Data quality in healthcare: The case for increased interoperability

Given that most of us see more than one doctor – in more than one health system – it’s no surprise that medical records from a single location are often incomplete. But that’s a problem, according to a new study about data quality in healthcare.
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Data quality in healthcare

Information sharing is key to ensuring data quality in healthcare, according to a new study published in the Journal of the American Medical Informatics Association. Specifically, the research showed that calculating quality improvement measures based on only one source of information is likely to generate flawed conclusions, which in turn has negative impacts on both patient care and financial return.

That’s because people rarely stay within one institution when seeking out healthcare. Because of this, information from a single source – like the electronic health record (EHR) system of only one hospital – is almost always incomplete.

The study looked at data from 53 different institutions. Specific data quality metrics were measured in two ways – first, by using data from a single institution’s EHR system only and second, by integrating relevant data from a local health information exchange (HIE) with this organization’s information. Overall, the integrated data showed that 79% of patients in the study had records located within more than one facility. For the quality measures calculated, 15% changed significantly once HIE data was incorporated with local, institutional records. This demonstrates the continuing need for increased interoperability in healthcare.

Getting the records right

But even after data is shared, there are still important steps to take to ensure that no information gets lost in the process. Once data from multiple sources has been aggregated, organizations like the HIE in this study often take on the extra work of making sure records are complete and correct. Without this process – known as data normalization – the quality of data may be degraded, since pieces of patient records can get lost and watered down as they’re collected and transferred.

And the task of normalizing isn’t always an easy one, since different hospitals, providers, and labs can use multiple forms of clinical documentation to describe the care they provide. On top of that, interoperability standards aren’t always clear, which can impact the integrity of shared data.

To learn more about patient data normalization, download our insight brief or watch our webinar-on-demand.
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