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Ethical Issues in E-Science The View From Clinical Genetics

Ethical Issues in E-Science The View From Clinical Genetics. Jonathan Berg Senior Lecturer and Honorary Consultant in Clinical Genetics University of Dundee. Starting a Project The Mountain of Paperwork. R+D approval MREC approval LREC locality approval Data protection Honorary contracts

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Ethical Issues in E-Science The View From Clinical Genetics

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  1. Ethical Issues in E-ScienceThe View From Clinical Genetics Jonathan Berg Senior Lecturer and Honorary Consultant in Clinical Genetics University of Dundee

  2. Starting a ProjectThe Mountain of Paperwork • R+D approval • MREC approval • LREC locality approval • Data protection • Honorary contracts • Caldicott • PIAG

  3. Wouldn’t it be better if it all just blew away ? It is important to distinguish the beurocracy of ethical approval From ethical behaviour

  4. Typical E-Science Grant Proposal We are going to collect a large amount of patient data, access it via the GRID and do something interesting with it. Key words: Data Mining, GRIDS, Object Oriented Database

  5. Inputs to a Medical Research Database Death Certificates Birth and Marriage Certificates GP Local Clinics Clinical Information High Quality Many Patients Hospital Discharge Specialised Clinics Prescribing Records Laboratory Investigations Cancer Registry

  6. Large Database Projects • Open Ended Research Question • Cannot specify nature of study at point of consent • Indefinite storage of data • Open access to data • Complete anonymisation of data impossible • Family structure • Genotypes • MRI scans • History • Can infer important clinical information from data available

  7. Example Data:The Family Tree Helen 60 Jean 45 Anne 55 Fred 62 Joan 35 Angela 38

  8. The Family TreeWhat The Patient Sees ? Anne 55 Breast CA 40 Jean 51 ? Cancer Helen 60 Fred 62 Joan 35 Angela 38

  9. The Family TreeClarified by a Geneticist Anne 55 Breast CA 40 Jean 45 Ovarian Cancer 42 Helen 60 Fred 62 Joan 35 Angela 38

  10. The Family TreeWhat The Geneticist Sees….Lifetime Breast Cancer Risk Anne 55 Breast CA 40 Jean 45 Ovarian Cancer 42 30% Fred 62 40% 40%

  11. Problems Surrounding Family History • Storage of information on individuals without their consent • Not easy to preserve family structure and important details when anonymising data • Important clinical observations are made from data derived on individuals who do not know they are being observed • It does not take much data to reach worrying conclusions

  12. Other dataE-Diamond Specific Issues • Mammograms available on GRID • Security and access • Matched with some clinical data • Effective anonymisation • Type of analysis not pre-determined • Is informed consent possible ? • Possible Risks of Participation • Previously unidentified cancer • New risk factors derived from mammogram

  13. EGC Package - Proposed flow of information Anonymisation +Security National research tools Regional Database Clinical data Family tree data Screening data Multimedia Data eg Mammograms Pathology Microarray data Tabulated Data Request Local research tools Clinical Domain

  14. Give me every individual • UK postcode HG4 4PH • Head Circumference >97th Centile • Case Initials Age Other sensitive data • AB 3.5 Likes Teddy Bears • JB 37 Wears Odd Socks

  15. Conclusion • E-Science has a lot to offer medical research • The ethical challenges are not trivial • The paperwork is the least of the problems

  16. Conclusion Ethical design has to be inherent in the database • System design has to take into account • Patient consent • Who accesses data (and who decides) • How the data is accessed • How the data is exported • How system use is policed

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