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Another Victim of Bad Maths?

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Criminologist Prof David Wilson writes on Suspected Miscarriage of Justice Case Colin Norris

As readers of my blogs and articles may know, I have an interest in miscarriages of justice, particularly those that result from poor use of statistics and probability (this is the link with investing). I was therefore interested to see renowned criminologist Prof David Wilson writing in the Scottish Herald this week about Colin Norris, the nurse who was convicted in 2008 of killing four of his elderly patients by injecting them with insulin.

Prof Wilson appears to have always had doubts about the soundness of Norris' conviction (as have many others, including me). Thankfully, the Criminal Cases Review Commission decided to refer the case in February 2021 to the Court of Appeal (the appeal is yet to be heard).

I mentioned the Norris case in a post in October titled Miscarriages of Justice in Killer Caregiver Cases, a piece that was prompted by the start of the trial in Manchester of another suspected killer nurse case, that of Lucy Letby:

Caregivers who have either been wrongly accused or convicted, or where there is for good scientific/statistical reason for suspicion of such, include Lucia de Berk, Daniela Poggiali, Jane Bolding, Sally Clark, Susan Nelles, Ben Geen, and Collin Norris. If it turns out there is no direct evidence against Lucy Letby, let's hope her name doesn't join the list.

It was therefore particularly interesting, given that Letby's case is ongoing, to read Prof Wilson's opening paragraph:

IT'S been hard to avoid discussing nurses over the last few weeks – quite apart from the fact that our daughter, who like many "twentysomethings" is still living at home, always wants to talk about her work as a nurse when she finishes her shift as a way of unwinding.

Although Prof Wilson does not mention Letby by name, her case may be what he is referring to when he writes, "It's been hard to avoid discussing nurses over the last few weeks" (it may of course also/instead be a reference to the recently released film The Good Nurse about killer nurse Charles Cullen and/or to the industrial action by the nurses' union in last few days).

Regardless, I have been following the Letby trial quite closely and thus far no direct evidence against her has been presented. Moreover, the prosecution has presented as evidence a number of Letby's text messages to and conversations with colleagues as well as her internet search history (she searched on Facebook for parents of babies she is accused of murdering or attempting to murder) which it suggests are incriminating.

I do not know what is like to be a nurse in a neonatal unit where the death of premature babies is a not uncommon occurrence, but I imagine it can sometimes be very upsetting. It certainly seems plausible to me that, once their shifts have ended, nurses in such situations would do things to help them come to terms with traumatic events. Examples might include texting or saying certain things to each other, perhaps using gallows humour, or feeling the need to seek some sort of connection with parents, albeit a passive one, via internet searches, or going dancing.

In other words, such behaviour would not be incriminating at all, but what Prof Wilson refers to when he writes about his daughter always wanting "to talk about her work as a nurse when she finishes her shift as a way of unwinding". Indeed, I suspect this is a veiled reference to Letby's post-shift behaviour and the prosecution's insinuation that it was something other than completely innocent 'unwinding'.

Thus, despite the case being sub judice, it would appear that Prof Wilson is hinting that he thinks that jurors may be assessing the evidence of Letby's post-shift comments and actions under a presumption of guilt not innocence. A different perspective changes everything.

Prof Wilson and his colleague Prof Elizabeth Yardley conducted research in 2014 on "the very small group of nurses who abuse their position of trust and kill their patients". He writes:

Why did nurses behave in this way, and what could hospital administrators and law enforcement do to ensure that this rare type of killer did not become more common? What “red flags”, as we called them, about the nurse or about their work performance give cause for concern, and how many of these red flags needed to be present before action would have to be taken?

Our research was based on a sample of nurses who had been convicted of murdering their patients in Europe and North America, and we used a 22-point checklist of personality traits and work behaviours that were associated with that sample. We then discovered how a median of six of these 22 points tended to cluster in the backgrounds of more than half of our sample. This cluster of red flags were higher incidences of death on his/her shift; has a history of mental instability and/or depression; makes colleagues anxious; moves from one hospital to another on a regular basis; is found to be in possession of drugs (both legal and illegal) at home/in their work locker; and, appears to have a personality disorder.

The most prevalent red flag that we identified was to have had higher incidences of death on his/her shift. In other words, where there were a number of deaths over a specified time period that exceeded those that were expected when compared to the usual number of deaths for that ward or the hospital, and shift patterns were then used to determine a suspect. Attendance data revealed the presence or absence of particular members of staff during, or around the time of these unusual death rates.

However, and this was the important finding, we discovered that there was an uneasy fit between scientific and legal principles in this context, as attendance data didn’t actually establish guilt on the basis of the “similar fact” principle of evidence where there needed to be a direct association between specific actions and specific events.

So, we discovered that what might appear sound and convincing from a policing point of view had great deficiencies when employed as evidence in court, and there were practical consequences as a result. Attendance data had been used to convict, for example, the Dutch nurse Lucia de Berk of killing seven of her patients in 2003, although she was acquitted seven years later when it was accepted that attendance data alone could not prove her guilt.

