 1,340,000
Began Receiving Q3 Prev. Year 460,000 (36.5%) 200,000 (15.9%) 100,000 (7.9%) 220,000 (17.5%) 40,000 (3.2%) 260,000 (20.6%) 1,260,000
Began Receiving Q4 Prev. Year 400,000 (31.7%) 100,000 (7.9%) 140,000 (11.1%) 300,000 (23.8%) 20,000 (1.6%) 300,000 (23.8%) 1,260,000
Eligible for < 61 Days of Previous Year 140,000 (25.9%) 20,000 (3.7%) 60,000 (11.1%) 140,000 (25.9%) 0 (0.0%) 160,000 (29.6%) 540,000
Eligible for 61 to 180 Days of Prev. Year 660,000 (34.0%) 240,000 (12.4%) 200,000 (10.3%) 400,000 (20.6%) 40,000 (2.1%) 440,000 (22.7%) 1,940,000
Eligible for > 180 Days of Prev. Year 9,560,000 (51.4%) 3,060,000 (16.5%) 1,660,000 (8.9%) 1,960,000 (10.5%) 380,000 (2.0%) 2,020,000 (10.9%) 18,600,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 60,000 (8.6%) 40,000 (5.7%) 40,000 (5.7%) 360,000 (51.4%) 20,000 (2.9%) 200,000 (28.6%) 700,000
Last Received Q2 Prev. Year 80,000 (9.5%) 40,000 (4.8%) 60,000 (7.1%) 340,000 (40.5%) 20,000 (2.4%) 300,000 (35.7%) 840,000
Last Received Q3 Prev. Year 440,000 (31.4%) 120,000 (8.6%) 120,000 (8.6%) 360,000 (25.7%) 20,000 (1.4%) 360,000 (25.7%) 1,400,000
Last Received Q4 Prev. Year 180,000 (18.8%) 100,000 (10.4%) 60,000 (6.3%) 320,000 (33.3%) 20,000 (2.1%) 260,000 (27.1%) 960,000
Eligible for < 61 Days of Previous Year 40,000 (7.4%) 20,000 (3.7%) 40,000 (7.4%) 260,000 (48.1%) 20,000 (3.7%) 160,000 (29.6%) 540,000
Eligible for 61 to 180 Days of Prev. Year 100,000 (8.9%) 60,000 (5.4%) 60,000 (5.4%) 440,000 (39.3%) 40,000 (3.6%) 400,000 (35.7%) 1,120,000
Eligible for > 180 Days of Prev. Year 580,000 (25.9%) 220,000 (9.8%) 180,000 (8.0%) 660,000 (29.5%) 40,000 (1.8%) 560,000 (25.0%) 2,240,000
*Due to rounding, total values may not equal column or row sums. 168
1
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Re-Weighted
Version=A: CPS-MSIS Matched Records, Receiving Full Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 10,450,000 (36.9%) 5,160,000 (18.2%) 2,400,000 (8.5%) 4,860,000 (17.2%) 580,000 (2.0%) 4,820,000 (17.0%) 28,300,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 480,000 (20.9%) 280,000 (12.2%) 200,000 (8.7%) 660,000 (28.7%) 60,000 (2.6%) 640,000 (27.8%) 2,300,000
MAX No Mngd. Care, Med. Service Received 3,720,000 (37.8%) 2,240,000 (22.8%) 980,000 (10.0%) 1,280,000 (13.0%) 240,000 (2.4%) 1,400,000 (14.2%) 9,840,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,700,000 (34.0%) 560,000 (11.2%) 340,000 (6.8%) 1,260,000 (25.2%) 60,000 (1.2%) 1,080,000 (21.6%) 5,000,000
MAX Some Mngd. Care, Med. Service Noted 8,720,000 (46.9%) 2,680,000 (14.4%) 1,160,000 (6.2%) 2,660,000 (14.3%) 260,000 (1.4%) 3,120,000 (16.8%) 18,600,000
No MAX Data Available 120,000 (50.0%) 20,000 (8.3%) 20,000 (8.3%) 20,000 (8.3%) 0 (0.0%) 40,000 (16.7%) 240,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 11,500,000 (47.5%) 4,500,000 (18.6%) 1,800,000 (7.4%) 2,820,000 (11.7%) 400,000 (1.7%) 3,200,000 (13.2%) 24,200,000
