Category Archives: Health & Welfare IQ Trainwrecks

Spelling mistake contributes to death of pensioner…

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From the Guardian (again) http://www.theguardian.com/uk-news/2016/feb/02/irmgard-cooper-bleeds-to-death-surgery-spelling-error-delays-blood-supply

A woman bled to death after a spelling mistake meant blood intended for her during an operation was sent back

The spelling mistake: IrNgard instead of IrMgard.

A second mistake related to the communication of key facts about the availability of blood during the procedure – an example of timeliness and completeness of data errors.

The Guardian report quotes the family solicitor as saying:

The first error was the misspelling of the patient’s name on the blood sample. The lack of communication between the anaesthetist and the surgeon over the absence of blood was the second error

It’s good to see that systems have been implemented to prevent recurrence. But sometimes, the processes we need to manage the quality of data in are zero-defect areas.

About Face due to data errors

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Via our eagle eyed correspondent Tash Whitaker comes this story from the UK health service:

Last month, the National Health Service took the unusual step of closing down a children’s heart surgery unit at a UK hospital, after data they had submitted showed that twice as many children and babies died in the unit than anywhere else in the UK. The UK media went went into a frenzy; people came out of the woodwork with stories about their treatment at the hospital, neglect and near death experiences in abundance.
Eleven days later and the unit is set to reopen. Turns out that there were not twice as many people dying after all, just a terminal case of data malaise. The data that the hospital submitted to the NHS was late and incomplete; in fact, 35% of the expected data was missing completely, with catastrophic results.

This particular hospital had obviously not stopped to think about the impact that bad quality data has on their business and on their customers. How many children and babies had heart surgery postponed as a result of the closure? How many may later die as a result of that postponement?

In a twist of fate, the unit was closed down only 24 hours after a High Court ruling that the hospital should keep its heart unit long term. I suspect that decision is now in jeopardy. How can the hospital’s reputation recover from something like this? Would you want your child to be operated on somewhere with a reputation for high death rates? A reputation that we know to be wrong but will no doubt stay with this hospital unit for many years to come.

The importance of data as a business asset is proclaimed regularly but we forget to mention that it can also be a liability. Most people don’t remember when good quality data helped them make decisions, helped them grow their business, or enabled them to beat the competition; but they sure as hell remember when it causes their business operations to cease, their reputation to be torn to ribbons and their status as a trusted entity to be shattered before their eyes.

(Sources: http://news.sky.com/story/1075720/leeds-hospitals-own-data-stopped-surgery

http://www.bbc.co.uk/news/health-22076206)

(Thanks to Tash for the alert and the excellent write up)

Unhealthy Healthcare data

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For a change (?) it is nice (?) to see stories about healthcare IQ Trainwrecks that don’t necessarily involve loss of life, injury, tears, or trauma.

Today’s Irish Examiner newspaper carries a story of the financial impacts of poor quality data in healthcare administration. At a time when the budgets for delivery of healthcare in Ireland are under increasing pressure due to the terms of the EU/IMF bailout of Ireland, it is essential that the processes for processing payments operate efficiently. It seems they do not:

  1. Staff continued to be paid pensions where they retired from one role and then re-entered the Health Service in a different role (HSE South)
  2. Absence of Controls meant staff who were on sick leave with pension entitlements being paid continued to be paid when they returned to work (HSE South)
  3. Pensions were calculated off incorrect bases for staff who were on secondment/shared with other agencies (HSE South)
  4. Inaccurate data about the ages of dependents resulted in overpayments of death in service benefits (HSE South).
  5. “Inappropriate” filing systems were resulting in “needlessly incurring wastage of scarce resources” (HSE Dublin/Mid Lenister)

 

Poor quality information costs between 10% and 35% of turnover in the average organisation. So the HSE may not be too bad. But the failure of controls and processes resulting in poor quality data leading to financial impacts is all too familiar.

Gas by-products give a pain in the gut

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Courtesy of Lwanga Yonke comes this great story about how the choice of unit of measure for reporting, particularly for regulatory reporting or Corporate Social Responsibility reports can be very important.

The natural gas industry’s claim that it is making great strides in reducing the polluted wastewater it discharges to rivers is proving difficult to assess because of inconsistent reporting and a big data entry error in the system for tracking contaminated fluids.