As a result, our research suggested that having just this one red flag should never be used as a basis for conviction, as a higher than average number of deaths over a given period of time may have various explanations – of which an active serial killer is only one – and therefore could in our view only be used as a basis to convict when found in combination with other red flags.

As I wrote in my October piece, the probability that a ward somewhere in the UK is going to have a well-above-average number (a cluster) of unexplained deaths during, say, a 20 year period by pure chance is very high, very possibly odds on. On the other hand, the probability of a particular ward experiencing such is very low, one in tens or hundreds of thousands. Think about The National Lottery. You are never surprised to hear that someone has won it, but you would be if that someone was you.

In the face of an elevated number of unexplained deaths, the hospital authority in question will often find it hard to accept that it was just incredibly unlucky, and thus search for an explanation. Furthermore, it might prefer a sinister explanation (murder) to one that implicates the hospital (poor management).

Once a hospital authority has convinced itself that a killer is in its midsts, and that the killer is probably a nurse (it couldn't possibly one of those nice and competent doctors, and anyway we might need them later to support us) the next step is to analyse nurse roster data. There is a 100% probability that the roster data of one of the nurses will match most closely with the pattern of unexplained deaths. It doesn't matter if the match is not a close one. It's the closest. And therefore the nurse with the closest fitting roster data must be the killer. As for the unexplained deaths that did not happen on said nurse's shifts - there will always be some - they are simply ignored. We have our man, after all.

What then follows is a frantic hunt for evidence against the suspect (in addition to that of the roster data). Suddenly, comments and actions that would previously have been considered completely innocent are seen in a suspicious light. Those with a grudge against the nurse might lie. Memories might get gradually distorted, pressure put on staff. And, before you know it, there is a large body of circumstantial evidence against the accused (miscarriages of justice do not tend to happen where there is direct evidence, as was the case with Harold Shipman and his tampering with his victims' wills).

Prof Wilson continues:

This nursing preamble leads me inexorably to Colin Norris. Born in Glasgow, and trained in Dundee, Norris was convicted in 2008 of killing four of his elderly patients by injecting them with insulin in Leeds, where he worked as a nurse at St James’s University Hospital and Leeds General Infirmary. It was claimed that Norris hated elderly, female patients and that was why Doris Ludlam, Bridget Bourke, Irene Cookes and Ethel Hall had lost their lives. However, Norris was an "outlier" – just like Lucia de Berk and that encouraged us to look a little more closely at how he had come to be convicted.

We were disturbed by what we found. It was soon clear that the case against Norris was entirely circumstantial but through the police interrogating attendance data he became the supposed “common denominator” in this cluster of deaths, although there was no direct evidence whatsoever to link him to what had happened to Doris, Bridget, Irene and Ethel.

There was no “good nurse” like Amy Loughren who had worked out what Cullen [Charles Cullen, an American nurse who confessed in 2003 to killing up to 40 patients] was doing, and reported her anxieties to the police. Instead there was simply rumour and tittle-tattle that was used to spin a motive for Norris, who was jailed for a minimum of 30 years, but who has never stopped maintaining his innocence. To this day both Elizabeth and I believe that there has been a miscarriage of justice, and it is good to see that his case has now been sent back to the Court of Appeal.

Norris was originally charged with five murders but it was then discovered he could not have committed one of them. The police started looking for a second murderer, right? Wrong. The fifth murder was deemed no longer a murder and...ignored.

Norris appears to have been a victim of poor use of probabilities as described above. He was also it seems the victim of expert after expert testifying that naturally occurring hypoglycaemia in the elderly was far rarer than it actually is (thus, in the case of Norris' 'victims', their hypoglycaemia could only have been caused by him having injected them with insulin).

There are many parallels between Letby's and Norris' cases. The Countess of Chester Hospital where Letby worked had received a damning review. It had had its neonatal competency level downgraded. The evidence against Letby is purely circumstantial. She is getting blasted in the press for going dancing after a shift on which one of her subjects had died. The list goes on.

I am not saying Letby is not a murderer. How would I know? What I do know is that her case bears similarities to others in the past that resulted in wrongful convictions. Judges tasked with guiding jurors are rarely also mathematicians (one UK judge is even on record as saying he did not understand the specific aspect of probability relevant to these so-called 'cluster cases'). Nor are jurors. Let's hope that in Letby's case her defence team can convert them, if only for the duration of their deliberations.

The views expressed in this communication are those of Peter Elston at the time of writing and are subject to change without notice. They do not constitute investment advice and whilst all reasonable efforts have been used to ensure the accuracy of the information contained in this communication, the reliability, completeness or accuracy of the content cannot be guaranteed. This communication provides information for professional use only and should not be relied upon by retail investors as the sole basis for investment.

© Chimp Investor Ltd

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