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A new study,1 conducted by researchers from PCCI, a non-profit R&D corporation, looked at an EMR-enabled strategy targeting high-risk heart failure (HF) patients to reduce readmissions.
By evaluating 1,747 admitted HF patients over a two-year period, the study provided evidence that technology allowing automated EMR data extraction, natural language processing-based disease identification, and computerized risk stratification may substantially reduce readmissions in HF patients.
"This is one of the first prospective studies to demonstrate how detailed data in EMRs can be used in real-time to automatically identify and target patients at the highest risk of readmission early in their initial hospitalization when there is a lot that can be done to improve and coordinate their care, so they will do well when they leave the hospital," said Ethan Halm, MD, MPH, senior author on the paper and Professor of Internal Medicine and Clinical Sciences and Chief of the Division of General Internal Medicine at UT Southwestern.
As health care providers struggle to sustain a combination of discharge planning, provider coordination, and intensive counseling to prevent readmissions, and the cost it incurs, this EMR-targeted strategy provides a possible solution.
"This project was able to achieve the 'holy grail' of readmission reduction strategies. It reduced the population-based rate of readmission and saved the hospital thousands by redeploying limited, existing resources to the 25% of the patients at highest risk. It was so successful that what started as a research project is now part of the way the hospital does business," said Dr. Halm.
Reference: 1. Amarasingham RA, Patel PC, Toto K, Nelson L, et al. Allocating scarce resources to reduce heart failure readmissions: A prospective controlled study. BMJ Quality & Safety. July 31, 2013 [Epub ahead of print].