Data integrity: Developing a successful strategy

DSS Innovations Inc.

By Mark Byers, President and CEO DSS, Inc

 

Rapid gains in data sharing and interoperability are something of a double-edged sword. Unlocking the patient data in electronic health records (EHR) enables tremendous advantages in virtually all aspects of healthcare, from patient safety to revenue cycle management. At the same time, streamlining the sharing of those records makes it possible for unintentional duplication errors to occur throughout multiple systems and for new errors to be introduced in data handling. It’s therefore imperative that we not only capture data accurately, but also maintain data integrity as records are exchanged throughout the federal healthcare system.

 

This is especially challenging when it comes to aggregating patient records from different systems. The most common problems that arise are fractured patient records – in which patient data from a more complete record is lost in a merging process – and duplicate records, where initially there may be identical patient data, but diverges when only one record is updated. Both issues compromise patient health record reliability, negatively impacting safety, efficiency and billing if left undiscovered. When issues are in fact identified, cleaning them up can require far more time and effort than it would have taken to protect data integrity proactively from the start.

 

Top considerations for maintaining integrity

The path to developing proactive strategies for data integrity involves carefully controlling processes related to the electronic exchange of patient information. The following best practices for ensuring completeness and accuracy of data will greatly reduce instances of duplicate and fragmented records. They include:

 

  • Institute strict quality guidelines for all exchange processes. Access to health record exchange processes should be tightly regulated and provided only to verified applications and personnel; following the same best practices often associated with protecting transfers to and from any sensitive data repository.
  • Keep training up-to-date for authorized personnel. Those who have authority over patient information exchange must be kept abreast of all changes to system interfaces, internal operations and regulations that affect their functional roles. Any changes should be accompanied by comprehensive training, and ongoing support should be provided in order to ensure staff are knowledgeable and qualified.
  • Keep systems and applications up-to-date. Systems and software vendors frequently issue updates and patches specifically to address potential issues that can arise in data exchange. Don’t skip updates and patches; install them upon receipt to ensure that your system is fully protected.
  • Employ sound extract, transformation and load (ETL) processes. ETL is the firmly established standard for data warehousing and ensures that data follows validation rules, is properly prepared for loading and joins existing data according to enterprise rules. These elements are all essential to maintaining data integrity in exchanges between dissimilar systems.

 

While the steps above aren’t unique to governmental healthcare IT, these best practices ensure accuracy, completeness and accessibility in the exchange of high-value data critical to ensuring timely and thorough care. With the goal of improved outcomes in mind, federal healthcare enterprises must ensure that the patient data captured electronically remains uncompromised as it moves through the care delivery system.

 

About the author

Mark Byers is President and CEO of DSS, Inc. He is a Service Disabled Veteran (United States Air Force). His professional software development experience spans more than 33 years in the data processing industry, of which more than 20 years have involved the development of VistA-integrated solutions. He has also been actively involved in the development of electronic health record software, specifically the VistA-based platform, for more than 16 years.

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