Care of extremely premature babies in England, 1995 – Present Andrei Scott Morgan Department of Neonatology Institute for Women’s Health University College London A thesis submitted for the degree of Doctor of Philosophy (PhD) June 2015 I, Andrei Scott Morgan, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Signed: Date: 17 July 2015 Supervisors NeilMarlow ElizabethS.Draper Professor of Neonatology Professor of Perinatal and Paediatric Epidemiology Department of Neonatology Department of Health Sciences Institute for Women’s Health University of Leicester University College London c Andrei Morgan 2015 This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/. 3 Abstract This thesis, arising from the EPICure studies into extremely preterm births, seeks to explain demographic, clinical and organisational factors associated with a large increase in admissions to neonatal intensive care. Using six pre-existing data sets, along with a repeat Unit Profile Study of English perinatal centres conducted in 2011 as part of this thesis, three studies were performed: Validation of the 44% increase in the number of admissions to neonatal intensive • care at 22–25 weeks gestation seen between 1995 and 2006 in England was at- tempted using three methods of probabilistic record linkage with Hospital Episode Statistics (HES) data. The effects of antenatal steroid administration, tocolysis and Caesarean delivery • on perinatal outcomes in the extremely preterm population were investigated. Changes in organisational characteristics – staffing and “activity” (expressed as • throughput and intensity) – that have occurred in England were examined using data from three time points. An increase was seen in the number of extremely premature babies in HES data. Link- age with EPICure data demonstrated that routine data are insufficiently precise for use in epidemiological investigations at the margins of viability. Tocolysis was associated with improved outcomes. Antenatal steroids were associated with improved outcomes at birth following vaginal delivery. No effect was demonstrated for Caesarean deliv- ery on birth outcomes but there was evidence of case selection at gestations below 26 weeks. Organisational data (from 1997, 2006 and 2011) demonstrated reduced num- bers of cots between 1997 and 2011 with increases in both throughput and intensity of workload. Staffing levels increased, but still failed to meet recommended standards. Current knowledge of extremely low gestational age births is inadequate for national policy or health care reorganisation. Suggestions were made for how knowledge could be improved. To Sylvia O. Who gave to me my love of maths and people . Acknowledgements I’d first like to say a huge thanks to my supervisors – Neil Marlow (Professor of Neonatology, Institute for Women’s Health, UCL) and Liz Draper (Professor of Peri- natal Epidemiology, University of Leicester) – who not only helped plan this research project, but provided much valuable guidance and support throughout the time I have been working on it. I’m also very grateful to the other members of the EPICure Re- search Group: Professor Kate Costeloe and Ms Enid Hennessy, without whom I would not have been able to understand the data in the way that I do. Thank you, too, to Dr. Laura McCormack for the help with coordinating the Unit Profile Study. There are many people who provided me with help and support along the way. I’d particularly like to give my thanks to those who expressed their faith in me over the last few years: Dan Arthur, Pat Doyle, Phil Edwards, Branwen Hennig, Craig Higgins, Emma Nabavian and Kate Walker of the London School of Hygiene and Trop- ical Medicine; and Angela Huertas-Ceballos of University College London Hospitals NHS Foundation Trust. Also, the many colleagues I have shared desks or working ar- rangements with – Tauseef Khan, Shahrul Kamaruzzaman, Amira Shaheen, Eleonora Staines-Urias, Snehal Pinto Pereira, James Woodcock, Beth Howden, Giles Kendall, Cally Tann, Cristina Uria-Avellano and Kate Bennett. To my many friends, who offered me routes of escape and wonderful meals when the pressures and writing all became too much: without you, I would never have survived! To each and every one of you, big hugs: Rob and Jenny Hunningher, Ben McAlister, Helen Dale, Dave Hrycyszyn, Pennie Quinton, William Lee, Emily Dook, Christopher Grollman, Catriona Towriss and Sam Moon. To the people who read through my thesis – Katie Harron, Chris, Helen, Cat and my mother: you now have an insight into how my head works. Thank you all for your time and constructive criticism. Thanks, too, to the inspirations for my clinical and epidemiological career - Henry Kahn and Mickey Gillmor, Robert and Marilyn Kessler. Finally, to my family: I could not have done this without you – you have my thanks and my love. Contents List of Figures 19 List of Tables 21 I Background information 25 1 Introduction 27 1.1 Thesisoverview................................ 