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Data Quality Corner: Optimizing Data Transfer

MSPP understands the importance of data accuracy and integrity in Immunization Information Systems. In this space, we highlight how our team is working to ensure and optimize data quality so that our clients can use that data to provide the best care possible in an efficient manner.  

This quarter we feature how MSPP’s collaborated with MDH to ensure data accuracy. 

Recently, MSPP collaborated with the Maryland Department of Health (MDH) and CRISP (Maryland’s health information exchange), to access data integrity and the effectiveness of data transfer. Our goal was to ensure our data accuracy was meeting the minimum 95% accuracy standard, and implement a process to continually monitor the success of data transmission, and resulted in achieving a 98.5% data accuracy in 2021 with timely transmissions to IIS.

In a joint effort, all identified defects/ missing data were reviewed and investigated. The process initially began with 1.7 million records of COVID data exported from PrepMod. This data was securely transferred to MDH and CRISP, where they compared and validated against the IIS data. 

Greg Reed, CDC Regional Field Supervisor and Deputy Program Manager for Maryland Department of Health, Center for Immunization, worked closely with PrepMod on the project. Greg said, "This process allowed us to identify data that wasn't being captured by ImmuNet but should have been. More importantly, it allowed us to identify why. We discover that certain special characters and certain shortened words, for example, having someone's name as Christopher in ImmuNet and Chris in PrepMod, would cause an error in data transfer."

"Through this research, we made adjustments in ImmuNet and expanded characters and character fields. It also allowed PrepMod to know what adjustments need to be made so that special characters we not accepted in their system. That way, untransferable data wasn't making its way from PrepMod over to ImmuNet, causing errors."  

Greg stated that "Since completing this process, we've noticed that the errors have significantly reduced. On a daily basis, I go into one of my favorite features in PrepMod called Data Transfer and look at the previous day's clinics transmissions to see any records have failed. I’m very pleased to say that the number of failed records is few and far between, showing us that the adjustments we've made previously are still functional and doing their job to ensure data accuracy. Working with PrepMod was a very smooth and flawless process that we plan to repeat annually to ensure that this type of data accuracy continues.”

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