Improving Census Data Accuracy to Reduce Readmission Rates

Improving Census Data Accuracy to Reduce Readmission Rates

The Challenge

Our client, a healthcare provider, was facing an issue where their patient admission data from two different sources didn’t align. They received census data from a Healthcare Information Exchange (HIE) and claims data, but noticed a discrepancy: while census data indicated a drop in admissions, the claims data showed no such reduction. This mismatch left the client uncertain about the true picture of patient admissions, leading to potential operational inefficiencies.

Our Approach

We conducted a thorough analysis of both data sources, focusing on identifying the root cause of the discrepancy. Through our investigation, we discovered that the issue stemmed from errors in the census data. By pinpointing the exact source of these errors, we were able to help the client correct their data processes.

The Outcome

With our insights, the client was able to significantly improve the accuracy of their census data, increasing the match rate between census and claims. This improvement allowed their operational team to better track patient admissions and ensure timely follow-ups with patients after discharge. By addressing the root cause of the data discrepancy, the client could reduce the risk of patient readmissions, avoiding unnecessary medical costs and improving patient outcomes.