Automated Predictor Flags Patients at Risk for 30-Day Readmission: Study

An automated prediction tool that identifies newly admitted patients at risk for readmission within 30 days of discharge has been successfully incorporated into the EHR of the University of Pennsylvania Health System.

The tool, developed by researchers at the Perelman School of Medicine, predicts at-risk patients as those who have been admitted to the hospital two or more times in the 12 months prior to admission. Once it identifies these high-risk patients, it creates a flag in their EHR, which appears next to the patient’s name in a column titled “readmission risk” once the patient is admitted. The flag can be double-clicked to display detailed information relevant to discharge planning including inpatient and emergency department (ED) visits over the previous 12 months, as well as information about the care teams, lengths of stay, and problem(s) associated with those prior admissions.

Interventions proven to help reduce 30-day readmissions include the following:

  • Enhanced patient education and medication reconciliation on the day of discharge;
  • Increased home services;
  • Follow up appointments soon after discharge;
  • Follow-up phone calls; and
  • Medication reconciliation of patient’s current and prior medication, to avoid medication errors such as omissions, duplications, dosing errors or drug interactions.

In support of the study, the Penn Medicine Center for Evidence-based Practice identified a number of variables associated with readmission to the hospital, including prior admissions, visits to the ED, previous 30-day readmissions, and the presence of multiple medical disorders.

Using two years of retrospective data, the team examined these variables using their own local data and found that a single variable – prior admission to the hospital two or more times within a span of 12 months — was the best predictor of being readmitted in the future. This marker was integrated into the EHR and was studied prospectively for the next year. During that time, patients who triggered the readmission alert were subsequently readmitted 31 percent of the time. When an alert was not triggered, patients were readmitted only 11 percent of the time.

The risk assessment tool is part of a series of steps taken by Penn Medicine to reduce readmissions.

Source: Penn Medicine , November 27, 2013

2012 Healthcare Benchmarks: Reducing Avoidable ER Visits

2012 Healthcare Benchmarks: Reducing Avoidable ER Visits provides critical benchmarks that show how the industry is working to reduce avoidable hospital ED visits, and is designed to meet business and planning needs of hospitals, health plans, physician practices and others.

This entry was posted in Avoidable Hospitalization, electronic health records (EHRs), Healthcare Information Technology, Healthcare IT, Hospital Readmissions and tagged , , . Bookmark the permalink.
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