Use of SAIL in multi-sectoral public health evaluation

Use of SAIL in multi-sectoral public health evaluation in Wales Professor Ronan Lyons

Secure Anonymised Information Linkage (SAIL) § Component of the strategic research infrastructure for the UK § Created from a partnership between: § Health Information Research Unit (Swansea Uni) § NHS Wales Informatics Service § Multiple public bodies § Core funding from NISCHR and Swansea University; rest from multiinstitutional grants § Many studies involve staff from Public Health Wales, local authorities or third sector bodies with academics from Welsh universities § Supporting grant income > £ 40 M since 2006

Challenges and solutions in public health evaluation

Many levers to improve health are outside the NHS • Education, employment, design of the built environment, transport, …. • Joined up government requires policy appraisal and evaluative research , e. g. health and social benefits of: • Improving educational achievement • Housing insulation • Urban designs supporting physical activity through walking and cycling • Providing safe and exciting play areas for children…

Mismatch of information and skills • Information for evaluation is fragmented – Exposures (Local Gov, …. – Interventions (Local Gov, 3 rd sector, emerg. services …. – Health outcomes (NHS) • Data sharing is very difficult at micro level needed • Skills are compartmentalised – Evaluation (academia, public health services, . . )

Past and Present/Future Public Health Academia: DECIPHer Epi-Screen CIPHER Local Government Questions NHS Public Health Wales and NHS organisations Academia Local Government 3 rd Sector

SAIL provides a solution Access to a multi-sourced data bank of linkable anonymised data on population of Wales drawn from: – health services – education, housing, social care, etc. The SAIL Gateway is a remote access analysis facility to data: uses world leading privacy protection technologies – still allows longitudinal analysis at anonymised individual and household level –

Patient Journey Analysis- Health and Social Care

Types of research supported by SAIL 1. Health Services Research 2. Epidemiology 3. Trials and evaluations of natural experiments 4. Policy development and evaluation of initiatives

Examples of SAIL supported studies • Wales Electronic Cohort for Children (WECC) • Carmarthenshire Housing Regeneration and Health Study • CHange in ALcohol outlet dens. Ity and al. Cohol-related harm to population h. Ealth (CHALICE) • Centre for the Improvement of Population Health through E-health Research (CIPHER)

WECC: relationship between pregnancy, birth, and childhood influences on educational attainment Factor Percentage increased likelihood of underachievement in Key Stage 1 – age 7 Prematurity < 28 weeks + 50% Prematurity 33 -36 weeks + 30% Frequent house moves + 79% Head injury admission + 46% Social deprivation + 160%

Injury Hospital Admissions Age 1 - < 5 years Incidence Ratios and 95% CI by House Moves for WECC 1999 -2008 (n=255, 733) Negative Binomial Incidence Ratio 2. 0 1. 5 1. 0 0. 5 0. 0 1 2 Frequency of moving house Age 0 - < 1 year Adjusted for: Denominator: CI: 3+ F Gender 2 3 4 Child Characteristics 5 6 7 8 9 10 Townsend Decile of LSOA at birth/first 4 months Gender, Parity, Gestation at birth, Maternal age at birth, Maternal smoking, Maternal breastfeeding, Townsend Decile of LSOA at birth/ first 4 months. Born in Wales, Year of birth 1999 -2008, No major congenital anomaly, No move out/ died/ end of WECC before age 1 year old. Confidence Interval

Housing Regeneration and Health Study • Collaboration with Carmarthenshire County Council • Bringing 9, 256 social homes to modern quality standards - £ 207 M • internal works: kitchen units, bathroom suites, downstairs toilets, central heating, rewiring • windows and doors: double-glazed, locks • thermal insulation: walls and loft • gardens and estate package: fencing, security lights, paths in good condition • Using SAIL to evaluate and quantify the health benefits of housing improvement to 2016

CHALICE • Another NIHR funded study – Cardiff/Swansea colaboration led by David Fone • Evaluating changes in exposure to alcohol outlet density on alcohol consumption and measures of alcohol related harm. • Uses multiple GIS approaches and data from: • • Welsh Health Survey: 75, 000 participants (2005 -9) Hospital admissions ED attendances Alcohol related violent crime

CIPHER MRC call for 4 UK Centres of Excellence • CIPHER is: – International (Australian, Canadian and English and Welsh universities) – led from Wales (Swansea, Cardiff, PHW, 1000 lives+, and WG) – Focussed on using existing data to move quickly from observation to intervention to measuring population impact • 4 work programmes: – Methodological innovation – Injury, the build environment and health • Evaluation of impact of Care and Repair interventions – Determinants of psychological and social well-being – Population aspects of infection

Evaluating obesity prevention initiatives Is childhood obesity a priority issue? • Evaluating interventions means actually measuring outcomes • In Wales, we measure height and weight at: – Birth – School entry (age 4) – ? Not at age 9 • So, we can evaluate pre-school interventions but probably not school based/age interventions • Deduction: we are not serious about this issue

Lessons in success 1. Collaborate – across sectors and institutions 2. Make high quality evaluation possible: a) Capture identities of all individuals and services receiving/giving interventions (especially if innovative) b) Insist on interventions being randomised by time or by topic 3. Work with academia and Public Health Wales to: a) Maximise integration of existing un-captured data in SAIL b) Acquire designated analytical and epidemiological support c) Support bids for high quality evaluations

