Personal Chair
Telephone: (01792) 513404
Room: Cellular Office - 402
Fourth Floor
Data Science Building
Singleton Campus

David Ford is Professor of Health Informatics and leads the Health Informatics Group at College of Medicine in Swansea University, Wales, UK.

David is Director of the Administrative Data Research Centre (ADRC) Wales, an £8 million investment by the Economic and Social Research Council (ESRC) as part of its Big Data initiative and is Deputy Director of a the Centre for Improvement in Population Health through E-records Research (CIPHER), part of the Farr Institute of Health Informatics Research, funded by a consortium of top UK research funders led by the Medical Research Council (MRC).

David is also Director of the eHealth Industries Innovation (ehi2) Centre, developing links between academia, the NHS, and business within the UK and internationally. He is also University Director of NHS Wales Informatics Research Laboratories, created through a collaboration between the College of Medicine, Swansea University and NHS Wales Informatics Service, the national programme for NHS IT for Wales. The Research Laboratories provide state-of-the-art facilities to design, prototype, test and evaluate innovative new information technologies for use in improving health and healthcare.

David is joint lead of the Health Information Research Unit for Wales (HIRU), which develops new ways of harnessing the potential of routinely collected information collected in health and other settings. HIRU’s main product is the SAIL Databank, an internationally recognised data linkage resource formed from a wide variety of routinely collected data from across Wales.

David is a Fellow of the Royal Society for the Encouragement of the Arts, Manufactures and Commerce (FRSA) and past Chairman and a current Director of MediWales, a membership organisation representing the medical technology sector of Wales.

David is a member of numerous committees and national bodies relating to health informatics and health-related research. He has received research grants and consultancy contracts valuing over £35m over recent years.

Areas of Expertise

  • Health Informatics
  • eHealth
  • Health Services
  • Population Health
  • Data Protection and Privacy Protection
  • Big Data Analytics
  • Administrative Data


