We extracted sex definitions and summarized them by data element, code system, and value set (Multimedia Appendix 2). There are 25 entries with 7 unique data element names. After merging names with minor variations, 5 distinct data element names remained. After eliminating duplicate entries, 7 code systems and 21 unique value sets remained (Textbox 1). Most variations are when sex is unknown, undifferentiated, other, or has no information. For instance, unknown is coded as U, UNK, 3, or 39; undifferentiated is coded as UN, U, or 1. The same code can also have different values. For example, U can be Unknown, Unknown or Undifferentiated, Undifferentiated, or Undetermined; UN can be Unknown, Undifferentiated, or Not assigned male or female. Other can be Other, Other (including hermaphrodites and transsexual), or Other (person could not be uniquely identified). When no information is given, different codes and values are used, including 9-Not stated, 281-Null, and blank. From the definitions, it is unclear if Undifferentiated, Undetermined, and Indeterminate refer to the same concept.

We extracted gender definitions and summarized them by data element, code system, and value set (Multimedia Appendix 3). There are 35 entries with 12 unique data element names. After merging names with minor variations, 5 distinct names remained. After eliminating duplicate entries, 9 code systems and 22 unique value sets remained (Textbox 2).

Most variations are in undifferentiated, unknown, other, and no information is given. For instance, undifferentiated is coded as UN or U; unknown as Unknown, U, UNK, 3, or 9; and other as O, OTH, Other, or ZZ. There are also different values for undifferentiated and other, regardless of whether the same code is used or not. For instance, the value for undifferentiated can be Undifferentiated, Undifferentiated still birth only, or Undifferentiated (could not be uniquely defined as male or female, eg, hermaphrodite). Other can be Other, Other or unknown, Other (trans-sexual or hermaphrodites), or Other gender identity. When no information is given, different codes and values are used, including 7-Not collected, 8-Don’t know or no answer, 9-Refused, Refused, or something else, NA-Not applicable, or NI-No information. From the definitions, it is unclear if Undifferentiated and Indeterminate refer to the same concept.

We extracted sex and gender definitions published by 10 standards communities (Multimedia Appendices 5 and 6). The published standards ranged from those in routine use such as HL7V2, V3, and DICOM specifications, to recently proposed specifications from the FHIR, HL7 Gender Harmony Project, ONC-Interoperability Standards Advisory, OpenEHR Gender Archetype, and BioPortal-GSSO. For sex, there are 11 unique data element names from 13 code systems and 16 value sets (Textbox 3). GSSO has also defined 3 sex subtypes as biological sex, anatomic sex, and genotypic sex. For gender, there are 10 unique data element names from 11 code systems and 12 value sets (Textbox 4).

There are variations in sex and gender value options. Examples are M-Male and 1-Male for male, and UN-Undifferentiated, 9-Indeterminate, X-Other, X-Not known (not recorded), 0-Not known, or O-Non binary if no information is available. When compared with more established standards such as HL7 V2 and DICOM, those from ONC, OpenEHR, and GSSO have more sex and gender value options. For instance, ONC has defined gender identity and sex assigned at birth value sets from LOINC and SNOMED CT. Examples include LOINC code 77691-5 for Gender identity and SNOMED CT code 407377005|Female-to-male transsexual|. GSSO has more sex-related value sets based on biological features such as anatomical, chromosomal, brain, and genetic sex.

There are wide variations in the definition and implementation of sex and gender in Canadian EHRs and international health information standards. There is a lack of clarity in some sex and gender concepts. There is inconsistency in the data element names, code systems, and value sets used to represent sex and gender concepts across EHRs. The appropriateness and adequacy of some value set options are questioned as our societal understanding of sexual health continues to evolve. Outdated value set options raise concerns about current EHRs supporting the provision of culturally competent, safe, and affirmative health care. The limited options available also perpetuate the inequities faced by the TGNB populations. The expanded sex and gender definitions from leading Canadian organizations and international standards communities have also brought implementation challenges in migrating these definitions into existing EHRs. These findings are elaborated below.