Funder acknowledgment

Acknowledgments: SAILors • Swansea University: David Ford, Kerina Jones, Mark Atkinson, Muhammad Rahman, Shangming Zhou, Samantha Turner, Sarah Rodgers, , Hayley Hutchings, Roxanne Cooksey, Sue Jordan, Sinead Brophy, Keith Lloyd, Ann john, Mick Dennis, John Williams, Stefan Siebert, Rohan D’Silva, Simon Thompson, Chris Jones, Ryan Lever, Michaela Barbu, Olly Littleton, Rod Middleton, Richard Fry, Caroline Brooks, Martin Heaven, Steven Macey, Joanne Demmler, Angharad Walters, Melanie Hyatt, Cynthia Mc. Nerney, Mike Gravenor and Richard Charlton • Cardiff University: David Fone, Frank Dunstan, Shantini Paranjothy, Annette Evans, Mark Kelly, John Watkins, John Gallacher, Laurence Moore, Stephen Palmer, Hilary Fielder, Chris Butler, Wouter Poortinga, Robert Smith, Simon Lannon, Chris Webster, Shin Lee, Narushige Shiode, Scott Orford, and Vaseekram Sivarajasingam • Bangor University: Richard Neal, Claire Wilkinson, Nefyn Williams • NHS Wales Informatics Service: Gareth John, Ken Leake, Katy Wilson, Louise Richards and Rhys Woodhead • All data providers and Public Health Wales staff too numerous to list

Selected publications • Lyons RA, Jones KH, John G, Brooks CJ, Verplancke JP, Ford DV, Brown G, Leake K. The SAIL databank: linking multiple health and social care datasets. BMC Med Inform Decis Mak. 2009 Jan 16; 9: 3. http: //www. biomedcentral. com/1472 -6947/9/3 • Ford DV, Jones KH, Verplancke JP, Lyons RA, John G, Brown G, Brooks CJ, Thompson S, Bodger O, Couch T, Leake K. The SAIL Databank: building a national architecture for e-health research and evaluation. BMC Health Services Research 2009; 9: 157 doi: 10. 1186/1472 -6963 -9 -157. http: //www. biomedcentral. com/1472 -6963/9/157 • Rodgers SE, Lyons RA, Dsilva R, Jones KH, Brooks CJ, Ford DV, John G, Verplancke JP. Residential Anonymous Linking Fields (RALFs): A Novel Information Infrastructure to Study the Interaction between the Environment and Individuals’ Health. J Public Health 2009 Dec; 31(4): 582 -8. Epub 2009 May 15. (doi: 10. 1093/pubmed/fdp 041). • Brooks CJ, Stephens JW, Price DE, Ford DV, Lyons RA, Prior SL, Bain SC. Use of a patient linked data warehouse to facilitate diabetes trial recruitment from primary care. Primary Care Diabetes 2009 online publication http: //dx. doi. org/10. 1016/j. pcd. 2009. 06. 004 • Snooks S, Cheung W-Y, Close J, Dale J, Gaze S, Humphreys I, Lyons R, Mason S, Merali Y, Peconi J, Phillips C, Phillips J, Roberts S, Russell I, Sánchez A, Wani M, Wells B, Whitfield R. Support and Assessment for Fall Emergency Referrals (SAFER 1) trial protocol. Computerised on-scene decision support for emergency ambulance staff to assess and plan care for older people who have fallen: evaluation of costs and benefits using pragmatic cluster randomised trial. BMC Emergency Medicine 2010; 10: 2. doi: 10. 1186/1471 -227 X-10 -2. http: //www. biomedcentral. com/1471 -227 X/10/2 • Mcgregor J, Brooks C, Chalasani P, Chukwuma J, Hutchings H, Lyons RA, Lloyd K. The Health Informatics Trial Enhancement Project (HITE): Using routinely collected primary care data to identify potential participants for a depression trial. Trials 2010, 11: 39. doi: 10. 1186/1745 -6215 -11 -39 http: //www. trialsjournal. com/content/11/1/39 • Brophy S, Cooksey R, Gravenor MB, Weston C, Macey SM, John G, Williams R, Lyons RA. Population based absolute and relative survival to 1 year of people with diabetes following a myocardial infarction: A cohort study using hospital admissions data. BMC Public Health 2010; 10: 338. http: //www. ncbi. nlm. nih. gov/pmc/articles/PMC 2894776/? tool=pubmed • Rodgers SE, Demmler JC, D’Silva R, Lyons RA. Protecting health data privacy while using residence-based environment and demographic data. Health & Place 2011; 18: 209 -217. doi: 10. 1016/j. healthplace. 2011. 09. 006 • Atkinson MD, Brophy S, Siebert S, Gravenor MB, Phillips CJ, Ford DV, Jones KH, Lyons RA. Protocol for a population-based Ankylosing Spondylitis (PAS) cohort in Wales. BMC Musculoskeletal Disorders 2010, 11: 197 http: //www. biomedcentral. com/1471 -2474/11/197