Statistical Issues in Serial Killer Nurse Cases

Richard D. Gill (), Norman Fenton and David Lagnado
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Richard D. Gill: Mathematical Institute, Leiden University, P.O. Box 9512, 2300 RA Leiden, The Netherlands
Norman Fenton: School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK
David Lagnado: Department of Experimental Psychology, University College London, Gower Street, London WC1E 6BT, UK

Laws, 2022, vol. 11, issue 5, 1-28

Abstract: We study statistical aspects of the case of the British nurse Ben Geen, convicted of 2 counts of murder and 15 of grievous bodily harm following events at Horton General Hospital (in the town of Banbury, Oxfordshire, UK) during December 2013–February 2014. We draw attention to parallels with the cases of nurses Lucia de Berk (the Netherlands) and Daniela Poggiali (Italy), in both of which an initial conviction for multiple murders of patients was overturned after the reopening of the case. We pay most attention to the investigative processes by which data, and not just statistical data, is generated; namely, the identification of past cases in which the nurse under suspicion might have been involved. We argue that the investigation and prosecution of such cases are vulnerable to many cognitive biases and errors of reasoning about uncertainty, exacerbated by the fact that fact-finders have to determine not only whether a particular person was guilty of certain crimes, but whether any crimes were committed by anybody at all. The paper includes some new statistical findings on the Ben Geen case and suggests further avenues for investigation. The experiences recounted here have contributed to the writing of the handbook Healthcare Serial Killer or Coincidence? Statistical Issues in Investigation of Suspected Medical Misconduct , Royal Statistical Society, London, 2022.

Keywords: clusters of unusual events; Baader-Meinhof phenomenon; Munchausen syndrome by proxy; confirmation bias; health care serial killers; unsafe convictions; forensic statistics (search for similar items in EconPapers)
JEL-codes: D78 E61 E62 F13 F42 F68 K0 K1 K2 K3 K4 (search for similar items in EconPapers)
Date: 2022
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