The issue:

Back in February the Natural Gas industry in the US released statistics which appeared to show that they had managed to recycle at least 65% of the toxic waste brine that is a by-product of natural gas production. Unfortunately they had their data input a little bit askew, thanks to one company who had reported data back to the State of Pennsylvania using the wrong unit of measure – confusing barrels with gallons.

For those of us who aren’t into the minutiae of natural gas extraction, the Wall Street Journal helpfully points out that there are 42 gallons in a barrel. So, by reporting 5.2 million barrels of wastewater recycled instead of the 5.2 million gallons that were actually recycled, the helpful data entry error overstated the recycling success by a factor of 42.

Which is, co-incidentally, the answer to Life the Universe and Everything.

According to the Wall Street Journal, it may be impossible to accurately identify the rate of waste water recycling in the natural gas industry in the US.

Not counting Seneca’s bad numbers — and assuming that the rest of the state’s data is accurate — drillers reported that they generated about 5.4 million barrels of wastewater in the second half of 2010. Of that, DEP lists about 2.8 million barrels going to treatment plants that discharge into rivers and streams, about 460,000 barrels being sent to underground disposal wells, and about 2 million barrels being recycled or treated at plants with no river discharge.

That would suggest a recycling rate of around 38 percent, a number that stands in stark contrast to the 90 percent recycling rate claimed by some industry representatives. But Kathryn Klaber, president of the Marcellus Shale Coalition, an industry group, stood by the 90 percent figure this week after it was questioned by The Associated Press, The New York Times and other news organizations.

The WSJ article goes on to point out that there is a lack of clarity about what should actually be reported as recycled waste water and issues with the tracking of and reporting of discharges of waste water from gas extraction.

At least one company, Range Resources of Fort Worth, Texas, said it hadn’t been reporting much of its recycled wastewater at all, because it believed the DEP’s tracking system only covered water that the company sent out for treatment or disposal, not fluids it reused on the spot.

Another company that had boasted of a near 100 percent recycling rate, Cabot Oil & Gas, also Houston-based, told The AP that the figure only included fluids that gush from a well once it is opened for production by a process known as hydraulic fracturing. Company spokesman George Stark said it didn’t include different types of wastewater unrelated to fracturing, like groundwater or rainwater contaminated during the drilling process by chemically tainted drilling muds.

So, a finger flub on data entry, combined with lack of agreement on meaning and usage of data in the industry, and gaps in regulation and enforcement of standards means that there is, as of now, no definitive right answer to the question “how much waste water is recycled from gas production in Pennsylvania?”.

What does your gut tell you?

 

Calculation errors casts doubt on TSA Backscatter safety

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It is reported in the past week on Wired.com and CNN that the TSA in the United States is to conduct extensive radiation safety tests on their recently introduced backscatter full body scanners (affectionately known as the “nudie scanner” in some quarters).

An internal review of the previous safety testing which had been done on the devices revealed a litany of

  • calculation errors,
  • missing data and
  • other discrepancies on paperwork

In short, Information Quality problems. A TSA spokesperson described the issues to CNN as being “record keeping errors”.

The errors affected approximately 25% of the scanners which are in operation, which Wired.com identifies as being from the same manufacturer, and included errors in the calculation of radiation exposure that occurs when passing through the machine. The calculations were out by a factor of 10.

Wired.com interviewed a TSA spokesperson and they provided the following information:

Rapiscan technicians in the field are required to test radiation levels 10 times in a row, and divide by 10 to produce an average radiation measurement. Often, the testers failed to divide results by 10.

For their part, the manufacturer is redesigning the form used by technicians conducting tests to avoid the error in the future. Also, it appears from documentation linked to from the Wired.com story that the manufacturer spotted the risk of calculation error in December 2010.

Here at IQTrainwrecks.com we are not nuclear scientists or physicists or medical doctors (at least not at the moment) so we can’t comment on whether the factor of 10 error in the calculations is a matter for any real health concern.

But the potential health impacts of radiation exposure are often a source of concern for people. Given the public disquiet in the US and elsewhere about the privacy implications and other issues surrounding this technology any errors which cast doubt on the veracity and trustworthiness of the technology, its governance and management, and the data on which decisions to use it are based will create headlines and headaches.

 

8 year old orphaned by a fat finger key stroke error

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Daragh O Brien has written and presented in the past for the IAIDQ on the topic of how the legal system and information quality management often look at the same issues from a different perspective, ultimately to identify how to address the issues of the cost and risk of poor quality.

This was brought home very starkly this morning in a case from the UK High Court which has opened the possibility of six figure damages being awarded to an 8 year old boy who was orphaned by a data quality error.

