How Poor Data Standardization Affects Healthcare Organizations

Ever wonder what could be hindering your organizations patient matching index? The answer could be that your data and workflow standardization is poor.

According to a study published in AHIMA’s Perspectives in Health Information Management, “Poor Data Standardization can result in incomplete and inaccurate data collection, patient matching issues, and slower organizational workflows.” For healthcare organizations to deliver the best, most efficient, and high quality of care, they must need accurate and up to the minute patient information and data.

The study also reports that the master patient index (MPI) plays a vital role in providing organizations with a “complete view of the patient’s medical and treatment history”. MPIs contain clinical information and demographic data, both of which aid in helping providers understand and identify patients across the organization better.

Researchers conducted interviews with HIM professionals at an outpatient healthcare facility to reveal what challenges were associated with MPIs in healthcare. The researchers found that “eighty percent of HIM professionals reported that data standardization issues result in inaccurate and incomplete MPI data.”

Participants stated that their organizations lacked standards for collecting data, which creates a problem when a demographic information changes. They also noted patients are often are changing their demographic information, and their current data collection methods are not addressing this issue.

“Incomplete or incorrect demographic data can be detrimental to patient matching and identification, with organizations failing to recognize existing patient records or failing to update their records with accurate information.

Participants also said that MPI records lacked enough matching data points, this causes patient matching to be depended on with limited data, which creases the risk of mixing up patients with the same records.

Eighty percent of those interviewed reported that “these mistakes were only discovered when providers were preforming treatment”. They also stated that “these challenges have slowed their workflows”.

Healthcare organizations should look at improving the methods they use for the collection of data, standardize the way to identify a patient across all registration points, and encourage patients to aid in the identification process.

Regardless of how your organizations workflow is structured, Extract can accommodate to your organizational needs. We specialize in creating software that reduces manual data entry, standardizes both data and workflow across all departments and clinics, all to make your company both more efficient and more accurate.

About the Author: Taylor Genter

Taylor is the Marketing Specialist at Extract with experience in data analytics, graphic design, and both digital and social media marketing.  She earned her Bachelor of Business Administration degree in Marketing at the University of Wisconsin- Whitewater. Taylor enjoys analyzing people’s behaviors and attitudes to find out what motivates them, and then curating better ways to communicate with them.