A major issue is the conflated use of sex and gender as a discrete single binary concept to define sex and gender identity. This longstanding practice can create confusion when a person’s biology of being male or female along a spectrum is different from one’s identity or feeling of one’s gender identity as a woman, man, neither, both, or something else. The use of clinical gender, administrative gender, and administrative sex to represent sex and gender concepts for specific use is problematic because their context for use is often not well defined. As an example, the historical reliance on administrative gender as a means to assign hospital beds is inappropriate for transgender persons. The expanded sex and gender concepts from standard communities such as intersex, genotypic sex, and gender identity (eg, neutrois) are unfamiliar and sometimes overlapping terms that can be confusing to most but some clinicians and staff with specialty knowledge in sex and gender issues. These findings are consistent with the review by Jeffee [9], where care providers lacked familiarity with the terms and were ill-prepared to collect sex and gender data. They also echo the need for “accurate use of [sex- and gender-based medicine] terminology in research and clinical practice across medical specialties and across health professions” [5].

Similar to what is reported in the literature [3,117], there is a great deal of semantic variability in the data element names, code systems, and value sets used to represent sex and gender concepts in EHRs. For instance, sex, sex code, administrative sex, and patient’s sex may all refer to a person’s biology along a spectrum. However, different value set options exist across systems, including indeterminate, intersex, undifferentiated, and not assigned male or female when the person is not male or female. For gender, it is unclear if undifferentiated, undifferentiated stillbirth only, and indeterminate are equivalent terms. Even when sex and gender information is not available, it is unclear if such options as unknown, no information, not collected, not applicable, or <blank> have the same meaning. Although some value sets are from the same code systems such as DICOM and HL7, they can contain different options with little explanation (see Textbox 3). The HL7 Gender Harmony Project also noted these discrepancies in their recent work to standardize sex and gender definitions [118].

As our understanding of sex and gender evolves over time, some historic value options are now considered offensive or outdated [119,120]. Terms such as hermaphrodite and natal are now recognized as being offensive. M2F and F2M are regarded as outdated by some and should be replaced by transfeminine and transmasculine. Similarly, intersex and indeterminate should not be interchangeable terms. Misuse of the label preferred pronouns over pronouns as a data element name is also common [9,120].

As our society gives greater attention to sex and gender identity, the range of value options for sex and gender continues to expand. Dunne et al [7] reported that care providers and patients cited the need for a broader range of gender options and birth-assigned sex in EHRs. For use contexts, such terms as cisgender, transgender, and gender diversity may be adequate for classifying and reporting gender profiles at the population level. However, when caring for individual patients, distinguishing specific gender identity can be central to understanding health status, planning appropriate care, and maintaining patient safety. The proposed use of men and women as gender options instead of males and females also requires major shifts in society’s discourse on sex and gender labeling [5,9]. As we broaden the range of value options available, the notion of third gender in other cultures such as Hijra in India also needs to be considered. To support culturally competent, equitable care requires expanding sex and gender options as an ongoing practice [7,121].

There is no mandate in Canada on the type of sex and gender data to be collected in EHRs at present. Introducing expanded sex and gender definitions into existing EHRs can be a major undertaking for health care organizations, given the competing demands, limited resources, and redevelopment effort required. Implementation efforts to date suggest that sex and gender concepts are foundational in nature, and implicate a myriad of technical, organizational, and societal aspects [17,122]. Technically, there is the potential for modernized definitions to affect all EHRs. As such, consensus on relevant sex and gender definitions is needed, and the implementation effort should be well coordinated. There needs to be a trusted source where one can validate the origin and provenance of the recorded sex and gender data in different EHRs to ensure their accuracy. Organizationally, the implementation plan and rationale for change must be clearly articulated to care providers, support staff, patients, and others affected. Education and training on the rationale, policies, and practices involved in collecting and using this information are necessary to cultivate a culturally safe and equitable environment and to prevent potential harm such as misgendering, outing, and deadnaming [5-7]. At the societal level, we need to engage the public to raise their awareness of this change and explain how it may affect their day-to-day interactions with the health ecosystem [9,15].

