Applied Analytics for Predicting Readmissions
A predictive analytics product for hospitals and health systems that want to decrease readmissions, identify patient intervention opportunities, and improve outcomes for high-risk populations.
Take control of avoidable readmissions by identifying contributing factors and determining which patients are at the highest risks. Our real-time analytics help hospitals and health systems combat high readmission rates.
Profile patients upon admission to assign a risk a readmission score using LACE criteria (length of stay, acuity, comorbidities, and recent ED visits), along with high-risk medications, social characteristics, and smoking status.
Prioritize inpatients for preventative nursing interventions with real-time patient intervention worklists that include the patient-specific likelihood of readmission score for each bedded patient.
Improve care during the patient’s initial stay with targeted interventions, such as patient/family education, post-acute care planning, and identification of financial obstacles.
Uncover the hidden factors driving avoidable readmissions, such as the cost and accessibility of prescription medications. Demonstrate the impact of new transitional care programs with cost and predictive analytics scorecards.
Forecast readmission measure performance and related penalties to adjust course in real time. Support behavioral changes with validated data, such as historical readmission data by department.