Agreement between medical records and self-reports: Implications for transgender health research

Abstract

A key priority of transgender health research is the evaluation of long-term effects of gender affirmation treatment. Thus, accurate assessment of treatment receipt is critical. The data for this analysis came from an electronic medical records (EMR) based cohort of transgender individuals. A subset of cohort members were also asked to complete a self-administered survey. Information from the EMR was compared with survey responses to assess the extent of agreement regarding transmasculine (TM)/transfeminine (TF) status, hormone therapy receipt, and type of surgery performed. Logistic regression models were used to assess whether participant characteristics were associated with disagreement between data sources. Agreement between EMR and survey-derived information was high regarding TM/TF status (99%) and hormone therapy receipt (97%). Lower agreement was observed for chest reconstruction surgery (72%) and genital reconstruction surgery (84%). Using survey responses as the "gold standard", both chest and genital reconstruction surgeries had high specificity (95 and 93%, respectively), but the corresponding sensitivities were low (49 and 68%, respectively). A lower proportion of TM had concordant results for chest reconstruction surgery (64% versus 79% for TF) while genital reconstruction surgery concordance was lower among TF (79% versus 89% for TM). For both surgery types, agreement was highest among the youngest participants. Our findings offer assurance that EMR-based data appropriately classify cohort participants with respect to their TM/TF status or hormone therapy receipt. However, current EMR data may not capture the complete history of gender affirmation surgeries. This information is useful in future studies of outcomes related to gender affirming therapy.

Longitudinal Changes in Hematologic Parameters Among Transgender People Receiving Hormone Therapy

“…Each transgender cohort member was categorized as TF or TM, based on sex documented at birth. The TM and TF assignment methodology was described and validated previously [ 23 , 24 ]. The receipt of gender-affirming HT was ascertained based on filled prescription information documented in the pharmacy records.…”

Development of a computable phenotype to identify a transgender sample for health research purposes: a feasibility study in a large linked provincial healthcare administrative cohort in British Columbia, Canada

“…There is limited literature on EHR-based studies with the ability to validate an administrative transgender measure using a ‘gold standard’ comparison measure. 16 The two previous studies that have developed and validated algorithms to identify transgender individuals have both been conducted in non-representative samples in the USA, one using Medicare data 38 and one in a university medical centre. 16 Similar to the current study, the Medicare study found high specificity when comparing an EHR-based and a two-step survey-based transgender measure.…”

“… 39 As ‘gold standard’ two-step sex assigned at birth and current gender identity measures of transgender status 12 are slowly being implemented in routinely collected healthcare data sources, in the meantime NLPs to extract free-text data can be used to produce better gold standards against which to measure algorithm performance, as demonstrated by the Medicare study. 38 …”

Emerging topics in transgender medicine

“…Large prospective studies are challenging to conduct in this population. However, novel techniques have been developed to obtain information from existing electronic medical records as described in this issue by Gerth et al 14 .…”