A single key stroke error on a computer cost a mother her life from breast cancer and left her eight-year-old son an orphan, the High Court has heard.

Two urgent letters informing the single mother of hospital appointments were sent to the wrong address – because the number of her home was typed as ’16’, instead of ‘1b’.

Read more: http://www.dailymail.co.uk/news/article-1366056/Mistyped-address-leaves-mother-dead-cancer-son-8-orphan.html#ixzz1GfRPOOHJ

In a tragic series of events a young mother discovered a lump on her breast. She was treated in hospital and given the all clear, but continued to be concerned. Her GP arranged further tests for her but she never received the letters due to a simple mis-keying of her address which meant she never received her appointment letters. As her cancer went untreated for a further 12 months by the time she was diagnosed her only treatment option was palliative care. Had she been treated in time, the Court heard, she would have had a 92% chance of survival for another 10 years.

Her doctor admitted liability arising from the failure of the surgery to follow up with the the woman on her tests, which might have uncovered that she hadn’t received the letters.

The Court dismissed an argument by the defence that the woman should have followed up herself, on the grounds that, while they would never know what had been in her mind, she had already been given an “all clear” and that she was likely either trying to get on with her life or may have been scared to return to the doctor.

A key lesson to be learned here is that ensuring accurate information is captured at the beginning of a process is critical. Equally critical is the need for organisations where the data is potentially of life and death importance to ensure that there is follow up where the process appears to have stalled (for example if expected test results are not received back from a hospital).

A simple error in data input, and a failure of or lack of error detection processes, has been found by the UK High Court to be the root cause for the death of a young mother and the orphaning of an 8 year old boy.  This is a SIGNIFICANT legal precedent.

Also, the case raises Data Protection Act compliance issues for the GP practice as sensitive personal data about a (now deceased) patient was sent to the wrong address.

RELATED POST: Daragh O Brien has a related post on his personal blog from 2009 about how Information Quality is getting some interesting legal support in the English legal system.

Smart Grid, Dumb Data

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In September 2010 a massive gas explosion ripped through the San Francisco suburb of San Bruno, not too far from San Francisco International Airport. The explosion was so powerful it was registered as a magnitude 1.1 earthquake.

Subsequent investigations have identified that poor quality data was a contributory factor in the disaster. According to Fresnobee.com

The cause of the deadly rupture has not yet been determined, but the PUC said it is moving ahead with the penalty phase after the National Transportation Safety Board recently determined that PG&E incorrectly described the pipe as seamless when in fact it was seamed and welded, making it weaker than a seamless pipe.

Read more: http://www.fresnobee.com/2011/02/25/2285689/pge-faces-big-fine-over-gas-pipeline.html#

According to the San Francisco Chronicle the problems with PG&E’s data were nothing new, with problems stretching back almost 20 years.

Omissions or data-entry errors made when the system was developed – and left uncorrected – may explain why PG&E was unaware that the 1956-vintage pipeline that exploded in San Bruno on Sept. 9, killing eight people, had been built with a seam, according to records and interviews. Federal investigators have found that the explosion started at a poorly installed weld on the seam.

Continue reading →

So exactly HOW pregnant is he?

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From the #dataquality correspondents on Twitter comes this great story of a classic IQ Trainwreck.

Hilton Plettell is pregnant and is expected to deliver in 7 months, according to the NHS. They’ve invited him to a scan to see his bundle of joy.

Yes. We did say HIM and HIS, because Hilton is a 50 year old department store merchandising manager. But that is not the end of the IQ Trainwreck here.

  1. The hospital he was directed to is 162 miles from his home (a long way to travel with the full bladder needed for an ultrasound scan).
  2. A sticker attached to the letter correctly identified Mr Plettell as being Male.

So, 3 errors or inconsistencies in the letter which indicate a Data Quality kerfuffle in the NHS (at least in Norwich).

A spokesperson for the hospital thanked Mr Plettell for raising the issue with them and indicated they were undertaking a Root Cause Analysis to see where their processes and procedures could be improved to prevent this type of obvious error.

We can’t help but wonder if the root cause might be similar to the problem encountered by DataQualityPro.com’s Dylan Jones last year, which we reported here in June 2009.

The story is covered in the Daily Male  Mail, which reproduces a picture of Mr Plettell’s hospital letter (but that image is copyright so we can’t republish it here).

Organ Donor Records Mix-up

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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.

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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.