{"title":"新西兰奥特亚罗瓦地区怀卡托地区初级和二级医疗保健服务机构中种族记录的准确性。","authors":"Brooke Blackmore, Marianne Elston, Belinda Loring, Papaarangi Reid, Jade Tamatea","doi":"10.26635/6965.6445","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Ethnicity is an important variable, and in Aotearoa New Zealand it is used to monitor population health needs, health services outcomes and to allocate resources. However, there is a history of undercounting Māori. The aim of this study was to compare national and primary care ethnicity data to self-reported ethnicity from a Kaupapa Māori research cohort in the Waikato region.</p><p><strong>Methods: </strong>Through individual record linkage, prospective self-reported ethnicity, collected using New Zealand Census and Ministry of Health - Manatū Hauora ethnicity protocol as a \"gold standard\", was compared to ethnicity in secondary and primary healthcare datasets. Logistic regression analyses were used to determine if demographic variables such as age, ethnicity and deprivation are associated with inaccuracies in ethnicity recording.</p><p><strong>Results: </strong>Māori were undercounted in secondary NHI (32.5%) and primary care (31.3%) datasets compared to self-reported (34.6%). Between 9.5-11% of individuals had a different ethnicity recorded in health datasets than self-reported. Multiple ethnicities were less often recorded (secondary NHI [5.3%] and primary care [5.8%]) compared to self-reported (8.7%). Māori ethnicity (p=0.039) and multiple ethnicity (p<0.001) were associated with lower ethnicity data accuracy.</p><p><strong>Conclusion: </strong>Routine health datasets fail to adequately collect ethnicity, particularly for those with multiple ethnicities. Inaccuracies disproportionately affect Māori and urgent efforts are needed to improve compliance with ethnicity data standards at all levels of the health system.</p>","PeriodicalId":48086,"journal":{"name":"NEW ZEALAND MEDICAL JOURNAL","volume":"137 1602","pages":"111-124"},"PeriodicalIF":1.2000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accuracy of ethnicity records at primary and secondary healthcare services in Waikato region, Aotearoa New Zealand.\",\"authors\":\"Brooke Blackmore, Marianne Elston, Belinda Loring, Papaarangi Reid, Jade Tamatea\",\"doi\":\"10.26635/6965.6445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>Ethnicity is an important variable, and in Aotearoa New Zealand it is used to monitor population health needs, health services outcomes and to allocate resources. However, there is a history of undercounting Māori. The aim of this study was to compare national and primary care ethnicity data to self-reported ethnicity from a Kaupapa Māori research cohort in the Waikato region.</p><p><strong>Methods: </strong>Through individual record linkage, prospective self-reported ethnicity, collected using New Zealand Census and Ministry of Health - Manatū Hauora ethnicity protocol as a \\\"gold standard\\\", was compared to ethnicity in secondary and primary healthcare datasets. Logistic regression analyses were used to determine if demographic variables such as age, ethnicity and deprivation are associated with inaccuracies in ethnicity recording.</p><p><strong>Results: </strong>Māori were undercounted in secondary NHI (32.5%) and primary care (31.3%) datasets compared to self-reported (34.6%). Between 9.5-11% of individuals had a different ethnicity recorded in health datasets than self-reported. Multiple ethnicities were less often recorded (secondary NHI [5.3%] and primary care [5.8%]) compared to self-reported (8.7%). Māori ethnicity (p=0.039) and multiple ethnicity (p<0.001) were associated with lower ethnicity data accuracy.</p><p><strong>Conclusion: </strong>Routine health datasets fail to adequately collect ethnicity, particularly for those with multiple ethnicities. Inaccuracies disproportionately affect Māori and urgent efforts are needed to improve compliance with ethnicity data standards at all levels of the health system.</p>\",\"PeriodicalId\":48086,\"journal\":{\"name\":\"NEW ZEALAND MEDICAL JOURNAL\",\"volume\":\"137 1602\",\"pages\":\"111-124\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NEW ZEALAND MEDICAL JOURNAL\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26635/6965.6445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NEW ZEALAND MEDICAL JOURNAL","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26635/6965.6445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Accuracy of ethnicity records at primary and secondary healthcare services in Waikato region, Aotearoa New Zealand.
Aims: Ethnicity is an important variable, and in Aotearoa New Zealand it is used to monitor population health needs, health services outcomes and to allocate resources. However, there is a history of undercounting Māori. The aim of this study was to compare national and primary care ethnicity data to self-reported ethnicity from a Kaupapa Māori research cohort in the Waikato region.
Methods: Through individual record linkage, prospective self-reported ethnicity, collected using New Zealand Census and Ministry of Health - Manatū Hauora ethnicity protocol as a "gold standard", was compared to ethnicity in secondary and primary healthcare datasets. Logistic regression analyses were used to determine if demographic variables such as age, ethnicity and deprivation are associated with inaccuracies in ethnicity recording.
Results: Māori were undercounted in secondary NHI (32.5%) and primary care (31.3%) datasets compared to self-reported (34.6%). Between 9.5-11% of individuals had a different ethnicity recorded in health datasets than self-reported. Multiple ethnicities were less often recorded (secondary NHI [5.3%] and primary care [5.8%]) compared to self-reported (8.7%). Māori ethnicity (p=0.039) and multiple ethnicity (p<0.001) were associated with lower ethnicity data accuracy.
Conclusion: Routine health datasets fail to adequately collect ethnicity, particularly for those with multiple ethnicities. Inaccuracies disproportionately affect Māori and urgent efforts are needed to improve compliance with ethnicity data standards at all levels of the health system.