28 2 Organisation of neonatal care 29 2.1 Definitions................................... 29 2.2 NeonatalcareinEnglandintheNineties. 32 2.2.1 Organisationofneonatalcare . 33 2.2.2 UKNeonatalStaffingStudy(UKNSS) . 34 2.2.3 Transportservices . 37 2.2.4 Medicaladvances........................... 38 2.3 Investigatingextremeprematurity . 42 2.3.1 TheEPICurestudy ......................... 43 2.3.2 TheEuropeancontext . 46 2.4 Reorganisationintonetworks . 48 2.4.1 Evidenceforchange . .. .. .. .. .. .. 48 2.4.2 Contemporaryevidence . 50 2.4.3 Implementation of managed care networks . 52 2.5 EPICure2................................... 52 2.5.1 Comparisons with the first EPICure study. 54 11 CONTENTS 2.5.2 Unitleveleffects ........................... 55 2.6 “Modern”neonatology............................ 56 2.6.1 Updated evidence for regionalisation . 56 2.6.2 Contemporarystudies . 61 2.6.3 Ethicalguidelines. 62 2.6.4 Bigdata................................ 64 2.7 NeonatalhealthcaredatainEngland . 65 2.7.1 Birthanddeathregistrationdata. 67 2.7.2 HospitalEpisodeStatistics . 67 2.7.3 Otherdatasources .......................... 68 2.7.4 Combiningdatasources . 69 2.8 Datalinkage.................................. 72 2.8.1 Deterministiclinkage. 73 2.8.2 Probabilisticlinkage . 73 2.8.3 Linkageissues............................. 74 2.9 Statistical and epidemiological considerations . .......... 76 2.9.1 Confounding ............................. 77 2.9.2 Chance ................................ 78 2.9.3 Bias .................................. 79 2.10 Workloadassessment. 81 2.10.1 Staffing ................................ 82 2.10.2 Activity ................................ 84 2.11Summary ................................... 85 3 Aims 87 3.1 Validation of the EPICure data sets using routinely collected Hospital EpisodeStatistics. .............................. 87 3.2 Identification of obstetric antecedents of extreme prematurity. 88 3.3 Organisational changes in neonatal care in England . ........ 88 4 Methodsoverview:theavailabledata 89 4.1 ThefirstEPICurestudy–1995. 90 4.2 EPICure2–2006............................... 92 4.3 UnitProfileStudy–2006 .......................... 93 12 CONTENTS 4.4 UKNeonatalStaffingStudy–1997. 95 4.5 UnitProfileStudy2011 ........................... 96 4.5.1 Preparingthequestionnaire . 96 4.5.2 Hospitalssurveyed . 99 4.5.3 Datamanagement . 100 4.5.4 Ensuringdataaccuracy . 101 4.6 HospitalEpisodeStatistics . 106 4.6.1 Datapermissions . 106 4.6.2 InitialmanagementoftheHESdata . 107 4.7 Statisticalanalyses . 108 4.8 Governance .................................. 109 4.8.1 Ethicalconsiderations . 109 4.8.2 Datasecurity ............................. 110 4.8.3 Funding ................................ 111 4.9 Summaryofdatasetsandcommonmethods . 111 II Admissions Validation Study 113 5 Data Linkage 115 5.1 Studycontext................................. 115 5.2 Deterministiclinkage. 118 5.3 Probabilisticlinkage . 120 5.3.1 Data availability and choice of variables . 120 5.3.2 Blockingvariables . 124 5.3.3 Linkagecriteria. 125 5.3.4 Missing data and sensitivity analyses . 128 5.3.5 Thresholds .............................. 128 5.3.6 Clericalreview ............................ 128 5.4 Errormeasures ................................ 129 5.5 Summaryoflinkagemethods . 130 13 CONTENTS 6 Linkage Results 133 6.1 Availabledata ................................ 133 6.1.1 EPICure................................ 133 6.1.2 HospitalEpisodeStatistics(HES) . 134 6.2 Dataquality.................................. 135 6.2.1 Linkagevariables . 135 6.2.2 Dataconsistency . 139 6.3 Maincomparisons .............................. 139 6.3.1 Baselineestimatedvalues . 142 6.3.2 Dattaniestimates. 142 6.3.3 Contieroalgorithm . 146 6.3.4 Estimation-Maximisation likelihood algorithm . ....... 150 6.4 Manualreviewoflinkedpairs . 158 6.5 Assessmentoferror.............................. 159 6.6 DeterministiclinkagebytheNHSHSCIC . 159 6.7 SavedHESdata ............................... 160 6.8 Answeringtheoriginalquestion . 161 6.9 Datadestruction ............................... 162 6.10 Chaptersummary .............................. 162 7 Discussion of data linkage exercise 165 7.1 Keyresults .................................. 165 7.2 Limitations .................................. 166 7.2.1 Data.................................. 166 7.2.2 Methods...............................