Abulibdeh Rawan, Tu Karen, Butt Debra A, Train Anthony, Crampton Noah, Sejdić Ervin
Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada.
Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
PLoS One. 2025 Jan 17;20(1):e0317599. doi: 10.1371/journal.pone.0317599. eCollection 2025.
There is a growing need to document sociodemographic factors in electronic medical records to produce representative cohorts for medical research and to perform focused research for potentially vulnerable populations. The objective of this work was to assess the content of family physicians' electronic medical records and characterize the quality of the documentation of sociodemographic characteristics. Descriptive statistics were reported for each sociodemographic characteristic. The association between the completeness rates of the sociodemographic data and the various clinics, electronic medical record vendors, and physician characteristics was analyzed. Supervised machine learning models were used to determine the absence or presence of each characteristic for all adult patients over the age of 18 in the database. Documentation of marital status (51.0%) and occupation (47.2%) were significantly higher compared to the rest of the variables. Race (1.4%), sexual orientation (2.5%), and gender identity (0.8%) had the lowest documentation rates with a 97.5% missingness rate or higher. The correlation analysis for vendor type demonstrated that there was significant variation in the availability of marital and occupation information between vendors (χ2 > 6.0, P < 0.05). Variability in documentation between clinics indicated that the majority of characteristics exhibited high variation in completeness rates with the highest variation for occupation (median: 47.2, interquartile range: 60.6%) and marital status (median: 45.6, interquartile: 59.7%). Finally, physician sex, years since a physician graduated, and whether a physician was a foreign vs a Canadian medical graduate were significantly associated with documentation rates of place of birth, citizenship status, occupation, and education in the electronic medical records. Our findings suggest a crucial need to implement better documentation strategies for sociodemographic information in the healthcare setting. To improve completeness rates, healthcare systems should monitor, encourage, enforce, or incentivize sociodemographic data collection standards.
在电子病历中记录社会人口学因素的需求日益增长，以便为医学研究生成具有代表性的队列，并针对潜在弱势群体开展针对性研究。这项工作的目的是评估家庭医生电子病历的内容，并描述社会人口学特征记录的质量。报告了每个社会人口学特征的描述性统计数据。分析了社会人口学数据的完整性率与各诊所、电子病历供应商以及医生特征之间的关联。使用监督机器学习模型确定数据库中所有18岁以上成年患者每种特征的有无。婚姻状况（51.0%）和职业（47.2%）的记录率明显高于其他变量。种族（1.4%）、性取向（2.5%）和性别认同（0.8%）的记录率最低，缺失率达到97.5%或更高。供应商类型的相关性分析表明，不同供应商之间婚姻和职业信息的可用性存在显著差异（χ2>6.0，P<0.05）。诊所之间记录的差异表明，大多数特征的完整性率差异很大，职业（中位数：47.2，四分位间距：60.6%）和婚姻状况（中位数：45.6，四分位间距：59.7%）的差异最大。最后，医生的性别、毕业年限以及是外国医学毕业生还是加拿大医学毕业生与电子病历中出生地、公民身份、职业和教育程度的记录率显著相关。我们的研究结果表明，在医疗环境中迫切需要实施更好的社会人口学信息记录策略。为了提高完整性率，医疗系统应监测、鼓励、强制或激励社会人口学数据收集标准。
