Tag Archives: health informatics

Organ Donor Records Mix-up

The Sunday Times reported in April 2010 that NHS Blood and Transplant, who run the UK organ donor register, last year wrote to new donors with their consent details. After respondents complained the information was incorrect it was discovered 800,000 individuals’ details had been recorded incorrectly. 45 of those affected have since died and their incorrect wishes carried out!

“The mistake occurred in 1999 when a coding error on driving licences wrongly specifying donors’ wishes was transferred to the organ registry.”

400,000 of the affected records have been changed, and the remaining 400,000 people will be contacted soon and asked to update their consent.

US Government Health (S)Care.

Courtesy of Jim Harris at the excellent OCDQBlog.com comes this classic example of a real life Information Quality Trainwreck concerning US Healthcare. Keith Underdown also sent us the link to the story on USAToday’s site

It seems that 1800 US military veterans have recently been sent letters informing them that they have the degenerative neurological disease ALS (a condition similar to that which physicist Stephen Hawking has).

At least some of the letters, it turns out, were sent in error.

[From the LA Times]

As a result of the panic the letters caused, the agency plans to create a more rigorous screening process for its notification letters and is offering to reimburse veterans for medical expenses incurred as a result of the letters.

“That’s the least they can do,” said former Air Force reservist Gale Reid in Montgomery, Ala. She racked up more than $3,000 in bills for medical tests last week to get a second opinion. Her civilian doctor concluded she did not have ALS, also known as Lou Gehrig’s disease.

So, poor quality information entered a process, resulting in incorrect decisions, distressing communications, and additional costs to individuals and governement agencies. Yes. This is ticking all the boxes to be an IQ Trainwreck.

The LA Times reports that the Department of Veterans Affairs estimates that 600 letters were sent to people who did not have ALS. That is a 33% error rate. The cause of the error? According to the USA Today story:

Jim Bunker, president of the National Gulf War Resource Center, said VA officials told him the letters dated Aug. 12 were the result of a computer coding error that mistakenly labeled the veterans with amyotrophic lateral sclerosis, or ALS.

Oh. A coding error on medical data. We have never seen that before on IQTrainwrecks.com in relation to private health insurer/HMO data. Gosh no.

Given the impact that a diagnosis of an illness which kills affected people within an average of 5 years can have on people, the simple coding error has been bumped up to a classic IQTrainwreck.

There are actually two Information quality issues at play here however which illustrate one of the common problems in convincing people that there is an information quality problem in the first place . While the VA now estimates (and I put that in bold for a reason) that the error rate was 600 out of 1800, the LA Times reporting tells us that:

… the VA has increased its estimate on the number of veterans who received the letters in error. Earlier this week, it refuted a Gulf War veterans group’s estimate of 1,200, saying the agency had been contacted by fewer than 10 veterans who had been wrongly notified.

So, the range estimates for error goes from 10 in1800 (1.8%) to 600 in 1800 (33%) to 1200 in 1800 (66%). The intersting thing for me as an information quality practitioner is that the VA’s initial estimate was based on the numberof people who had contacted the agency.

This is an important lesson.. the number of reported errors (anecdotes) may be less than the number of actual errors and the only real way to know is to examine the quality of the data and look for evidence of errors and inconsistency so you can Act on Fact.

The positive news… the VA is changing its procedures. The bad news about that… it looks like they are investing money in inspecting defects out of the process rather than making sure the correct fact is correctly coded in patient records.