The reports of Nuffield Trust highlight the discrepancies in the ethnicity coding.
Poor data regarding ethnicity is obscuring the extent of disparities for the impact of COVID. The Nuffield Trust has found it recently. In a report regarding the ethnicity coding in English health service datasets, the health think tank said that the NHS is failing in it. The NHS is also failing to record the ethnicities for an excessive and growing portion of patients, which leads to health inequalities.
The analysis of hospital A&E and the community service data has found that 13% of inpatients and 17% of the outpatients are not in records. Other data quality problems are including incomplete coding, systematic biases in the data, and inconsistent use of the codes.
For the patients with multiple contacts with NHS, patients of the minority ethnic group are more likely to have a different code. The Nuffield Trust says these issues are meaning the estimate of the COVID infections. Also, it includes the hospitalizations and the deaths which could miscount in the minority section and white groups.
This report is noting that NHS guidance on thee ethnicity coding has not had its update since 2001. Also, it is calling for the development and the implementation of the various updates in the guidance.
Nuffield Trust is saying that the lack of comprehensive data on the health and mortality of ethnicity is a significant obstacle. It is also addressing the various health inequalities.
Earlier this year, the NHS England came up with its announcement about it. It has announced that it would begin publishing the ethnicity data on those who are receiving the Covid vaccines. It is also following many backlashes and many accusations about the potential bias.
Public Health England published a report in August 2020. It says that people of Bangladeshi origin are most likely to die from COVID-19. People from the black ethnic groups would be the most likely ones to get diagnosed with the virus.
Hence it is essential to commit to improving the recording of the patient ethnicity data to get better information to meet the challenges.
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