About Face due to data errors

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


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

One thought on “About Face due to data errors

  1. Jumping to the conclusion that this was a data problem is equivalent to the rush to judgment that the hospital should be closed. It makes for good headlines but poor advice. Data errors are the result, not the cause of quality. More obviously this was a business policy and process problem.

    A lack of quality in decision making and perhaps the quality of skills of those involved in this entire episode. Or perhaps the hubris surrounding data is itself a root cause. Examining the root cause of the benefits of data such as “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” should likewise be the subject analysis.

    Blaming the data is politically safe. The “data” can’t defend itself. It’s inanimate. Further readings regarding this incident as well as the policies and processes for recording hospital related data provides a broader perspective of the problems that “appear” to be data quality problems.

    Understanding the environment and context in which data is used is frequently more critical than the errors publicized in this case and in industry and other domains. Headlines don’t solve problems and repeating headlines don’t add to the understanding of data quality.
    Without the full story, articles such as this provide a myopic and limited view of the problems that manifest themselves as data errors. Without these insights we will continue to address the symptoms not the causes of data errors.

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