Toa Payoh Polyclinic, National Healthcare Group Polyclinics, Singapore.
Ann Acad Med Singap. 2023 Feb;52(2):62-70. doi: 10.47102/annals-acadmedsg.2022246.
Studies of concordance between patients' self-report of diseases and a criterion standard (e.g. chart review) are usually conducted in epidemiological studies to evaluate the agreement of self-reported data for use in public health research. To our knowledge, there are no published studies on concordance for highly prevalent chronic diseases such as diabetes and pre-diabetes. The aims of this study were to evaluate the concordance between patients' self-report and their medical records of diabetes and pre-diabetes diagnoses, and to identify factors associated with diabetes concordance.
A cross-sectional, interviewer-administered survey was conducted on patients with chronic diseases after obtaining written consent to assess their medical notes. Interviewers were blinded to the participants' profiles. Concordance was evaluated using Cohen's kappa (κ). A multivariable logistic regression model was used to identify factors associated with diabetes concordance.
There was substantial agreement between self-reported and medical records of diabetes diagnoses (κ=0.76) and fair agreement for pre-diabetes diagnoses (κ=0.36). The logistic regression model suggested that non-Chinese patients had higher odds of diabetes concordance than Chinese patients (odds ratio [OR]=4.10, 95% confidence interval [CI] 1.19-14.13, =0.03). Patients with 3 or more chronic diseases (i.e. multimorbidity) had lower odds of diabetes concordance than patients without multimorbidity (OR=0.21, 95% CI 0.09-0.48, <0.001).
Diabetes concordance was substantial, supporting the use of self-report of diabetes by patients with chronic diseases in the primary care setting for future research. Pre-diabetes concordance was fair and may have important clinical implications. Further studies to explore and improve health literacy and patient-physician communication are needed.
为了评估自我报告数据在公共卫生研究中的应用一致性，通常在流行病学研究中对患者自我报告的疾病与标准（如病历回顾）之间的一致性进行研究。据我们所知，目前尚无关于糖尿病和糖尿病前期等高发慢性病患者自我报告与病历诊断一致性的研究。本研究旨在评估患者自我报告与病历中糖尿病和糖尿病前期诊断的一致性，并确定与糖尿病一致性相关的因素。
在获得书面同意后，对慢性病患者进行了横断面、访谈员管理的调查，以评估他们的病历。访谈员对参与者的情况一无所知。采用 Cohen's kappa（κ）评估一致性。使用多变量逻辑回归模型确定与糖尿病一致性相关的因素。
自我报告和病历中糖尿病诊断的一致性很高（κ=0.76），而糖尿病前期诊断的一致性为中等（κ=0.36）。逻辑回归模型表明，非华裔患者比华裔患者更有可能出现糖尿病一致性（比值比[OR]=4.10，95%置信区间[CI]1.19-14.13，=0.03）。患有 3 种或更多慢性病（即多种合并症）的患者比没有多种合并症的患者出现糖尿病一致性的可能性更低（OR=0.21，95%CI 0.09-0.48，<0.001）。
糖尿病的一致性很高，支持在初级保健环境中使用患有慢性病的患者自我报告糖尿病，用于未来的研究。糖尿病前期的一致性为中等，可能具有重要的临床意义。需要进一步研究以探索和提高健康素养和医患沟通。
