Improving UK data on avoidable perinatal brain injury: review of data dictionaries and consultation

Wu, Y. W., Croen, L. A., Shah, S. J., Newman, T. B. & Najjar, D. V. Cerebral Palsy in a Term Population: Risk Factors and Neuroimaging Findings. Pediatrics 118, 690–697 (2006).

Article  PubMed  Google Scholar 

Liu, L. et al. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet 388, 3027–3035 (2016).

Article  PubMed  PubMed Central  Google Scholar 

Ockenden, D. Findings, conclusions and essential actions from the independent review of maternity services at The Shrewsbuty and Telford Hospital NHS Trust (APS Group on behalf of the Controller of Her Majesty’s Stationery Office, 2022).

Eunson, P. The long-term health, social, and financial burden of hypoxic-ischaemic encephalopathy. Dev. Med Child Neurol. 57, 48–50 (2015).

Article  PubMed  Google Scholar 

NHS Resolution. Five years of Cerebral Palsy claims. A thematic review of NHS Resolution data (NHS Resolution, 2017).

Royal College of Obstetricians and Gynaecologists. Each Baby Counts: 2020 Final Progress Report (RCOG, 2021).

Gale, C., Statnikov, Y., Jawad, S., Uthaya, S. N. & Modi, N. Neonatal brain injuries in England: population-based incidence derived from routinely recorded clinical data held in the National Neonatal Research Database. Arch. Dis. Child. Fetal Neonatal Ed. 103, F301–f6 (2018).

Article  PubMed  Google Scholar 

Molloy, E. J. et al. Neonatal encephalopathy and hypoxic-ischemic encephalopathy: moving from controversy to consensus definitions and subclassification. Pediatr. Res. 94, 1860–1863 (2023).

Article  PubMed  Google Scholar 

Branagan, A., et al. Consensus definition and diagnostic criteria for neonatal encephalopathy-study protocol for a real-time modified delphi study. Pediatr Res. https://doi.org/10.1038/s41390-024-03303-3 (2024). Online ahead of print.

Endrich, O. et al. Asphyxia in the Newborn: Evaluating the Accuracy of ICD Coding, Clinical Diagnosis and Reimbursement: Observational Study at a Swiss Tertiary Care Center on Routinely Collected Health Data from 2012-2015. PLoS One 12, e0170691 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Martinez-Biarge, M., Diez-Sebastian, J., Wusthoff, C. J., Mercuri, E. & Cowan, F. M. Antepartum and intrapartum factors preceding neonatal hypoxic-ischemic encephalopathy. Pediatrics 132, e952–e959 (2013).

Article  PubMed  Google Scholar 

Cowan, F. et al. Origin and timing of brain lesions in term infants with neonatal encephalopathy. Lancet 361, 736–742 (2003).

Article  PubMed  Google Scholar 

Graham, E. M., Ruis, K. A., Hartman, A. L., Northington, F. J. & Fox, H. E. A systematic review of the role of intrapartum hypoxia-ischemia in the causation of neonatal encephalopathy. Am. J. Obstet. Gynecol. 199, 587–595 (2008).

Article  CAS  PubMed  Google Scholar 

Kurinczuk, J. J., White-Koning, M. & Badawi, N. Epidemiology of neonatal encephalopathy and hypoxic-ischaemic encephalopathy. Early Hum. Dev. 86, 329–338 (2010).

Article  PubMed  Google Scholar 

Shipley, L., Gale, C. & Sharkey, D. Trends in the incidence and management of hypoxic-ischaemic encephalopathy in the therapeutic hypothermia era: a national population study. Arch. Dis. Child. Fetal Neonatal Ed. 106, 529–534 (2021).

Article  PubMed  Google Scholar 

Black, N. & Tan, S. Use of national clinical databases for informing and for evaluating health care policies. Health Policy 109, 131–136 (2013).

Article  PubMed  Google Scholar 

Stewart, K., Bray, B. & Buckingham, R. Improving quality of care through national clinical audit. Future Hospital. Journal 3, 203–206 (2016).

Google Scholar 

Dixon-Woods, M., Campbell, A., Aveling, E.-L. & Martin, G. An ethnographic study of improving data collection and completeness in large-scale data exercises. Wellcome Open. Research 4, 203 (2019).

Google Scholar 

Gale, C. & Morris, I. The UK National Neonatal Research Database: using neonatal data for research, quality improvement and more. Arch. Dis. Child Educ. Pr. Ed. 101, 216–218 (2016).

Article  CAS  Google Scholar 

National Maternity and Perinatal Audit (NMPA). National Maternity and Perinatal Audit. Clinical report 2017 - revised version. Based on births in NHS maternity services between 1st April 2015 and 31st March 2016. Available at: https://maternityaudit.org.uk/FilesUploaded/NMPA%20Clinical%20Report%202018.pdf (2017).

Collins, K. J. & Draycott, T. Measuring quality of maternity care. Best. Pract. Res. Clin. Obstet. Gynaecol. 29, 1132–1138 (2015).

Article  PubMed  Google Scholar 

Mohammad, K. et al. Consensus Approach for Standardizing the Screening and Classification of Preterm Brain Injury Diagnosed With Cranial Ultrasound: A Canadian Perspective. Front. Pediatr. 9, 618236 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Gupta, M. & Kaplan, H. C. Measurement for quality improvement: using data to drive change. J. Perinatol. 40, 962–971 (2020).

