The accuracy of population health data for monitoring trends and outcomes among women with diabetes in pregnancy
Introduction
Pregestational and gestational diabetes mellitus (PDM and GDM) are common complications of pregnancy, affecting around 0.3–0.6% and 2–9% of pregnancies respectively [1], [2], [3], [4], [5], [6]. Both forms of diabetes are associated with adverse outcomes for mothers and their infants [4], [7], [8], [9], [10], [11].
The population coverage and availability of routinely collected, population health data sets (PHDS) make PHDS a cost-efficient resource for estimating the prevalence of PDM and incidence of GDM in pregnant populations, and for assessing the health outcomes for these women and their infants [12], [13]. These type of data are used internationally to monitor diabetes and as the basis of research studies, usually without regard for the validity of the reporting [2], [10], [14], [15], [16]. There are, however, limitations relating to the completeness and validity of data in studies utilising single datasets [4], [12], [13]. For conditions like diabetes where information is available from more than one dataset, linkage of PHDS may reduce the problem of under-ascertainment, but this allows the possibility of discordant reports [17], [18], [19]. Only one recent study has assessed the accuracy and reliability of the reporting of diabetes in pregnancy in population health data [17]. The aim of this study was to assess the accuracy of the individual birth and hospital datasets alone, and either of these datasets, in identifying maternal PDM and GDM.
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Data sources
New South Wales (NSW) is the most populous Australian state with a population of ∼6.8 million and 83,000 births per annum in over 100 hospitals. The population health data for this study were obtained from two NSW Department of Health routinely collected datasets, the NSW Midwives Data Collection (MDC) and the NSW Admitted Patient Data Collection (APDC). The MDC (referred to as ‘birth data’) is a legislated surveillance system covering all NSW births ≥20 weeks gestation or ≥400 g birthweight,
Results
Medical records were available for 1184 of the 1200 women sampled. Demographic and pregnancy characteristics of the weighted sample were not statistically different from the population [23]; 18.2% were aged 35 years or older, 39.9% were primiparous, 10.3% were admitted to rural hospitals, 44.3% to tertiary hospitals, and 93.3% had a gestational age of 37 weeks or more. Diabetes prevalence is reported in Table 1 and the accuracy of the diabetes coding in the individual birth and hospital
Discussion
This study reports the accuracy and reliability of contemporary birth and ICD10-coded hospital discharge data (individual and linked) in identifying diabetes during pregnancy. We have demonstrated that hospital data are more accurate and reliable than birth data, and that PDM is more reliably reported than GDM. Where available, hospital data should be used in preference to birth data to monitor population rates of diabetes during pregnancy.
Assessment of the validity of PHDS is important from
Conflict of interest statement
The authors declare that they have no conflict of interest.
Acknowledgements
We wish to acknowledge the help of Margie Pym in collecting the data. Jane Ford is supported by the Health Research and Outcomes Network, a National Health and Medical Research Council (NHMRC) Capacity Building Grant. Christine Roberts is a NHMRC Senior Research Fellow. This study was supported by a NHMRC Project Grant (#402498).
References (34)
- et al.
Medicaid data as a resource for epidemiologic studies: strengths and limitations
J. Clin. Epidemiol.
(1989) - et al.
Factors influencing the cost of hospital care for people with diabetes in Australia
J. Diab. Complications
(2006) - et al.
The reporting of pre-existing maternal medical conditions and complications of pregnancy on birth certificates and in hospital discharge data
Am. J. Obstet. Gynecol.
(2005) - et al.
Using administrative data to describe casemix: a comparison with the medical record
J. Clin. Epidemiol.
(1994) - et al.
Accuracy of obstetric diagnoses and procedures in hospital discharge data
Am. J. Obstet. Gynecol.
(2006) - et al.
Trends in postpartum haemorrhage
Aust. N.Z. J. Public Health
(2006) - P.J. Laws, E.A. Sullivan, Australia's mothers and babies 2002, AIHW Cat. No. PER 28, AIHW National Perinatal Statistics...
- et al.
Fetal and neonatal outcomes of diabetic pregnancies
Obstet. Gynecol.
(2006) - et al.
Retraction of paper on maternal diabetes
BMJ
(2003) - et al.
Gestational diabetes in Victoria in 1996: incidence, risk factors and outcomes
Med. J. Aust.
(2002)
Gestational diabetes mellitus–management guidelines. The Australasian Diabetes in Pregnancy Society
Med. J. Aust.
Diagnosis and classification of diabetes mellitus
Diab. Care
Risk of complications of pregnancy in women with type 1 diabetes: nationwide prospective study in the Netherlands
BMJ
Effect of treatment of gestational diabetes mellitus on pregnancy outcomes
N. Engl. J. Med.
Trends in prevalence and outcomes of pregnancy in women with pre-existing type I and type II diabetes
BJOG
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