| Autor: |
Khai Wei Tan, Jeremy Kaiwei Lew, Poay Sian Sabrina Lee, Sin Kee Ong, Hui Li Koh, Doris Yee Ling Young, Eng Sing Lee |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Annals of the Academy of Medicine, Singapore. 52:62-70 |
| ISSN: |
0304-4602 |
| DOI: |
10.47102/annals-acadmedsg.2022246 |
| Popis: |
Introduction: 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. Method: 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. Results: 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, P=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, P |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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