On the basis of these findings, we propose a set of high-level actions to modernize sex and gender definitions in Canadian EHRs. These proposed actions are meant to initiate a dialogue with stakeholders, including individuals, communities, and organizations involved with developing or implementing, or affected by, the definitions. Collectively, they represent a set of guiding principles for organizations wishing to strive toward an inclusive EHR. These actions are also consistent with those reported by early adopters and leading organizations, including Fenway Health [17], Veteran Health Administration [11], University of California Davis Health System [122], and Canada’s St. Michael’s Hospital [123], that have started collecting expanded sex and gender data in their EHRs. Our proposed actions are described below.

Articulate the need for this work by explaining why the proposed actions are necessary to improve the health of sexual and gender minorities in Canada. These include the rationale for the collection of modernized sex and gender information in EHRs, how this information can advance our understanding of this population, and provide safe and culturally competent care. For instance, having expanded sex and gender definitions in the EHR is seen as an organization’s obligation for inclusion as part of the Canadian Human Rights Code and Charter of Rights and Freedom [124].

Reach consensus on relevant sex and gender concepts that can improve the health of Canadians, especially the underserved sex and gender minority populations. These concepts should address the need from policy, practice, research, and community perspectives [5]. Guidance from clinicians who use the data at the patient care level will be critical. This will help determine what codes and values are necessary versus what changes could occur at the policy level. Key concepts to consider include sex, sex assigned at birth, gender, administrative gender, gender identity, pronouns, and such variants as current sex or gender, gender expression, and legal sex or gender.

Reach consensus on expanded sex and gender definitions in EHRs with respect to data element names, code systems, and value sets [14,26,27]. For instance, the use of subtypes and synonyms for data element names may improve shared meaning while allowing flexibility in local systems. Further harmonization of code systems and value sets to represent sex and gender concepts may facilitate wider adoption. An example is the development of reference sex-gender code systems and value sets with cross-maps to those used in local systems to guide the transition. Another is to allow write-in options at the patient care level that can be rolled-up for analysis and reporting without suppressing important data.

Develop a coordinated action plan to implement expanded sex and gender definitions in Canadian EHRs. This plan should be action-oriented, stakeholder- and consensus-driven, and achievable in stages over time, given the limited resources and competing priorities in EHR redevelopment work [17,20]. The plan should also be coordinated with nonhealth government agencies where sex and gender data are collected (eg, driver’s licenses and passports). Examples include expanding or harmonizing sex-gender concepts, creating reference sex-gender definitions with cross-maps to local systems, conducting small-scale implementation with selected EHRs, collaborating with standards communities, and sharing the lessons.

Embrace EHR changes from socio-organizational and technical aspects to ensure success. Modernizing sex and gender definitions in EHRs is more than just a technical endeavor on data standardization but one that involves complex interplay of various social and organizational dynamics [125]. Organizations embarking on this journey need to engage senior executives, clinical leaders, and TGNB communities to cocreate an inclusive environment with culturally competent staff who are respectful of diversity, familiar with TGNB terminology, and knowledgeable in unique care needs of TGNB patients [126]. Key success factors include having explicit policy and practice guidelines on inclusion, ongoing staff education and training, a flexible EHR, and patient and public awareness to address the transition [11,15].

Demonstrate the benefits in tangible terms by establishing relevant and meaningful measures to evaluate the impact of these expanded definitions in EHRs on individuals, communities, organizations, and the health ecosystem over time. The measures should be multifaceted covering policy, practice, research, and community perspectives. Knowledge translation is an essential element of this evaluation process to share the results and lessons learned. Examples of measures include adherence to best practices and respecting protected human rights, data completeness in EHRs, perceived usefulness by patients and providers, and quantified improvements in health risks, service use, and health status.