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Problems With the Collection and Interpretation of Asian-American Health…
Problems With the Collection and Interpretation of Asian-American Health Data
In the US, 6 Asian American subgroups comprise abound 97% of the Asian American population. These ^ subgroups include Asian Indian, Chinese, Filipino, Japanese, Korean, and Vietnamese.
Within these subgroups, things like education, income, and language can differ greatly. In the US, however, Asian Americans are combined into a single categories in many situations, which doesn't allow us to see the differences between subgroups.
There is not much existing data on Asian-American health in general, so of course the health disparities among the subgroups are still largely unknown.
In order to explore possible disparities in Asian American populations, President Obama signed Executive Order 13125, and stated the need to disaggregate data by Asian American subgroup.
The next step after disaggregation is to gather statistically estimates across Asian subgroups, providing them with adequate translators if needed.
The purpose of the article: -
Address the implications of federal policy changes to data collection and reporting, and
Identify methods to improve the collection and interpretation of Asian American health data, focusing on omission, aggregation, and extrapolation.
Only in 2003 did the Secretary of the HHS approve the separation of the Asian and Pacific Islander race categories and apply Asian subcategories on birth and death certificates.
The recent Affordable Care Act requires the Secretary of HHS to establish data collection standards for race, ethnicity, etc.
Goals to improve collection of data on Asian Americans:
prioritizing Asian sample size in NHIS
enhancement of quality of data within the Substance Abuse and Mental Health Services Administrations National Survey on Drug use and health.
Omission of Asian American Subjects
The omission of Asian Americans from survey reports can affect the policies used to set the disparities agenda for the US.
Asian Americans are many times under sampled by subgroup, and some national surveys even omit people who are not English-proficient or low-SES Asian Americans.
Asian-Americans are also more likely to be omitted from clinical trials, cohort studies, and health surveys which hinders understanding of health disparities in the general Asian American group, but especially in Asian American subgroups.
Aggregate of Asian American Subgroups
In health surveys and studies that include Asian Americans, their data is often aggregated for the group, which can mask differences in subgroups.
The new HHS data standards may improve data collection and reporting for Asian Americans, but this does not extend to all national surveys
The NHIS collects data by Asian American subgroup, but many research papers using this data still group all Asian Americans together. This leads to statistically unstable estimates, masking existing differences in disease rates within subgroups.
In order to appropriately change healthcare for Asian American subgroups, subgroup levels data collection is imparative.
Extrapolation of Findings for Asian Americans
The findings for studies examining one Asian subgroup are often inappropriately interpreted and extrapolated. This is because findings from a single subgroup are presumed to be applicable to the entire American Asian population.
This can also be seen in drug trials. For example, the FDA included a statement on the table for a medication called Crestor suggesting half the usual dose for all Asians. However, this was only useful based on studies of one, subgroup, the Japanese.
Recommendations to improve the collection of and interpretation of Asian American health data to reduce the errors associated with omission, aggregation, and extrapolation:
collection of race/ethnicity data by Asian-American subgroup
2.oversampling of Asian Americansby subgroup
reporting of data by separate Asian-American subgroups, and
acknowledgement of heterogeneity among Asian Americans when interpreting data.