Evidence map›Paper›PMID 33174858›Full record

ArticleJournal of medical Internet research2020

An Environmental Scan of Sex and Gender in Electronic Health Records: Analysis of Public Information Sources.

Francis Lau, Marcy Antonio, Kelly Davison, Roz Queen, Katie Bryski

Erratum issuedAbstract read
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Toward an inclusive digital health system for sexual and gender minorities in Canada.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  14. Article
  15. Review
  16. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Francis Lau *School of Health Information Science, University of Victoria, Victoria, BC, Canada.ORCID 0000-0001-7010-3281
Marcy Antonio *School of Health Information Science, University of Victoria, Victoria, BC, Canada.ORCID 0000-0001-9332-8512
Kelly Davison *School of Health Information Science, University of Victoria, Victoria, BC, Canada.ORCID 0000-0002-1965-4691
Roz Queen *School of Health Information Science, University of Victoria, Victoria, BC, Canada.ORCID 0000-0002-6064-521X
Katie BryskiCanada Health Infoway, Toronto, ON, Canada.ORCID 0000-0001-5339-1437

Funding

CIHR
6 · The paper itself

Abstract

backgroundHistorically, the terms sex and gender have been used interchangeably as a binary attribute to describe a person as male or female, even though there is growing recognition that sex and gender are distinct concepts. The lack of sex and gender delineation in electronic health records (EHRs) may be perpetuating the inequities experienced by the transgender and gender nonbinary (TGNB) populations.

objectiveThis study aims to conduct an environmental scan to understand how sex and gender are defined and implemented in existing Canadian EHRs and current international health information standards.

methodsWe examined public information sources on sex and gender definitions in existing Canadian EHRs and international standards communities. Definitions refer to data element names, code systems, and value sets in the descriptions of EHRs and standards. The study was built on an earlier environment scan by Canada Health Infoway, supplemented with sex and gender definitions from international standards communities. For the analysis, we examined the definitions for clarity, consistency, and accuracy. We also received feedback from a virtual community interested in sex-gender EHR issues.

resultsThe information sources consisted of public website descriptions of 52 databases and 55 data standards from 12 Canadian entities and 10 standards communities. There are 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 options are questioned as our societal understanding of sexual health evolves. Outdated value options raise concerns about current EHRs supporting the provision of culturally competent, safe, and affirmative health care. The limited options also perpetuate the inequities faced by the TGNB populations. The expanded sex and gender definitions from leading Canadian organizations and international standards communities have brought challenges in how to migrate these definitions into existing EHRs. We proposed 6 high-level actions, which are to articulate the need for this work, reach consensus on sex and gender concepts, reach consensus on expanded sex and gender definitions in EHRs, develop a coordinated action plan, embrace EHR change from socio-organizational and technical aspects to ensure success, and demonstrate the benefits in tangible terms.

conclusionsThere are variations in sex and gender concepts across Canadian EHRs and the health information standards that support them. Although there are efforts to modernize sex and gender concept definitions, we need decisive and coordinated actions to ensure clarity, consistency, and competency in the definition and implementation of sex and gender concepts in EHRs. This work has implications for addressing the inequities of TGNB populations in Canada.

Indexed as

Electronic Health RecordsFemaleGender IdentityHumansMaleMedical InformaticsSex Characteristicselectronic health recordsgendersexstandardstransgender persons

Identifiers

PMID33174858
PMCPMC7688387

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.