Began Receiving Q2 Prev. Year 780,000 (39.8%) 300,000 (15.3%) 160,000 (8.2%) 300,000 (15.3%) 60,000 (3.1%) 360,000 (18.4%) 1,960,000
Began Receiving Q3 Prev. Year 620,000 (34.1%) 280,000 (15.4%) 140,000 (7.7%) 340,000 (18.7%) 40,000 (2.2%) 400,000 (22.0%) 1,820,000
Began Receiving Q4 Prev. Year 580,000 (30.5%) 180,000 (9.5%) 180,000 (9.5%) 460,000 (24.2%) 20,000 (1.1%) 460,000 (24.2%) 1,900,000
Eligible for < 61 Days of Previous Year 220,000 (25.6%) 100,000 (11.6%) 60,000 (7.0%) 220,000 (25.6%) 0 (0.0%) 240,000 (27.9%) 860,000
Eligible for 61 to 180 Days of Prev. Year 920,000 (31.7%) 360,000 (12.4%) 260,000 (9.0%) 600,000 (20.7%) 60,000 (2.1%) 700,000 (24.1%) 2,900,000
Eligible for > 180 Days of Prev. Year 12,300,000 (47.0%) 4,820,000 (18.4%) 1,980,000 (7.6%) 3,100,000 (11.9%) 440,000 (1.7%) 3,500,000 (13.4%) 26,150,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 140,000 (12.1%) 80,000 (6.9%) 80,000 (6.9%) 480,000 (41.4%) 20,000 (1.7%) 340,000 (29.3%) 1,160,000
Last Received Q2 Prev. Year 180,000 (13.4%) 60,000 (4.5%) 80,000 (6.0%) 500,000 (37.3%) 20,000 (1.5%) 500,000 (37.3%) 1,340,000
Last Received Q3 Prev. Year 640,000 (29.9%) 220,000 (10.3%) 140,000 (6.5%) 520,000 (24.3%) 20,000 (0.9%) 580,000 (27.1%) 2,140,000
Last Received Q4 Prev. Year 320,000 (21.9%) 160,000 (11.0%) 80,000 (5.5%) 460,000 (31.5%) 40,000 (2.7%) 400,000 (27.4%) 1,460,000
Eligible for < 61 Days of Previous Year 100,000 (11.9%) 40,000 (4.8%) 60,000 (7.1%) 340,000 (40.5%) 20,000 (2.4%) 260,000 (31.0%) 840,000
Eligible for 61 to 180 Days of Prev. Year 260,000 (14.0%) 120,000 (6.5%) 120,000 (6.5%) 660,000 (35.5%) 40,000 (2.2%) 660,000 (35.5%) 1,860,000
Eligible for > 180 Days of Prev. Year 900,000 (26.3%) 360,000 (10.5%) 220,000 (6.4%) 940,000 (27.5%) 40,000 (1.2%) 920,000 (26.9%) 3,420,000
*Due to rounding, total values may not equal column or row sums. 171
4
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Re-Weighted
Version=B: CPS-MSIS Matched Records, Receiving Full Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 9,200,000 (40.1%) 3,840,000 (16.7%) 2,020,000 (8.8%) 3,540,000 (15.4%) 440,000 (1.9%) 3,900,000 (17.0%) 22,950,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 360,000 (19.8%) 180,000 (9.9%) 160,000 (8.8%) 520,000 (28.6%) 40,000 (2.2%) 540,000 (29.7%) 1,820,000
MAX No Mngd. Care, Med. Service Received 3,280,000 (41.1%) 1,740,000 (21.8%) 800,000 (10.0%) 860,000 (10.8%) 140,000 (1.8%) 1,140,000 (14.3%) 7,980,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,380,000 (35.4%) 320,000 (8.2%) 300,000 (7.7%) 980,000 (25.1%) 60,000 (1.5%) 860,000 (22.1%) 3,900,000
MAX Some Mngd. Care, Med. Service Noted 7,780,000 (51.2%) 1,960,000 (12.9%) 1,020,000 (6.7%) 1,880,000 (12.4%) 200,000 (1.3%) 2,340,000 (15.4%) 15,200,000
No MAX Data Available 100,000 (50.0%) 20,000 (10.0%) 20,000 (10.0%) 20,000 (10.0%) 0 (0.0%) 20,000 (10.0%) 200,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 10,150,000 (52.2%) 3,260,000 (16.8%) 1,560,000 (8.0%) 1,880,000 (9.7%) 240,000 (1.2%) 2,340,000 (12.0%) 19,450,000
