Why Clinical Document Architecture doesn’t solve data quality issues

Why Clinical Document Architecture doesn’t solve data quality issues

Clinical Document Architecture (CDA), for all its promises of better-organized and better-quality data, is not perfect. Its weakness is due, in part, to what it is able to do—exchange data.

To be sure, it is no secret that healthcare data has a quality issue, whether it’s technical or otherwise. In fact, from a developer’s perspective, health data is really at the mercy of those who treat patients and enter data into their records.

However, it is possible to give doctors feedback on the data that they are entering to improve its usefulness. Why do they need such feedback? A big reason is the loose definition of CDA, which is able to place results in many fields in the typical Electronic Medical Records (EMR).

The CDA is a standard that provides the ability to place data in records, enabling clinician notes to be transferred as free text entry. For better or worse, that leaves developers at the whim of the data that a human has manually entered into an EMR program. It is difficult to tell a system what to do when the word “wheelchair” is entered in a field for the height of a patient, or the word “childhood” is used for recording the date of a procedure in a surgical history questionnaire.

EMR vendors do not take the time to educate doctors and other medical staff properly on how to enter data, especially after systems are running and operational. EMR systems typically do not run any analytics on information entered—usually, they just do edit checks to ensure the data is valid. However, the systems do not ensure that entered data is actually accurate and useful.

To extend the previous example, an entry such as “wheelchair” is technically valid for height, weight, blood pressure, allergy, favorite soft drink and smoking habits, among other things. This scope of variation is bad for data analytics efforts, because it mixes invalid data with valid data.

An analytics mindset needs to have a desire to drive down healthcare costs by allowing better risk calculations while, at the same time, helping doctors and other medical staff provide better healthcare by identifying which patients need treatment, and how that treatment needs to be organized.

Physicians and other medical staff are increasingly receptive to feedback offered about how to improve data entry. In many cases, they just need the proper education. This means that with the proper analytics approach, the benefits of better data entry can provide tangible and actionable benefits for providers, patients and payers.

And this is where software architecture can help out. CDA is an XML-based structure designed to contain any number of Continuity Care Documents (CCD). The documents are used for tracking patient data. However, while they both use XML as their document structure standard, the use of that XML for these purposes has not been stringently defined.

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