Evaluation of the Metrological Quality of Medico-Administrative Data for Perinatal Indicators: A Pilot StudyGoueslard K1, Revert M2,3, Pierron A1, Vuagnat A1,4, Cottenet J1, Benzenine E1, Fresson J5 and Quantin C1,6,7*
- *Corresponding Author:
- Catherine Quantin
CHRU Dijon, Biostatistics and Medical Information Department (DIM)
University of Burgundy, Dijon, France
E-mail: [email protected]
Received date: April 29, 2016; Accepted date: June 06, 2016; Published date: June 15, 2016
Citation: Goueslard K, Revert M, Pierron A, Vuagnat A, Cottenet J, et al. (2016) Evaluation of the Metrological Quality of Medico-Administrative Data for Perinatal Indicators: A Pilot Study. J Community Med Health Educ 6:437. doi:10.4172/2161-0711.1000437
Copyright: © 2016 Goueslard K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background: In order to assess public health policies for the perinatal period, routinely produced indicators are needed for the whole population. These indicators are used to compare French national public health policy with those of other European countries. French medico-administrative data are straightforward and may be a valuable source of information for research. The study aimed to assess the metrological quality of medico-administrative data for perinatal indicators in three university hospitals.
Methods: The hospital data were compared with medical records for 2012 for 300 live births after 22 weeks of amenorrhea, drawn at random from three university hospitals. The variables were chosen according to the Europeristat Project’s core and recommended indicators, as well as those of the French National Perinatal survey conducted in 2010. The information gathered blindly from the medical records was compared with the medicoadministrative data. The positive predictive value (PPV) and the sensitivity were used to assess data quality.
Results: Data on maternal age, parity and mode of delivery as well as the rates of premature births from the two sources were superimposable. The PPV was 100.0% for pre-existing diabetes, 88.9% [74.3-100] for gestational diabetes and 100.0% for hypertension disorders with a rate of 9.0% in hospital data and 6.3% in the medical records. The positive predictive value for pre-eclampsia and HELLP syndrome was also 100% but the sensitivity was only 81.3%. The positive predictive value was 81.3% [67.8-94.8] for obesity and 90% [79.8-99.2] for postpartum hemorrhage.
Conclusion: This pilot study showed variability between establishments and between indicators, which reinforces the need for specific training in coding for activities. It confirms the importance of conducting such studies at the national level.