Dr Kerina Jones
Associate Professor
Swansea University Medical School
Telephone: (01792) 602764
Room: Cellular Office - 305
Third Floor
Data Science Building
Singleton Campus

Kerina Jones is an Associate Professor of Health Informatics at the College of Medicine. She is part of the senior management team of the Secure Anonymised Information Linkage (SAIL) system, and leads the Governance initiatives to ensure data protection and to maximise data utility. She has led the development of successful bids to extend the SAIL system and to secure research grants. She is a co-investigator on the centre grant for CIPHER: the Centre for the Improvement of Population Health through Erecords Research, and leads the Innovative Governance workstream for the Farr Institute of Health Informatics Research. She is a co-investigator on the centre grant for CADRE: the Centre for Administrative Data Research & Evaluation, one of four Administrative Data Research Centres (ADRCs) in the UK. Within this she holds the position of Associate Director for Data and Methodologies. She also leads the Public Involvement and Engagement in data linkage research workstream for SAIL, CIPHER and CADRE. As part of this work, she established an active Consumer Panel for data linkage research.

Kerina is engaged in many projects that bring together disparate sources of data to enhance research and enable new types of studies to be conducted, and has a keen interest in the development of innovative disease registers. She leads the flagship UK Multiple Sclerosis Register, the data model for which brings together clinical data, routinely-collected data and a wealth of patient-reported data to create new knowledge about MS. With an academic background in Biochemistry, she is also particularly interested in projects where laboratory data can be linked to routinely collected health related records to create rich datasets for research. She is actively publishing research and methodology articles.

Areas of Expertise

  • Data linkage: research
  • Data linkage: methodologies and governance
  • Information governance for data-intensive research

Publications

  1. & Consensus Statement on Public Involvement and Engagement with Data Intensive Health Research. International Journal of Population Data Science
  2. Metabolism of p-cresol by the fungus Aspergillus fumigatus.
  3. & Diketocamphane enantiomer-specific "Baeyer-Villiger" monooxygenases from camphor-grown Pseudomonas putida ATCC 17453. Journal of General Microbiology 139(4), 797-805.
  4. 4-Ethylphenol metabolism by Aspergillus fumigatus.
  5. & Evidence of two pathways for the metabolism of phenol by Aspergillus fumigatus. Archives of Microbiology 163(3), 176-181.
  6. & Evidence of two pathways for the metabolism of phenol by Aspergillus fumigatus. Archives of Microbiology 163(3), 176-181.
  7. & Evidence of two pathways for the metabolism of phenol by Aspergillus fumigatus. Archives of Microbiology 163(3), 176-181.
  8. Urban legend versus rural reality: patients' experience of attendance at accident and emergency departments in west Wales. Emergency Medicine Journal 22(3), 165-170.
  9. A 3-dimensional balanced scorecard model for R&D. British Journal of Healthcare Management 13(1), 19-22.
  10. & The Secure Anonymised Information Linkage (SAIL) system in Wales has privacy protection at its heart. BMJ 348(apr03 1), g2384-g2384.
  11. & On moving targets and magic bullets: Can the UK lead the way with responsible data linkage for health research?. International Journal of Medical Informatics 84(11), 933-940.
  12. & A UKSeRP for SAIL: striking a balance. International Journal for Population Data Science 1(1)
  13. & (2018). Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review (Preprint).
  14. & (2018). Towards an ethically-founded framework for the use of mobile phone CDRs in health research (Preprint).
  15. & Challenges and Potential Opportunities of Mobile Phone Call Detail Records in Health Research: Review. JMIR mHealth and uHealth 6(7), e161
  16. et. al. Validating the portal population of the United Kingdom Multiple Sclerosis Register. Multiple Sclerosis and Related Disorders 24, 3-10.
  17. & Assessing the medium-term impact of a home-visiting programme on child maltreatment in England: protocol for a routine data linkage study. BMJ Open 7(7), e015728
  18. & The other side of the coin: harm due to the non-use of health-related data. International Journal for Population Data Science 1(1)
  19. & Data safe havens to combine health and genomic data: benefits and challenges. International Journal for Population Data Science 1(1)
  20. & Data Safe Havens and Trust: Toward a Common Understanding of Trusted Research Platforms for Governing Secure and Ethical Health Research. JMIR Medical Informatics 4(2), e22
  21. & The UK Secure eResearch Platform for public health research: a case study. The Lancet 388, S62
  22. & Dangers from Within? Looking Inwards at the Role of Maladministration as the Leading Cause of Health Data Breaches in the UK. In Data Protection and Privacy: (In)visibilities and Infrastructures. -239). Springer.
  23. & Physical Disability, Anxiety and Depression in People with MS: An Internet-Based Survey via the UK MS Register. PLoS ONE 9(8), e104604
  24. & The other side of the coin: Harm due to the non-use of health-related data. 97, 43-51.
  25. & (2014). A review of evidence relating to harm resulting from uses of health and biomedical data. A report to the Nuffield Council on Bioethics working party on biological and health data, and the Wellcome Trust’s expert advisory group on data access.
  26. & Factors associated with low fitness in adolescents – A mixed methods study. BMC Public Health 14(1), 764
  27. & Local modelling techniques for assessing micro-level impacts of risk factors in epidemiological data: Understanding health and socioeconomic inequalities in childhood educational attainments. PLoS One