  1. & The Secure Anonymised Information Linkage (SAIL) system in Wales has privacy protection at its heart. BMJ 348(apr03 1), g2384-g2384.
  2. & (2017). The SAIL Databank: 10 years of spearheading data privacy and research utility, 2007-2017.
  3. & (2018). Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review (Preprint).
  4. & Toward an Ethically Founded Framework for the Use of Mobile Phone Call Detail Records in Health Research. JMIR mHealth and uHealth 7(3), e11969
  5. & Public Views on Using Mobile Phone Call Detail Records in Health Research: Qualitative Study. JMIR mHealth and uHealth 7(1), e11730
  6. & Population Data Science: Advancing the safe use of population data for public benefit. Epidemiology and Health 40, e2018061
  7. et. al. A Position Statement on Population Data Science: The Science of Data about People. International Journal of Population Data Science 3(1)
  8. & Towards an ethically-founded framework for the use of mobile phone CDRs in health research. International Journal of Population Data Science 3(4)
  9. & Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review. JMIR mHealth and uHealth 6(7), e161
  10. et. al. Validating the portal population of the United Kingdom Multiple Sclerosis Register. Multiple Sclerosis and Related Disorders 24, 3-10.
  11. & Reusable, set-based selection algorithm for matched control groups. International Journal for Population Data Science 1(1)
  12. & A UKSeRP for SAIL: striking a balance. International Journal of Population Data Science 1(1)
  13. & Clinical Validation of the UKMS Register Minimal Dataset utilising Natural Language Processing. International Journal for Population Data Science 1(1)
  14. & Obtaining structured clinical data from unstructured data using natural language processing software. International Journal for Population Data Science 1(1)
  15. & Thoughts and musings from the new International Population Data Linkage Network (IPDLN) Co-directors. International Journal for Population Data Science 1(1)
  16. & The other side of the coin: Harm due to the non-use of health-related data. International Journal of Medical Informatics 97, 43-51.
  17. & The UK Secure eResearch Platform for public health research: a case study. 388, S62
  18. & TIMELY SOCIAL CARE AND EMERGENCY HOSPITAL ADMISSIONS. Emergency Medicine Journal 33(9), 678-678.
  19. & How to refer to people with disease in research outputs: The disconnection between academic practise and that preferred by people with multiple sclerosis. 10, 127-133.
  20. & The Life Science Exchange: a case study of a sectoral and sub-sectoral knowledge exchange programme. 14(1)
  21. A national population-based e-cohort of people with psychosis (PsyCymru) linking prospectively ascertained phenotypically rich and genetic data to routinely collected records: Overview, recruitment and linkage. 166(1-3), 131-136.
  22. Suicide Information Database-Cymru: a protocol for a population-based, routinely collected data linkage study to explore risks and patterns of healthcare contact prior to suicide to identify opportunities for intervention. 4(11), e006780
  23. & A case study of the Secure Anonymous Information Linkage (SAIL) Gateway: A privacy-protecting remote access system for health-related research and evaluation. Journal of Biomedical Informatics 50, 196-204.
  24. & Involving consumers in the work of a data linkage research unit. International Journal of Consumer Studies, n/a-n/a.
  25. Identifying and Addressing the Barriers to the Use of an Internet-Register for Multiple Sclerosis. 8(1), 1-16.
  26. & How People with Multiple Sclerosis Rate Their Quality of Life: An EQ-5D Survey via the UK MS Register. PLoS ONE 8(6), e65640
  27. & Identifying and Addressing the Barriers to the Use of an Internet-Register for Multiple Sclerosis. International Journal of Healthcare Information Systems and Informatics 8(1), 1-16.
  28. & Desirability and expectations of the UK MS Register: Views of people with MS. International Journal of Medical Informatics 82(11), 1104-1110.
  29. Outcome measures for multiple sclerosis. Physical Therapy Reviews
  30. & The Physical and Psychological Impact of Multiple Sclerosis Using the MSIS-29 via the Web Portal of the UK MS Register. PLoS ONE 8(1), e55422
  31. & Commentary on 'Disability outcome measures in multiple sclerosis clinical trials'. Multiple Sclerosis Journal 18(12), 1718-1720.
  32. & The feasibility of collecting information from people with Multiple Sclerosis for the UK MS Register via a web portal: characterising a cohort of people with MS. BMC Medical Informatics and Decision Making 12(1), 73
  33. & A Large-Scale Study of Anxiety and Depression in People with Multiple Sclerosis: A Survey via the Web Portal of the UK MS Register. PLoS ONE 7(7), e41910
  34. & Sources of Discovery, Reasons for Registration, and Expectations of an Internet-Based Register for Multiple Sclerosis. International Journal of Healthcare Information Systems and Informatics 7(3), 27-43.
  35. et. al. Development and use of a privacy-protecting total population record linkage system to support observational, interventional, and policy relevant research. The Lancet 380, S6
  36. & Comment on: Polonsky et al. Structured Self-Monitoring of Blood Glucose Significantly Reduces A1C Levels in Poorly Controlled, Noninsulin-Treated Type 2 Diabetes: Results From the Structured Testing Program Study. Diabetes Care 2011;34:262-267. Diabetes Care 34(5), e57-e57.
  37. & Protocol for a population-based Ankylosing Spondylitis (PAS) cohort in Wales. BMC Musculoskeletal Disorders 11(1), 197
  38. & The prescribed duration algorithm: utilising ‘free text’ from multiple primary care electronic systems. Pharmacoepidemiology and Drug Safety 19(9), 983-989.
  39. & The SAIL Databank: building a national architecture for e-health research and evaluation. BMC Health Services Research 9(1), 157
  40. & The SAIL databank: linking multiple health and social care datasets. BMC Medical Informatics and Decision Making 9(1), 3
  41. & Effectiveness and cost-effectiveness of a stepped care intervention for alcohol use disorders in primary care: pilot study. The British Journal of Psychiatry 195(5), 448-456.
  42. & Residential Anonymous Linking Fields (RALFs): a novel information infrastructure to study the interaction between the environment and individuals' health. Journal of Public Health 31(4), 582-588.
  43. & Are blood pressure levels taken during a secondary care diabetic clinic likely to be higher than when measured in primary care?. Primary Care Diabetes 3(3), 193-195.
  44. & Use of a patient linked data warehouse to facilitate diabetes trial recruitment from primary care. Primary Care Diabetes 3(4), 245-248.


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