Quality of Data in Perinatal Population Health Databases

Lain, Samantha J.; Hadfield, Ruth M.; Raynes‐Greenow, Camille; Ford, Jane B.; Mealing, Nicole; Algert, Charles S.; Roberts, Christine L.

doi:10.1097/mlr.0b013e31821d2b1d

Cited by 204 publications

(200 citation statements)

References 58 publications

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“…17 Only factors that are well and accurately reported were included in the analyses. 16,[18][19][20][21][22] Missing data were infrequent, only 0.02% records were missing a gestational age and 0.02% were missing mode of onset of labor.…”

Section: Methodsmentioning

confidence: 99%

Trends in planned early birth: a population-based study

Morris

Algert

Falster

et al. 2012

American Journal of Obstetrics and Gynecology

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were inductions. As planned births increased, maternal risks shifted, including a decline in inductions with maternal hypertension from 31.9% to 23.9%. Earlier birth was contemporaneous with increases (trend P<0.001) in neonatal and maternal morbidity from 3.0% to 3.2% and 0.9 % to 1.3%, respectively. Conclusion:Planned birth before the due date is increasing but without reducing perinatal deaths.

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Section: Methodsmentioning

confidence: 99%

Trends in planned early birth: a population-based study

Morris

Algert

Falster

et al. 2012

American Journal of Obstetrics and Gynecology

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“…Validation studies comparing these linked population datasets to medical records have shown that gestational age and jaundice are accurately reported. 35 We have also adjusted for a comprehensive list of known risk factors for jaundice. The limitations of the study include the calculation for LOS at birth; we were only able to calculate LOS in days rather than hours.…”

Section: Figurementioning

confidence: 99%

Early Discharge of Infants and Risk of Readmission for Jaundice

et al. 2015

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OBJECTIVES: To examine the association between early discharge from hospital after birth and readmission to hospital for jaundice among term infants, and among infants discharged early, to investigate the perinatal risk factors for readmission for jaundice.METHODS: Birth data for 781 074 term live-born infants born in New South Wales, Australia from 2001 to 2010 were linked to hospital admission data. Logistic regression models were used to investigate the association between postnatal length of stay (LOS), gestational age (GA), and readmission for jaundice in the first 14 days of life. Other significant perinatal risk factors associated with readmission for jaundice were examined for infants discharged in the first 2 days after birth.RESULTS: Eight per 1000 term infants were readmitted for jaundice. Infants born at 37 weeks' GA with an LOS at birth of 0 to 2 days were over 9 times (adjusted odds ratio [aOR] 9.43; 95% CI, and at 38 weeks' GA were 4 times (aOR 4.05; 95% CI, 3.62-4.54) more likely to be readmitted for jaundice compared with infants born at 39 weeks' GA with an LOS of 3 to 4 days. Other significant risk factors for readmission for jaundice for infants discharged 0 to 2 days after birth included vaginal birth, born to mothers from an Asian country, born to first-time mothers, or being breastfed at discharge.CONCLUSIONS: This study can inform guidelines or policy about identifying infants at risk for readmission for jaundice and ensure that appropriate post-discharge follow-up is received.WHAT'S KNOWN ON THIS SUBJECT: Studies examining early postnatal discharge and readmission for jaundice report conflicting results. Infants born 37 to 38 weeks' gestation have an increased risk for readmission for jaundice; however, the impact of early discharge on this group has not been investigated. WHAT THIS STUDY ADDS:Early postnatal discharge was significantly associated with readmission for jaundice. Of the infants discharged early, those born 37 to 38 weeks' gestation, born via vaginal delivery, born to Asian mothers, or were breastfed had the greatest risk for readmission. Dr Lain participated in the study design, took primary responsibility of the data analysis, and drafted the initial manuscript; Associate Professor Roberts participated in the study design and data analysis and interpretation, and reviewed and revised manuscript; Dr Bowen participated in interpretation of the data and revision of manuscript for important clinical content; Associate Professor Nassar participated in the study design and data analysis and interpretation, and reviewed and revised manuscript; and all authors approved the final manuscript as submitted. The length of stay (LOS) in hospital after the birth of a child has been a controversial topic over the past few decades. A Cochrane Review found early postnatal discharge, defined as earlier than standard care, to have no adverse effects on breastfeeding and maternal depression when accompanied by a policy of nursing/midwifery home visits. However, they reported more re...

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“…The accuracy and reliability of individual data items are typically reported. 3,4 The variables in perinatal population data can be continuous (e.g. gestational age), nominal (e.g.…”

Section: Abstract: Aimmentioning

confidence: 99%

Are pregnancy outcomes associated with risk factor reporting in routinely collected perinatal data?

Ampt¹,

Ford²,

Taylor³

et al. 2013

NSW Public Health Bull.

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Aim:To assess reporting characteristics of commonly dichotomised pregnancy outcomes (e.g. preterm/term birth); and to investigate whether behaviours (e.g. smoking), medical conditions (e.g. diabetes) or interventions (e.g. induction) were reported differently by pregnancy outcomes. Methods: Further analysis of a previous validation study was undertaken, in which 1680 perinatal records were compared with data extracted from medical records. Continuous and polytomous variables were dichotomised, and risk factor reporting was assessed within the dichotomised outcome groups. Agreement, kappa, sensitivity and positive predictive value calculations were undertaken. Results: Gestational age, birthweight, Apgar scores, perineal trauma, regional analgesia and baby discharge status (live birth/ stillbirth) were reported with high accuracy and reliability when dichotomised (kappa values 0.95-1.00, sensitivities 94.7-100.0%). Although not statistically significant, there were trends for hypertension, infant resuscitation and instrumental birth to be more accurately reported among births with adverse outcomes. In contrast, smoking ascertainment tended to be poorer among preterm births and when babies were ,2500 g. Conclusion: Dichotomising variables collected as continuous or polytomous variables in birth data results in accurate and well ascertained data items. There is no evidence of systematic differential reporting of risk factors.Population level data are well suited to studies evaluating health care. With the risk of sampling bias removed, estimation of incidence and prevalence rates can be made, allowing for description of the total burden of a particular disease or outcome, analysis of risk factors and trends, as well as identification of health inequalities and estimation of health costs. 1,2 Accurate conclusions from such analyses rely on high quality data that truly represent the population experience. Assessment of data quality (completeness and accuracy) is typically undertaken by a validation study, in which data from a sample of records from the population dataset are compared to a highly reliable and accurate source of data ('the gold standard') for the corresponding records. The accuracy and reliability of individual data items are typically reported. 3,4 The variables in perinatal population data can be continuous (e.g. gestational age), nominal (e.g. mode of delivery) and ordinal (e.g. first, second, third or fourth degree perineal tears), with validation of such variables typically reporting percent agreement and kappa statistics. These types of variables are frequently dichotomised in analyses (e.g. preterm birth, caesarean section, or third-fourth degree tears), 5,6 but little assessment has been undertaken into the accuracy and reliability of their dichotomised form.Differential reporting in population health data occurs when a variable is reported with different accuracy and reliability amongst different strata of another variable. This can introduce systematic bias, leading to under or over...

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Quality of Data in Perinatal Population Health Databases

Abstract: This comprehensive collection of validation studies summarizing the quality of perinatal population data will be an invaluable resource to all researchers working with PHDS.

Cited by 204 publications

References 58 publications

Trends in planned early birth: a population-based study

Trends in planned early birth: a population-based study

Early Discharge of Infants and Risk of Readmission for Jaundice

Are pregnancy outcomes associated with risk factor reporting in routinely collected perinatal data?

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