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Teaching

  • PM-348 Data to Decisions

    The module gives students an understanding, not only of the importance of using data, but of doing so safely and effectively to inform decision-making for population health and well-being. It covers five staged themes (forming a repeating cycle) and one cross-cutting theme: Stages: 1. Data provenance and collection 2. Data sharing platforms, formats and management 3. Data-intensive research 4. Evidence-based policy and practice development 5. The application of data in decision-making, which loops back to point 1. Cross-cutting theme: 6. Data in context This cross-cutting theme covers data governance, and the legal, ethical and societal (ELSI) issues in the safe use of person-based data for research, development and evaluation initiatives leading to evidence-based decisions. As well as the benefits of data use, it brings in harm that occurs when data are misused, and the harm that occurs to individuals and burdens to society when data cannot be used effectively. This module introduces students to the fundamental concepts, theories and applications of data use within a population health context. It explores the practical issues of dealing with large amounts of routinely collected health data, and the ways these data can be used to in evidence-based medicine. Topics will cover data linkage, data analytics, data governance, bias in data, emerging forms of data and innovations in data visualization.

  • PM-349 Global Population Health: future opportunities and challenges

    This module consolidates global issues on the social, economic, political and environmental determinants of population size, structure and population health in both, high income countries as well as low and middle income countries from a multidisciplinary approach including social sciences, epidemiology, demography and public health. Topics include the relationship health and economic change; social support, social capital and health; policy responses to inequalities in health; prospects for mortality and morbidity change; urbanization and its implications for health, poverty, population change and inequalities; the `double burden¿ of disease and its consequences; the roles of nutrition an obesity for health of populations; emerging and current infectious diseases; the global burden of mental health disorders; and priorities for health improvements for low income countries. Throughout the module, students are encouraged to consider potential future opportunities and challenges for global population health.

  • PM-401 Science Communication

    This module will encompass a range of communication modes, from presentation of science to the general public to making a pitch for funding to `investors¿ The module will be run as a series of online seminars to prepare, firstly, for a short 3 minute thesis-like presentations to both a professional and non-professional audience. This will be complemented by preparation of short, New Scientist-style articles by each student on the topic of their presentation. Students will be assigned a topic that is appropriate to their degree title. For example, a Medical Geneticist could address recent advances in gene therapy. Subsequently, their task will be to produce a pitch to attract investment to commercialise their research. In the latter half of the module, the focus will be on skills-training for writing a scientific paper, preparing the ground for their project dissertations.

  • PMGM13 Ethical, Legal and Societal Issues (ELSI) in Applied Genomics

    This module will provide students with an understanding of the legal, regulatory & governance frameworks associated with medical genomics and the use of genomic data. It will equip students to explore and evaluate the main ethical, legal and social issues (ELSI) involved in: genomic testing and the wider implications for the patient and their families; precision medicine; and the use of genomic data for population research.

  • PMIM02 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. Module leader is Dr Joanne Demmler

  • PMIM202 Health Data Modelling

    Health data scientists are expected to work with diverse data sources. Modelling data encompasses setting up database models and analysing the data using statistical models. The objective of this module is to raise the awareness of students about the various processes of data modelling and the key operations involved in the data processing of large and diverse datasets. This is a core / compulsory module and worth 20 Masters level credits. Module leader is Dr Joanne Demmler

Supervision

  • 'Determining reasons for anxiety among people with MS' (current)

    Student name:
    MRes
    Other supervisor: Dr Kerina Jones
  • Medicines information on websites: a new proposed automatic approach of information quality assessment. (current)

    Student name:
    PhD
    Other supervisor: Dr Kerina Jones
    Other supervisor: Prof Gareth Jenkins
    Other supervisor: Prof David Skibinski
    Other supervisor: Prof David Skibinski
  • Risk appetite and personal data sharing;«br /» To what extent does the understanding of risk appetite impact upon the processing of personal data within Public Health Wales and the organisation’s ability to deliver on its Wellbeing objectives?«br /» (current)

    Student name:
    PhD
    Other supervisor: Dr Jodie Croxall
    Other supervisor: Dr Kerina Jones