Began Receiving Q2 Prev. Year 700,000 (43.2%) 240,000 (14.8%) 120,000 (7.4%) 200,000 (12.3%) 60,000 (3.7%) 300,000 (18.5%) 1,620,000
Began Receiving Q3 Prev. Year 540,000 (36.0%) 220,000 (14.7%) 120,000 (8.0%) 260,000 (17.3%) 40,000 (2.7%) 320,000 (21.3%) 1,500,000
Began Receiving Q4 Prev. Year 480,000 (32.0%) 120,000 (8.0%) 160,000 (10.7%) 340,000 (22.7%) 20,000 (1.3%) 400,000 (26.7%) 1,500,000
Eligible for < 61 Days of Previous Year 200,000 (29.4%) 40,000 (5.9%) 60,000 (8.8%) 160,000 (23.5%) 0 (0.0%) 220,000 (32.4%) 680,000
Eligible for 61 to 180 Days of Prev. Year 780,000 (33.3%) 260,000 (11.1%) 220,000 (9.4%) 440,000 (18.8%) 40,000 (1.7%) 580,000 (24.8%) 2,340,000
Eligible for > 180 Days of Prev. Year 10,900,000 (51.9%) 3,540,000 (16.9%) 1,680,000 (8.0%) 2,060,000 (9.8%) 300,000 (1.4%) 2,580,000 (12.3%) 21,000,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 80,000 (8.5%) 60,000 (6.4%) 80,000 (8.5%) 420,000 (44.7%) 20,000 (2.1%) 280,000 (29.8%) 940,000
Last Received Q2 Prev. Year 140,000 (12.5%) 40,000 (3.6%) 60,000 (5.4%) 400,000 (35.7%) 20,000 (1.8%) 440,000 (39.3%) 1,120,000
Last Received Q3 Prev. Year 560,000 (31.8%) 160,000 (9.1%) 140,000 (8.0%) 380,000 (21.6%) 20,000 (1.1%) 500,000 (28.4%) 1,760,000
Last Received Q4 Prev. Year 260,000 (21.3%) 120,000 (9.8%) 80,000 (6.6%) 380,000 (31.1%) 20,000 (1.6%) 340,000 (27.9%) 1,220,000
Eligible for < 61 Days of Previous Year 60,000 (8.8%) 40,000 (5.9%) 40,000 (5.9%) 300,000 (44.1%) 20,000 (2.9%) 200,000 (29.4%) 680,000
Eligible for 61 to 180 Days of Prev. Year 220,000 (13.9%) 80,000 (5.1%) 100,000 (6.3%) 540,000 (34.2%) 40,000 (2.5%) 580,000 (36.7%) 1,580,000
Eligible for > 180 Days of Prev. Year 760,000 (27.3%) 280,000 (10.1%) 200,000 (7.2%) 740,000 (26.6%) 40,000 (1.4%) 760,000 (27.3%) 2,780,000
*Due to rounding, total values may not equal column or row sums. 180
13
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Re-Weighted
Version=E: CPS-MSIS Matched Records, Receiving Any Benefits, All CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 10,850,000 (35.3%) 5,520,000 (18.0%) 2,960,000 (9.6%) 5,300,000 (17.2%) 840,000 (2.7%) 5,260,000 (17.1%) 30,750,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 520,000 (16.7%) 360,000 (11.5%) 480,000 (15.4%) 800,000 (25.6%) 220,000 (7.1%) 760,000 (24.4%) 3,120,000
MAX No Mngd. Care, Med. Service Received 3,860,000 (36.1%) 2,440,000 (22.8%) 1,180,000 (11.0%) 1,400,000 (13.1%) 280,000 (2.6%) 1,560,000 (14.6%) 10,700,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,740,000 (33.0%) 600,000 (11.4%) 380,000 (7.2%) 1,320,000 (25.0%) 100,000 (1.9%) 1,140,000 (21.6%) 5,280,000
MAX Some Mngd. Care, Med. Service Noted 8,900,000 (46.6%) 2,760,000 (14.5%) 1,200,000 (6.3%) 2,760,000 (14.5%) 280,000 (1.5%) 3,200,000 (16.8%) 19,100,000
No MAX Data Available 120,000 (46.2%) 20,000 (7.7%) 20,000 (7.7%) 40,000 (15.4%) 0 (0.0%) 40,000 (15.4%) 260,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 12,050,000 (45.4%) 4,880,000 (18.4%) 2,340,000 (8.8%) 3,160,000 (11.9%) 560,000 (2.1%) 3,540,000 (13.3%) 26,550,000
