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The NAPHSIS/NCHS Collaboration Past Successes and Future Challenges Salt Lake City, UT June 3 rd – 7 th, 2007 Estimation of US Life Tables for Minority.

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Presentation on theme: "The NAPHSIS/NCHS Collaboration Past Successes and Future Challenges Salt Lake City, UT June 3 rd – 7 th, 2007 Estimation of US Life Tables for Minority."— Presentation transcript:

1 The NAPHSIS/NCHS Collaboration Past Successes and Future Challenges Salt Lake City, UT June 3 rd – 7 th, 2007 Estimation of US Life Tables for Minority Populations: Issues of Data Quality and Availability Elizabeth Arias, Ph.D. Mortality Statistics Branch Division of Vital Statistics National Center for Health Statistics

2 Will it be possible to estimate life tables for groups other than the White and Black populations? Data Limitations and Availability Vital Statistics and Medicare Data US Life Table Methodology Example: Comparison of White and Hispanic US Life Tables for Decennial Period

3 Data Limitations and Availability Race/Ethnic Misclassification on Death Certificate Race/Ethnic Classification on Centers for Medicare and Medicaid Services (CMS) Medicare Data

4 Race/Ethnic Misclassification on Death Certificates Results based on study The Validity of Race and Hispanic Origin Reporting on Death Certificates in the United States, by Arias, et al. (2007) Study used the National Longitudinal Mortality Study (NLMS) – linkage of Current Population Surveys (1973, ) with NCHS Mortality Data (Mortality follow-up ) For Sample of Decedents identified in the NLMS, results show that reporting on the death certificate is excellent for White and Black populations; less than optimal for API and Hispanic populations; and, poor for AIAN population. There is some improvement between 1980s and 1990s for most of these groups

5 Ratio of CPS (self) to Death Certificate Report for the Sample of NLMS Decedents White1.00 Black AIAN API Hispanic

6 Application of Validity Study to the Estimation of Life Tables Evaluation of misclassification was carried out by age, sex, region, rural/urban residence, and co-ethnic concentration These results can be used to adjust observed death rates These adjusted death rates can then be used to estimate life tables Ideally, this would be all that is needed……But,

7 The Role of CMS Medicare Data in the Production of US Life Tables NCHS has traditionally used Medicare data to estimate mortality at the oldest ages for its Decennial Life Tables (Annual Life Tables since 1997) It is believed that Medicare coverage is better because age- reporting is verified with date of birth, whereas the denominators of Vital Statistics rates come from Census estimates, which are not verified for age reporting The US Decennial Life Table Method blends Vital and Medicare rates to estimate mortality for ages 65 – 100 q(x) for ages are blended with progressive weight given to Medicare Data q(x) for ages are derived exclusively from Medicare Data

8 CMS Medicare Race/Ethnic Classification CMS Medicare Data derives its Race and Ethnic information from the Social Security Administration Race and ethnic data is collected by SSA when individuals complete form SS-5 for SS Card. Between 1936 and 1980 Race categories included in the SS-5 application were limited to: White, Negro or Other As per OMB Directive No. 15 SSA revised the SS-5 (1980) by expanding the options to 5 categories, combining Race and Hispanic Origin : White (Non-Hispanic) Black (Non-Hispanic) Asian or Pacific Islander American Indian or Alaskan Native Hispanic

9 CMS Medicare Race/Ethnic Classification The result is that CMS Race/Ethnic Categories are a combination of pre-1980 and post-1980 SSA Race/Ethnic Categories: 0=Unknown 1=White (Non-Hispanic) 2=Black (Non-Hispanic) 3=Other 4=Asian, Asian American or Pacific Islander 5=Hispanic 6=American Indian or Alaskan Native

10 Use of CMS Medicare for Groups Other than White or Black How do we disentangle AIANs, APIs, and Hispanics from the combination of pre-1980 and post-1980 categories? Experiment: Use NLMS – CMS linked Data. NLMS was recently linked to CMS Medicare files Compare CPS and CMS-Medicare Classification CPS has provided respondents with full- range of race/ethnicity since 1977

11 Sensitivity: Percent of NLMS Respondents Correctly Identified by CMS – Medicare ( ) HispanicNHWhiteNHBlackNHAIANNHAPI UK NHWhite NHBlack Other API Hispanic AIAN Total100.0

12 Predictive Value Positive: Percent of Respondents Identified by CMS who Self-Identified in the same group in NLMS HispanicNHWhiteNHBlackNHAIANNHAPITotal UK NHWhite NHBlack Other API Hispanic AIAN

13 Effects on Estimation of Life Tables for these Populations NLMS-CMS link suggests the majority of Hispanics, AIANs, and APIs are not easily identifiable in CMS Medicare Data. Does it Matter? Can we do without Medicare Data? Exploration Hispanic Mortality Compared to White Mortality Following 3 Graphs compare Vital q(x) between Hispanic (observed and adjusted for DC under- report) and White populations

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17 What do Mortality Patterns Say? Even after Adjustment for DC misclassification, Hispanic Mortality remains lower. Lower Mortality for Hispanics is concentrated in the older ages, except for Hispanic Females who show advantage throughout full age range. Next, Closer look at Mortality at ages 65 and above

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21 Effects of Using Medicare Data on Life Expectancy Previous 3 graphs show that for the white population CMS Medicare shows higher mortality at ages than Vital Statistics What impact does including CMS Medicare Data have on Life Expectancy Estimates? Experiment: Quantify the Effect of Excluding Medicare Data and Closing the Life Table at age 85 for the White Population:

22 Comparison of Life Expectancy - Blending Vital and Medicare Data for Ages vs. Vital Statistics Closed at Age 85 – White Population Decennial MethodClose at Age 85Diff Total White Population Birth White Male Birth White Female Birth

23 Comparison of White and Hispanic Life Expectancy Using Estimates based Solely on Vital Statistics, Closing Table at Age Decennial Period Total HispanicTotal WhiteDiff Birth Hispanic MaleWhite Male Birth Hispanic FemaleWhite Female Birth

24 How Do Vital Statistics Estimates Compare to NLMS Estimates of Hispanic Life Expectancy? Vital StatisticsNLMS Total Hispanic Diff Birth Hispanic Male Birth Hispanic Female Birth

25 Summary and Future Research and Exploration Data Quality and Limitations Pose Challenges to the Production of Life Tables for Minority Populations. Are they insurmountable? Perhaps, Perhaps Not On the plus side: We have been able to identify and quantify Race/Ethnic misclassification on DC and use this information to correct the resulting under- count of deaths for affected groups

26 Summary and Future Research and Exploration On the negative side: we may not be able to use Medicare data for a very long time, if ever for minority populations We may need to accept that if we want life tables for Hispanics, APIs, and AIANs we will need to rely solely on Vital Statistics Can we accept this alternative? For example, can we accept that Hispanic life expectancy is higher than that of NHWhites? Previous studies using the NLMS, NHIS-NDI all show that Hispanics indeed have lower mortality than NHWhites. One study attributes the advantage to the Salmon Bias Effect, but finds that this Effect applies only to Foreign Born Mexicans and Central/South Americans (Palloni and Arias, 2004) Could the large gap in mortality at the oldest ages we observed be due to Salmon Bias?

27 Next Steps Explore upcoming NLMS – CMS Medicare linkage for possibility of re-classification of CMS categories for use in the Decennial Life Tables. Repeat comparative exercises for AIANs and APIs Explore other statistical modeling techniques for estimates of old-age mortality for these populations.

28 Contact Information Elizabeth Arias MSB/DVS/NCHS


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