Premium
How accurate is the reporting of obstetric haemorrhage in hospital discharge data? A validation study
Author(s) -
LAIN Samantha J.,
ROBERTS Christine L.,
HADFIELD Ruth M.,
BELL Jane C.,
MORRIS Jonathan M.
Publication year - 2008
Publication title -
australian and new zealand journal of obstetrics and gynaecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.734
H-Index - 65
eISSN - 1479-828X
pISSN - 0004-8666
DOI - 10.1111/j.1479-828x.2008.00910.x
Subject(s) - medicine , gold standard (test) , medical diagnosis , incidence (geometry) , medical record , population , postpartum haemorrhage , hospital discharge , diagnosis code , positive predicative value , emergency medicine , antepartum haemorrhage , obstetrics , medical emergency , predictive value , pregnancy , surgery , intensive care medicine , caesarean section , environmental health , physics , pathology , biology , optics , genetics
Background: Routinely collected datasets are frequently used for population‐based research but their accuracy needs to be assured. Aim: This study aims to assess the accuracy of hospital discharge data in identifying obstetric haemorrhage diagnoses and procedures, and estimate their population incidence. Methods: The medical records of 1200 randomly selected women were reviewed and compared with obstetric haemorrhage diagnoses and procedures in the hospital discharge data. Sensitivity, specificity, and positive and negative predictive values were calculated using the medical records as the ‘gold standard’. Estimates of population incidence were calculated and weighted by the sampling probabilities. Results: Estimated population incidence for any antepartum haemorrhage was 1.8 per 100, and post partum haemorrhage was 7.2 per 100 women. Obstetric haemorrhage diagnosis and procedure codes tended to be underreported, with sensitivities ranging from 28.3% to 100%. All codes had specificities of 98.9% or greater. The identification of obstetric haemorrhage differed between levels of severity. Conclusion: The results indicate that population health datasets can be a reliable information source; however, these datasets could be improved with more complete documentation in medical records.