Began Receiving Q2 Prev. Year 780,000 (38.6%) 300,000 (14.9%) 180,000 (8.9%) 300,000 (14.9%) 80,000 (4.0%) 380,000 (18.8%) 2,020,000
Began Receiving Q3 Prev. Year 620,000 (32.3%) 300,000 (15.6%) 160,000 (8.3%) 340,000 (17.7%) 40,000 (2.1%) 460,000 (24.0%) 1,920,000
Began Receiving Q4 Prev. Year 560,000 (28.6%) 200,000 (10.2%) 180,000 (9.2%) 480,000 (24.5%) 20,000 (1.0%) 500,000 (25.5%) 1,960,000
Eligible for < 61 Days of Previous Year 200,000 (23.3%) 80,000 (9.3%) 80,000 (9.3%) 220,000 (25.6%) 0 (0.0%) 260,000 (30.2%) 860,000
Eligible for 61 to 180 Days of Prev. Year 920,000 (30.7%) 380,000 (12.7%) 280,000 (9.3%) 620,000 (20.7%) 60,000 (2.0%) 740,000 (24.7%) 3,000,000
Eligible for > 180 Days of Prev. Year 12,900,000 (45.1%) 5,220,000 (18.3%) 2,500,000 (8.7%) 3,460,000 (12.1%) 640,000 (2.2%) 3,860,000 (13.5%) 28,600,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 120,000 (10.7%) 60,000 (5.4%) 60,000 (5.4%) 500,000 (44.6%) 40,000 (3.6%) 340,000 (30.4%) 1,120,000
Last Received Q2 Prev. Year 120,000 (9.2%) 60,000 (4.6%) 80,000 (6.2%) 500,000 (38.5%) 40,000 (3.1%) 480,000 (36.9%) 1,300,000
Last Received Q3 Prev. Year 600,000 (27.5%) 200,000 (9.2%) 180,000 (8.3%) 560,000 (25.7%) 40,000 (1.8%) 580,000 (26.6%) 2,180,000
Last Received Q4 Prev. Year 280,000 (19.2%) 160,000 (11.0%) 100,000 (6.8%) 460,000 (31.5%) 40,000 (2.7%) 420,000 (28.8%) 1,460,000
Eligible for < 61 Days of Previous Year 80,000 (9.3%) 40,000 (4.7%) 60,000 (7.0%) 380,000 (44.2%) 40,000 (4.7%) 260,000 (30.2%) 860,000
Eligible for 61 to 180 Days of Prev. Year 180,000 (10.5%) 120,000 (7.0%) 100,000 (5.8%) 660,000 (38.4%) 60,000 (3.5%) 620,000 (36.0%) 1,720,000
Eligible for > 180 Days of Prev. Year 860,000 (24.9%) 360,000 (10.4%) 260,000 (7.5%) 1,000,000 (28.9%) 60,000 (1.7%) 940,000 (27.2%) 3,460,000
*Due to rounding, total values may not equal column or row sums. 183
16
Phase II, Table 3: Reported Insurance Status of Matched Persons Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Re-Weighted
Version=F: CPS-MSIS Matched Records, Receiving Any Benefits, Edited CPS Health Insurance Responses Version Page=1
MAX Section 1931 Qualified: No 9,540,000 (38.2%) 4,160,000 (16.6%) 2,560,000 (10.2%) 3,860,000 (15.4%) 620,000 (2.5%) 4,240,000 (17.0%) 25,000,000
MAX No Mngd. Care, Medical Svc. Not Rcvd. 380,000 (15.3%) 240,000 (9.7%) 420,000 (16.9%) 640,000 (25.8%) 160,000 (6.5%) 640,000 (25.8%) 2,480,000
MAX No Mngd. Care, Med. Service Received 3,400,000 (39.1%) 1,920,000 (22.1%) 980,000 (11.3%) 940,000 (10.8%) 180,000 (2.1%) 1,280,000 (14.7%) 8,700,000
MAX Some Mngd. Care, Med. Svc. Not Noted 1,420,000 (34.3%) 360,000 (8.7%) 360,000 (8.7%) 1,020,000 (24.6%) 80,000 (1.9%) 920,000 (22.2%) 4,140,000
MAX Some Mngd. Care, Med. Service Noted 7,940,000 (50.9%) 2,040,000 (13.1%) 1,060,000 (6.8%) 1,960,000 (12.6%) 220,000 (1.4%) 2,400,000 (15.4%) 15,600,000