Article  PubMed  Google Scholar 

Shah, P. S. et al. The International Network for Evaluating Outcomes (iNeo) of neonates: evolution, progress and opportunities. Transl. Pediatr. 8, 170–181 (2019).

Article  PubMed  PubMed Central  Google Scholar 

Norman, M., Källén, K., Wahlström, E. & Håkansson, S. The Swedish Neonatal Quality Register - contents, completeness and validity. Acta Paediatr. 108, 1411–1418 (2019).

Article  PubMed  Google Scholar 

Lammons, W. B., et al. Involving multiple stakeholders in assessing and reviewing a novel data visualisation tool for a national neonatal data asset. BMJ Health Care Inform. 30, e100694 (2023).

Lee, S. K. et al. Outcomes and care practices for preterm infants born at less than 33 weeks’ gestation: a quality-improvement study. Cmaj 192, E81–e91 (2020).

Article  PubMed  PubMed Central  Google Scholar 

NHS Digital. Maternity Services Data Set. Available at: https://digital.nhs.uk/data-and-information/data-collections-and-data-sets/data-sets/maternity-services-data-set (2022).

NHS Digital. Hospital Episode Statistics (HES). Available from: https://digital.nhs.uk/data-and-information/data-tools-and-services/data-services/hospital-episode-statistics (2022).

Aughey, H., NMPA project team. Technical Report: Linking the National Maternity and Perinatal Audit Data Set to the National Neonatal Research Database for 2015/16; Available from: https://maternityaudit.org.uk/FilesUploaded/NMPA%20Neonatal%20sprint%20report.pdf (2019).

NHS Digital. NHS Maternity Statistics, England - 2020-21: MSDS Data Quality. Available at: https://digital.nhs.uk/data-and-information/publications/statistical/nhs-maternity-statistics/2020-21/ (2021).

Chen, A. et al. The acceptability of implementing patient‐reported measures in routine maternity care: A systematic review. Acta Obstetricia Gynecologica Scand. 102, 406–419 (2023).

Article  Google Scholar 

Craig, A. K., Munoz-Blanco, S., Pilon, B. & Lemmon, M. Communicating with Parents About Therapeutic Hypothermia and Hypoxic Ischemic Encephalopathy: Integrating a Palliative Care Approach into Practice. Clin. Perinatol. 51, 711–724 (2024).

Article  PubMed  Google Scholar 

Shah, P. S. et al. Sustained quality improvement in outcomes of preterm neonates with a gestational age less than 29 weeks: results from the Evidence-based Practice for Improving Quality Phase 3 (1). Can. J. Physiol. Pharmacol. 97, 213–221 (2019).

Article  CAS  PubMed  Google Scholar 

Delnord, M. et al. Linking databases on perinatal health: a review of the literature and current practices in Europe. Eur. J. Public Health 26, 422–430 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Johansen, L. T., Braut, G. S., Acharya, G., Andresen, J. F. & Øian, P. Adverse events reporting by obstetric units in Norway as part of their quality assurance and patient safety work: an analysis of practice. BMC Health Serv. Res. 21, 931 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Helps, A., Leitao, S., Greene, R. & O’Donoghue, K. Perinatal mortality audits and reviews: Past, present and the way forward. Eur. J. Obstet. Gynecol. Reprod. Biol. 250, 24–30 (2020).

Article  PubMed  Google Scholar 

Shah, P. S., et al. International network for evaluating outcomes of neonates: outputs and future directions. Pediatr. Med. 5, 40 (2022).

Westergren, H., Marell Hesla, H., Altman, M. & Wickström, R. Validation of central nervous system-induced seizures and other neurological variables in the Swedish Neonatal Quality Register. Acta Paediatr. 111, 1331–1337 (2022).

Article  PubMed  PubMed Central  Google Scholar 

NHS Data Model and Dictionary. Maternity Services Data Set. Available at: https://www.datadictionary.nhs.uk/data_sets/clinical_data_sets/maternity_services_data_set.html?hl=maternity%2Cservices%2Cdata%2Cset (2023).

NHS Data Model and Dictionary. Hospital Episode Statistics. Available at: https://www.datadictionary.nhs.uk/supporting_information/hospital_episode_statistics.html (2023).

NHS Digital. The processing cycle and HES data quality. Available at: https://digital.nhs.uk/data-and-information/data-tools-and-services/data-services/hospital-episode-statistics/the-processing-cycle-and-hes-data-quality (2023).

NHS Data Model and Dictionary. National Neonatal Data Set - Episodic and Daily Care. Available at: https://www.datadictionary.nhs.uk/data_sets/clinical_data_sets/national_neonatal_data_set/national_neonatal_data_set_-_episodic_and_daily_care.html?hl=neonatal (2023).

Imperial College London. Neonatal Medicine Research Group. Available at: https://www.imperial.ac.uk/neonatal-data-analysis-unit/ (2023).

National Maternity and Perinatal Audit (NMPA). About the NMPA. Available at: https://maternityaudit.org.uk/pages/aboutnmpa (2023).

Kwok, T. C. & Battersby, C. Using data to improve UK neonatal care: past, present and future. Infant. 19, 54–59 (2022).

Royal College of Paediatrics and Child Health (RCPCH). National Neonatal Audit Programme. Available at: https://www.rcpch.ac.uk/work-we-do/clinical-audits/nnap (2021).

Linnarsson, R. & Wigertz, O. The data dictionary-a controlled vocabulary for integrating clinical databases and medical knowledge bases. Methods Inf. Med. 28, 78–85 (1989).

留言 (0)

沒有登入
gif