Iatrogenic and spontaneous preterm birth in England: A population-based cohort study.

OBJECTIVE: To describe the rates of and risk factors associated with iatrogenic and spontaneous preterm birth and the variation in rates between hospitals. DESIGN: Cohort study using electronic health records. SETTING: English National Health Service. POPULATION: Singleton births between 1 April 2015 and 31 March 2017. METHODS: Multivariable Poisson regression models were used to estimate adjusted risk ratios (adjRR) to measure association with maternal demographic and clinical risk factors. MAIN OUTCOME MEASURES: Preterm births (<37 weeks of gestation) were defined as iatrogenic or spontaneous according to mode of onset of labour. RESULTS: Of the births, 6.1% were preterm and of these, 52.8% were iatrogenic. The proportion of preterm births that were iatrogenic increased after 32 weeks. Both sub-groups were associated with previous preterm birth, extremes of maternal age, socio-economic deprivation and smoking. Iatrogenic preterm birth was associated with higher body mass index (BMI) (BMI >40 kg/m2 adjRR 1.59, 95% CI 1.50-1.69) and previous caesarean (adjRR 1.88, 95% CI 1.83-1.95). Spontaneous preterm birth was less common in women with a higher BMI (BMI >40 kg/m2 adjRR 0.77, 95% CI 0.70-0.84) and in women with a previous caesarean (adjRR 0.87, 95% CI 0.83-0.90). More variation between NHS hospital trusts was observed in rates of iatrogenic, compared with spontaneous, preterm births. CONCLUSIONS: Just over half of all preterm births resulted from iatrogenic intervention. Iatrogenic births have overlapping but different patterns of maternal demographic and clinical risk factors to spontaneous preterm births. Iatrogenic and spontaneous sub-groups should therefore be measured and monitored separately, as well as in aggregate, to facilitate different prevention strategies. This is feasible using routinely acquired hospital data.

Establishing a composite neonatal adverse outcome indicator using English hospital administrative data.

OBJECTIVE: We adapted a composite neonatal adverse outcome indicator (NAOI), originally derived in Australia, and assessed its feasibility and validity as an outcome indicator in English administrative hospital data. DESIGN: We used Hospital Episode Statistics (HES) data containing information infants born in the English National Health Service (NHS) between 1 April 2014 and 31 March 2015. The Australian NAOI was mapped to diagnoses and procedure codes used within HES and modified to reflect data quality and neonatal health concerns in England. To investigate the concurrent validity of the English NAOI (E-NAOI), rates of NAOI components were compared with population-based studies. To investigate the predictive validity of the E-NAOI, rates of readmission and death in the first year of life were calculated for infants with and without E-NAOI components. RESULTS: The analysis included 484 007 (81%) of the 600 963 eligible babies born during the timeframe. 114/148 NHS trusts passed data quality checks and were included in the analysis. The modified E-NAOI included 23 components (16 diagnoses and 7 procedures). Among liveborn infants, 5.4% had at least one E-NAOI component recorded before discharge. Among newborns discharged alive, the E-NAOI was associated with a significantly higher risk of death (0.81% vs 0.05%; p<0.001) and overnight hospital readmission (15.7% vs 7.1%; p<0.001) in the first year of life. CONCLUSIONS: A composite NAOI can be derived from English hospital administrative data. This E-NAOI demonstrates good concurrent and predictive validity in the first year of life. It is a cost-effective way to monitor neonatal outcomes.