No MAX Data Available 100,000 (50.0%) 20,000 (10.0%) 20,000 (10.0%) 20,000 (10.0%) 0 (0.0%) 40,000 (20.0%) 200,000
Received Benefits in Survey Year
Began Rcvng. Q1 Prev. Year or Earlier 10,650,000 (49.8%) 3,580,000 (16.7%) 2,040,000 (9.5%) 2,120,000 (9.9%) 400,000 (1.9%) 2,600,000 (12.1%) 21,400,000
Began Receiving Q2 Prev. Year 700,000 (41.7%) 240,000 (14.3%) 140,000 (8.3%) 220,000 (13.1%) 60,000 (3.6%) 300,000 (17.9%) 1,680,000
Began Receiving Q3 Prev. Year 540,000 (34.6%) 240,000 (15.4%) 140,000 (9.0%) 260,000 (16.7%) 40,000 (2.6%) 360,000 (23.1%) 1,560,000
Began Receiving Q4 Prev. Year 460,000 (29.1%) 120,000 (7.6%) 160,000 (10.1%) 360,000 (22.8%) 20,000 (1.3%) 440,000 (27.8%) 1,580,000
Eligible for < 61 Days of Previous Year 180,000 (26.5%) 40,000 (5.9%) 80,000 (11.8%) 180,000 (26.5%) 0 (0.0%) 220,000 (32.4%) 680,000
Eligible for 61 to 180 Days of Prev. Year 780,000 (32.0%) 280,000 (11.5%) 240,000 (9.8%) 480,000 (19.7%) 40,000 (1.6%) 620,000 (25.4%) 2,440,000
Eligible for > 180 Days of Prev. Year 11,400,000 (49.4%) 3,880,000 (16.8%) 2,180,000 (9.4%) 2,300,000 (10.0%) 460,000 (2.0%) 2,860,000 (12.4%) 23,100,000
Did Not Receive Benefits in Survey Year
Last Received Q1 Prev. Year 60,000 (6.7%) 60,000 (6.7%) 40,000 (4.4%) 420,000 (46.7%) 20,000 (2.2%) 280,000 (31.1%) 900,000
Last Received Q2 Prev. Year 80,000 (7.5%) 40,000 (3.8%) 80,000 (7.5%) 400,000 (37.7%) 40,000 (3.8%) 420,000 (39.6%) 1,060,000
Last Received Q3 Prev. Year 520,000 (29.2%) 140,000 (7.9%) 140,000 (7.9%) 440,000 (24.7%) 40,000 (2.2%) 500,000 (28.1%) 1,780,000
Last Received Q4 Prev. Year 220,000 (18.3%) 120,000 (10.0%) 80,000 (6.7%) 380,000 (31.7%) 40,000 (3.3%) 360,000 (30.0%) 1,200,000
Eligible for < 61 Days of Previous Year 60,000 (8.8%) 20,000 (2.9%) 40,000 (5.9%) 320,000 (47.1%) 20,000 (2.9%) 220,000 (32.4%) 680,000
Eligible for 61 to 180 Days of Prev. Year 120,000 (8.3%) 80,000 (5.6%) 80,000 (5.6%) 540,000 (37.5%) 60,000 (4.2%) 560,000 (38.9%) 1,440,000
Eligible for > 180 Days of Prev. Year 700,000 (24.8%) 260,000 (9.2%) 220,000 (7.8%) 780,000 (27.7%) 60,000 (2.1%) 800,000 (28.4%) 2,820,000
*Due to rounding, total values may not equal column or row sums. 192
1
Phase II, Table 4: Reported Insurance Status of Persons Not Shown Receiving Medicaid in MSIS CY 2001 Full Sample, Original Weight
Version=A: Unmatchable CPS Records (Refused or Bad SSN), Receiving No Benefits, All CPS Health Insurance Responses Version Page=1
Selected Characteristics
Persons Report-ing
Medicaid Only
Persons Report-ing
Medicaid and Other
Coverage
Persons Not Report-
ing Medicaid But Other Public Coverage Only
Persons Not Report-
ing Medicaid But Other Private
Coverage Only
Persons Not Report-
ing Medicaid But Other Public
and Private Coverage
Persons Report-ing
as Uninsured Total Total Unweighted Count 2,550 (5.7%) 1,550 (3.5%) 2,650 (5.9%) 24,900 (55.8%) 3,500 (7.8%) 9,450 (21.2%) 44,600
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