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Establishing a composite neonatal adverse outcome indicator using English hospital administrative data
  1. Hannah Ellin Knight1,2,
  2. Sam J Oddie3,
  3. Katie L Harron4,
  4. Harriet K Aughey2,5,
  5. Jan H van der Meulen6,7,
  6. Ipek Gurol-Urganci1,
  7. David A Cromwell6,7
  1. 1 Health Services Research and Policy, London School of Hygiene & Tropical Medicine Faculty of Public Health and Policy, London, UK
  2. 2 Lindsay Stewart Centre for Audit and Clinical Informatics, Royal College of Obstetricians and Gynaecologists, London, UK
  3. 3 Bradford Neonatology, Bradford Royal Infirmary, West Yorkshire, UK
  4. 4 UCL Great Ormond Street Institute of Child Health, University College London, London, UK
  5. 5 University Hospitals Bristol NHS Foundation Trust, Bristol, UK
  6. 6 Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK
  7. 7 Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK
  1. Correspondence to Dr Hannah Ellin Knight, Health Services Research and Policy, London School of Hygiene and Tropical Medicine Faculty of Public Health and Policy, London WC1E 7HT, UK; hknight{at}


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.

  • neonatal morbidity
  • outcome measure
  • administrative data
  • international classification of diseases

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  • Contributors The study was conceived by HEK and DAC; HEK, DAC, IG-U, SJO and JHvdM agreed the study design and definitions; KLH prepared the data extract; HEK, DAC, SJO and HKA were involved in analysis; all authors contributed to writing the manuscript and reviewed the final version submitted.

  • Funding KH is funded by Wellcome Trust grant 103975/Z/14/Z.

  • Competing interests None declared.

  • Patient consent Not required.

  • Ethics approval The study is exempt from UK National Research Ethics Service approval because it involved the analysis of an existing dataset of anonymised data for service evaluation. Hospital Episode Statistics (HES) data were made available by National Health Service (NHS) Digital (Copyright 2015, reused with the permission of NHS Digital. All rights reserved). Approvals for the use of HES and Office for National Statistics (ONS) data were obtained as part of the standard NHS Digital data access process (NIC 383345).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement The data governance arrangements for the study do not allow us to redistribute HES data to other parties. Researchers interested in accessing HES data can apply for access through NHS Digital’s Data Access Request Service ( This study made use of pseudonymised HES extracts of infants born between April 2014 and March 2015, linked with the ONS death register.

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