Medical record review to recover missing data in a Portuguese birth cohort: agreement with self-reported data collected by questionnaire and inter-rater variability.

Abstract

OBJECTIVES To assess the yield of medical record review to recover missing data originally collected by questionnaire, to analyze the agreement between these two data sources and to determine interobserver variability in clinical record review. METHODS We analyzed data from a birth cohort of 8,127 women who were consecutively recruited after giving birth from 2005-2006. Recruitment was conducted at all public maternity units of Porto, Portugal. We reviewed the medical records of 3,657 women with missing data in the baseline questionnaire and assessed agreement between these two sources by using information from participants with data from both sources. Interobserver variability was assessed by using 400 randomly selected clinical records. RESULTS Data on pregnancy complications and maternal anthropometric parameters were successfully recovered. Agreement between the questionnaire and records in family history data was fair, particularly for cardiovascular disease [k=0.27; 95% confidence interval (95%CI): 0.23-0.32]. The highest agreement was observed for personal history of diabetes (k=0.82; 95%CI 0.70-0.93), while agreement for hypertension was moderate (k=0.60; 95%CI 0.50-0.69). Discrepancies in prepregnancy body mass index classes were observed in 10.3% women. Data were highly consistent between the two reviewers, with the highest agreement found for gestational diabetes (k=1.00) and birth weight (99.5% concordance). CONCLUSION Data from the medical records and questionnaire were concordant with regard to pregnancy and well-known risk factors. The low interobserver variability did not threaten the precision of our data.

DOI: 10.1016/j.gaceta.2010.10.013
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@article{Alves2011MedicalRR, title={Medical record review to recover missing data in a Portuguese birth cohort: agreement with self-reported data collected by questionnaire and inter-rater variability.}, author={Elisabete Alves and Nuno Lunet and Sofia Correia and V{\'i}tor Manuel de Morais and Ana Azevedo and Henrique Barros}, journal={Gaceta sanitaria}, year={2011}, volume={25 3}, pages={211-9} }