What Can Health Care Teach Us About Data Quality?

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By Elliot King

Elliot King
Data quality issues are more acute in health care than in perhaps any other industry sector. According to a seminal study by the Institute of Medicine, (IOM) preventable medical errors are responsible for nearly 100,000 deaths annually, making it the sixth leading cause of death in the United States. These errors cost $98 billion annually.

Of course, not all of these errors reflect problems in data, but many do. And sometimes, data errors seems astonishing and the outcome devastating. According to the IOM, as many as 40 wrong sites, wrong side, wrong patient procedures occur every week. For example, a surgeon will amputate a person's right leg instead of the left or remove the gall bladder instead of a kidney. This is a "data error" of the most grievous kind.

Archaic paper record keeping has long been cited as a source of cost and a cause of medical errors. With paper records, if a patient is treated by more than one doctor, each doctor may not have read what the other doctors are doing. And that is not good.

But the aggressive move to electronic health records (EHR) has its own risks as well. Mistakes in patient data can follow the patient from doctor to doctor. Moreover, some programs allow health care providers to auto-fill fields, making it appear that they performed a more thorough examination, let's say, than they actually did.

The issue of the quality of the data used in EHRs has been thrown into the spotlight by efforts to reuse EHR information for clinical research. Within the medical community, most practitioners agree that clinical data is not recorded as carefully as research data. So researchers studying the potential of using EHRs for research measure quality by the characteristics with which most data quality professionals are familiar--completeness, correctness, timeliness, and so on. They assess those characteristics using multiple methods including comparisons to established standards, data element agreement, data source agreement and others.

Unfortunately, the early results of data quality assessment for EHRs are not very encouraging. Some studies have indicated that the introduction of EHRs does not lead to higher quality data being gathered, but just larger quantities of bad data. Findings like that have triggered a spirited debate in the medical community, with some arguing that the experience with EHRs demonstrate the first law of informatics--that data should only be used for the purpose for which is was collected.

-- For more info on data quality and the healthcare industry, download our free whitepaper on "Data Quality Is Good Medicine for Healthcare Providers."

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