The collection and use of patient sex, gender, race, ethnicity, and ancestry data among US-based clinical genomics laboratories
Laboratory Genetics and Genomics
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Introduction:
Clinical genetics organizations are responsible for continually assessing their practices and procedures using a lens of diversity, equity, and inclusion. However, there is a dearth of guidance pertaining to these principals from regulatory and professional organizations that laboratories generally defer to for direction. The collection of patient demographics including sex, gender, and race, ethnicity, and ancestry (REA) by genetic testing laboratories is not standardized and lacks consensus. Furthermore, evidence for the precise scientific value of this information on laboratory workflows is limited. Several studies have called for the development of consensus guidelines to aid both clinicians and researchers in collecting useful sex, gender, and REA data, and to reduce potential harms from the use of historic, confusing, or inaccurate language. In an effort to inform guideline development, we conducted a survey to assess the ways in which sex, gender, and REA data are collected and utilized among clinical genomics laboratories.
Methods:
The survey was developed using SurveyMonkey and distributed by email to laboratory directors and genetic counselors at 30 different US-based laboratories which offer clinical exome and/or genome sequencing. Responses were anonymized and extracted into Excel for analysis by the authors.
Results:
The survey was completed by 11 individuals, each representing a different clinical lab (37% response rate). Four participants work at commercial laboratories and the remainder work in a hospital or academic-based lab. Self-reported roles within their respective laboratories included genetic counselor, director, manager, administrator, and variant scientist.
According to survey responses, the most common source of patient sex, gender, and REA data across laboratories is the test requisition form. Patient sex is collected by all 11 labs, whereas gender is collected by two. Ten participants reported that their lab relies on patient sex as a quality assurance metric. Other common uses of sex data include variant interpretation and customized report content. Among the 8 labs that report collecting REA data, the terms used and sources of this information were markedly variable, with ethnicity being the most common term ascertained. Notably, 5 participants indicated that their laboratory does not routinely use patient REA data at any point in the testing pipeline. Among those that did report using REA data, the most common uses reported were variant interpretation, customized report content, and post-testing data analysis.
Participants noted various drivers for their collection practices, including clinical necessity, software requirements, regulatory requirements, and historic practice. Seven participants indicated that their lab had made recent changes to their processes for collection or use of patient sex and gender data, while 4 reported recent changes in the collection or use of patient REA data. Four participants reported lack of published guidelines as a barrier to making changes to their test request form or other processes related to collection and use of patient REA data.
Conclusion:
Conclusions: Taken together, the results of this survey highlight a dependence on patient sex for quality assurance and minimal use of patient gender data. Additionally, methods for collection of REA data are highly variable, and utility of this data appears to be limited or absent in most laboratories. The results from this study can be used to inform the development of guidelines which are needed to help standardize the collection of demographic data and to promote inclusive language practices by clinical genetics laboratories.
Clinical genetics organizations are responsible for continually assessing their practices and procedures using a lens of diversity, equity, and inclusion. However, there is a dearth of guidance pertaining to these principals from regulatory and professional organizations that laboratories generally defer to for direction. The collection of patient demographics including sex, gender, and race, ethnicity, and ancestry (REA) by genetic testing laboratories is not standardized and lacks consensus. Furthermore, evidence for the precise scientific value of this information on laboratory workflows is limited. Several studies have called for the development of consensus guidelines to aid both clinicians and researchers in collecting useful sex, gender, and REA data, and to reduce potential harms from the use of historic, confusing, or inaccurate language. In an effort to inform guideline development, we conducted a survey to assess the ways in which sex, gender, and REA data are collected and utilized among clinical genomics laboratories.
Methods:
The survey was developed using SurveyMonkey and distributed by email to laboratory directors and genetic counselors at 30 different US-based laboratories which offer clinical exome and/or genome sequencing. Responses were anonymized and extracted into Excel for analysis by the authors.
Results:
The survey was completed by 11 individuals, each representing a different clinical lab (37% response rate). Four participants work at commercial laboratories and the remainder work in a hospital or academic-based lab. Self-reported roles within their respective laboratories included genetic counselor, director, manager, administrator, and variant scientist.
According to survey responses, the most common source of patient sex, gender, and REA data across laboratories is the test requisition form. Patient sex is collected by all 11 labs, whereas gender is collected by two. Ten participants reported that their lab relies on patient sex as a quality assurance metric. Other common uses of sex data include variant interpretation and customized report content. Among the 8 labs that report collecting REA data, the terms used and sources of this information were markedly variable, with ethnicity being the most common term ascertained. Notably, 5 participants indicated that their laboratory does not routinely use patient REA data at any point in the testing pipeline. Among those that did report using REA data, the most common uses reported were variant interpretation, customized report content, and post-testing data analysis.
Participants noted various drivers for their collection practices, including clinical necessity, software requirements, regulatory requirements, and historic practice. Seven participants indicated that their lab had made recent changes to their processes for collection or use of patient sex and gender data, while 4 reported recent changes in the collection or use of patient REA data. Four participants reported lack of published guidelines as a barrier to making changes to their test request form or other processes related to collection and use of patient REA data.
Conclusion:
Conclusions: Taken together, the results of this survey highlight a dependence on patient sex for quality assurance and minimal use of patient gender data. Additionally, methods for collection of REA data are highly variable, and utility of this data appears to be limited or absent in most laboratories. The results from this study can be used to inform the development of guidelines which are needed to help standardize the collection of demographic data and to promote inclusive language practices by clinical genetics laboratories.