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

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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
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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

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Purpose

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

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Asian Population in Louisiana
From Census 2000 54,022 (1.208)
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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

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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

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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)

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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

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ResultsComparing 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

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ResultsComparing Original Race with NAPIIA
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ResultsDistribution of 374 Cases with
Inconsistent Race Codes
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ResultsComparing 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

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ResultsComparing Reviewed Race with NAPIIA
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ResultsComparing 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

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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

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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

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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

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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

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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

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Recommendations

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