Abstract
BackgroundThe national Epithor database was initiated in 2003 in France. Fifteen years on, a quality assessment of the recorded data seemed necessary. This study examines the completeness of the data recorded in Epithor through a comparison with the French PMSI database, which is the national medico-administrative reference database. The aim of this study was to demonstrate the influence of data quality with respect to identifying 30-day mortality hospital outliers.MethodsWe used each hospital’s individual FINESS code to compare the number of pulmonary resections and deaths recorded in Epithor to the figures found in the PMSI. Centers were classified into either the good-quality data (GQD) group or the low-quality data (LQD) group. To demonstrate the influence of case-mix quality on the ranking of centers with low-quality data, we used 2 methods to estimate the standardized mortality rate (SMR). For the first (SMR1), the expected number of deaths per hospital was estimated with risk-adjustment models fitted with low-quality data. For the second (SMR2), the expected number of deaths per hospital was estimated with a linear predictor for the LQD group using the coefficients of a logistic regression model developed from the GQD group.ResultsOf the hospitals that use Epithor, 25 were classified in the GQD group and 75 in the LQD group. The 30-day mortality rate was 2.8% (n = 300) in the GQD group vs. 1.9% (n = 181) in the LQD group (P <0.0001). The between-hospital differences in SMR1 appeared substantial (interquartile range (IQR) 0–1.036), and they were even higher in SMR2 (IQR 0–1.19). SMR1 identified 7 hospitals as high-mortality outliers. SMR2 identified 4 hospitals as high-mortality outliers. Some hospitals went from non-outlier to high mortality and vice-versa. Kappa values were roughly 0.46 and indicated moderate agreement.ConclusionWe found that most hospitals provided Epithor with high-quality data, but other hospitals needed to improve the quality of the information provided. Quality control is essential for this type of database and necessary for the unbiased adjustment of regression models.
Highlights
Epithor, a French national database for thoracic surgery, has been in operation since 2003
For the second (SMR2), the expected number of deaths per hospital was estimated with a linear predictor for the low-quality data (LQD) group using the coefficients of a logistic regression model developed from the good-quality data (GQD) group
The 30-day mortality rate was 2.8% (n = 300) in the GQD group vs. 1.9% (n = 181) in the LQD group (P
Summary
A French national database for thoracic surgery, has been in operation since 2003. It has led to the publication of several research articles [1,2,3,4,5,6]) and, most notably, Falcoz et al [7] used it to develop the Thoracoscore, a predictive score that is widely used by European surgeons according to the latest European recommendations [8].A number of existing publications have highlighted the importance of data quality in medical databases [9,10], since missing or biased data can lead to erroneous conclusions regarding hospital quality [11,12] At this stage of development, it seems to us that the quality of the data within the Epithor database needs to be assessed. The aim of this study was to demonstrate the influence of data quality with respect to identifying 30-day mortality hospital outliers
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
