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Using NAPIIA to Improve the Accuracy of Asian Race Code in Registry Data

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To demonstrate how the NAPIIA can improve the coding accuracy on Asian races ... Non-Asian race with birthplace in Asian country: 58 (3.4%), white 55 and black 3 ... – PowerPoint PPT presentation

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Title: Using NAPIIA to Improve the Accuracy of Asian Race Code in Registry Data


1
Using NAPIIA to Improve the Accuracy of Asian
Race Code in Registry Data
Mei-Chin Hsieh, MSPH, CTR Lisa A. Pareti, BS,
RHIT, CTR Vivien W. Chen, PhD
NAACCR Conference, Denver, June 2008
2
Background
  • Overall, Asians have lower risk of developing
    cancer than non-Hispanic whites and blacks
  • For certain types of cancer, such as liver and
    stomach, Asians have higher incidence rates than
    other races
  • For a registry with small numbers of Asians, even
    a few miscoding on these minority races could
    potentially bias the estimation of incidence
    rates
  • To ensure Asian races are coded correctly, the
    Louisiana Tumor Registry implements NAPIIA into
    its routine data quality procedure

3
Purpose
  • To demonstrate how the NAPIIA can improve the
    coding accuracy on Asian races
  • To find the misclassification on Asian groups

4
Asian Population in Louisiana
From Census 2000 54,022 (1.208)
5
Methods and Approach
  • Data source Louisiana Tumor Registry
  • Cases diagnosed in year 1995 to 2005 with race1
    (NAACCR item 160) coded to any Asians, other
    race, unknown race, or non-Asian race with
    birthplace in Asian country were selected
  • Converted race1 to 96 (Asian, NOS) and applied
    NAPIIA on records

6
Methods and Approach
  • New Asian codes assigned by NAPIIA were compared
    with original race1 and manually reviewed when
    the assigned Asian codes were different from the
    original race1 codes
  • Research sources utilized for the review
    Abstract Text, Accurint Voter Registration,
    Online Death Certificate, Online Medical Records,
    and contact hospitals as last resort

7
Results
  • Out of 221,732 cases diagnosed between years 1995
    and 2005, 1,711 (0.77) eligible cases were run
    through the NAPIIA
  • Non-Asian race with birthplace in Asian country
    58 (3.4), white 55 and black 3
  • Specific Asian codes 837 (48.9)
  • Asian NOS 238 (13.9)
  • Unknown race 578 (33.8)

8
Results
  • 21.8 (374) of cases were identified with race
    coding differing between original race1 and
    NAPIIA
  • Comparisons
  • Original race vs. NAPIIA
  • NAPIIA vs. reviewed race
  • Original race vs. reviewed race

9
Results Comparing Original Race with NAPIIA
  • 767 (44.8) cases had original race unchanged
  • 570 (33.3) cases had same Asian race codes
  • 374 (21.9) cases (highlighted in yellow and
    blue) had inconsistent race code between original
    race and NAPIIA, which required manually reviewed

10
Results Comparing Original Race with NAPIIA
11
Results Distribution of 374 Cases with
Inconsistent Race Codes
12
Results Comparing Reviewed Race with NAPIIA
  • After manually reviewing, of the 374
    inconsistent race code 254 (67.9) were
    identified with same race code as assigned by
    NAPIIA
  • Of the 89 Filipino codes assigned by NAPIIA, 48
    (53.9) cases were white (mainly Hispanic) after
    review

13
Results Comparing Reviewed Race with NAPIIA
14
Results Comparing Original Race with Reviewed
Race
  • Out of 374, only 34 (9.1) cases were initially
    coded correctly
  • 46.3 (19 out of 41) of Asian Indian/Pakistani
    were recoded to Vietnamese after review

15
Results Final Race Categories After Review
  • White out of 52, 37 were actually Asian
  • Black all remained as black (due to incorrect
    birthplace)
  • Asian races out of 91, 79 were misclassified or
    miscoded
  • Asian NOS out of 167, 163 were able to be
    classified with a more specific Asian race
  • Unknown race
  • out of 61, 60 were more specifically classified
    to a correct race code
  • 42 (70) out of 60 were white

16
Conclusions
  • Through this exercise, we were able to re-assign
    the correct race on 340 (90.9) cases out of 374
    cases reviewed
  • Miscoding was one of the main reasons for
    misclassification of race1, other reasons
    included multiple races and code transposition
  • Miscoding code 10 to 09, 04 to 05
  • Patient with multiple races white and Asian
    Indian
  • Code transposition code 10 to 01

17
Conclusions
  • NAPIIA was able to more accurately identify
    Vietnamese race group compare with other Asian
    race groups
  • Filipino race code had the least improved
    accuracy among race groups after NAPIIA
  • Reduce the percentage of unknown race and Asian
    NOS
  • Unknown race 0.26 to 0.23
  • Asian NOS 0.11 to 0.07

18
Conclusions
  • For a registry with small proportion of Asian
    cases, NAPIIA seems to be an excellent tool to
    improve the race coding accuracy on Asian groups
  • NAPIIA also can be applied to race codes other
    than Asian NOS to enhance registry data quality
    (with review)
  • A potential additional benefit of using NAPIIA
    for data quality control is the identification of
    cases with incorrect birthplace

19
Recommendations
  • Double check race codes to make sure you coded
    what you intended
  • If race is known, document the race information
    in the PE text field. For example, Filipino male
  • If race information is obtained from death
    certificate or other sources, make sure the
    corresponding NAACCR race code is coded

20
Recommendations
  • Factors that could improve the NAPIIAs
    performance
  • Correct Spelling on last and first name
  • Maiden name
  • Birthplace
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