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Online Webinar
28 Sep 2015
Health

Care Transitions Based on Predicted Readmission Risk: A Model of Hospital-Commun

Care Transitions Based on Predicted Readmission Risk: A Model of Hospital-Community Collaboration

Overview: This 402 bed regional medical system has developed a comprehensive transition program to identify and guide patients from acute care through comprehensive discharge planning and into community care. In the process, hospital readmission reductions were attained using transition nurses to proactively manage patients with a high risk of readmission. Using the modified LACE (Length of stay, Acute admission, Co-morbidities and ER visits) tool to identify patients at risk for discharge delays and/or readmissions and analytics to evaluate target populations, the program has been successful. The analytics allow us to correlate the patient risk of readmission with the actual observed readmission rate, the total cost of readmission encounters, the clinical drivers of readmissions. They also provide a financial model that calculates the overall impact of readmission rate reductions on reimbursement, cost, and value based purchasing payments. The program includes 30 day any cause readmission and follows specific clinical populations of AMI, Heart Failure, Pneumonia, Hip/Knee Replacement, Stroke, COPD, and Sepsis.Through analytics, we identified that a LACE score of 13-16 requires intense resources or a readmission is likely to occur. We aligned community resources such as medication assistance, transportation vouchers, self-monitoring equipment and home care navigators to assist in maintaining home placement for these patients. Unfunded patients have coordination of medications, equipment, etc. through community resources. Patients with scores above 8 receive a 3 -7 day follow-up, while patients with a score above 12 receive a full 30 days of follow-up.Goals included improving the patient experience, promoting health and wellness in the community and reducing readmissions. The collaboration between acute care and the community resources has proven beneficial to all involved. Beyond these goals, we understand and monitor our readmission trends. We are now delving into readmission analysis for same cause versus different cause and by diagnosis.

When

28 Sep 2015 @ 10:00 am

28 Sep 2015 @ 11:00 am

Duration: 1 hours

Timezone: GMT -5:00


Where

Online Webinar


Language

English en


Organised by

NetZealous (deactivated)

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