Employing a strategy that uses electronic medical records to direct care transition resources to the high-risk heart failure patients who need them most can reduce hospital readmissions, according to a new study by University of Texas Southwestern Medical Center and the Mayo Clinic.

Published in British Medical Journal Quality & Safety, the study – conducted by investigators from Dallas-based PCCI, a nonprofit research corporation, the University of Texas Southwestern Medical Center and the Mayo Clinic – offers evidence that technology platforms that enable automated EMR data extraction, natural language processing-based disease identification and computerized risk stratification may substantially reduce readmissions in heart failure in conjunction with thoughtful care coordination and cardiac evaluation, researchers say.

"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 the study's author, Ethan Halm, MD, professor of internal medicine and clinical sciences and chief of the division of general internal medicine at UT Southwestern.

The study prospectively evaluated 1747 adult inpatients admitted with heart failure, acute myocardial infarction and pneumonia over two years at Parkland Memorial Hospital in Dallas. PCCI developed the software platform used in the study, which sits above the EMR and stratifies patients admitted with heart failure on a daily basis by 30-day readmission risk, as defined by a published heart failure readmission reduction electronic model

Many studies have found that some combination of careful discharge planning, care coordination and counseling can prevent readmissions, deploying such high-intensity care for all patients, regardless of risk can be expensive, say researchers.

"This project was able to achieve the 'holy grail' of readmission reduction strategies," said Halm, in a press statement. "It reduced the population-based rate of readmission and saved the hospital thousands by redeploying limited, existing resources to the 25 percent 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."

By using the real-time risk stratification program and concentrating intensive care management and cardiac resources on about one-quarter of the patients admitted with HF, study investigators found that the hospital was able to produce a 26 percent relative reduction in the odds of readmission and an absolute reduction of five readmissions per 100 heart failure admissions, researchers say.

"These findings have important implications for the management of acute heart failure across large inpatient populations and health systems," said another of the study's authors, Parag C. Patel, MD, an assistant professor of medicine at the Mayo Clinic. "Patients with heart failure present to the hospital with different levels of readmission risk due to both physiologic and non-physiologic factors. Real-time electronic systems that capture this risk could significantly advance the way we manage these patients at a system level with greater efficiency and precision."

[See also: BOOST helps reduce readmissions]