On-Demand Broadcast: Predictive Healthcare Analytics: Four Pillars for Success
Allina Health System's Minneapolis has saved over $155 million by reducing unnecessary clinical variation through its predictive analytics programs.
During Predictive Healthcare Analytics: Four Pillars for Success, a March 29th webinar, Pam Rush, cardiovascular clinical service line program director at Allina Health, and Dr. Steven Bradley, cardiologist, Minneapolis Heart Institute (MHI) and associate director, MHI Healthcare Delivery Innovation Center, sharee their organization's four pillars of predictive analytics success...addressing population health issues, reducing clinical variation, testing new processes and leveraging an enterprise data warehouse. Click here to view this webinar today.
10 Questions on Post-Acute Care
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- Arizona Care Network Adopts Blockchain Technology Platform To Improve Clinical Outcomes, Transparency and Efficiency
- Remote Patient Monitoring for Chronic Condition Management: Leveraging Technology in a Value-Based System
- New Chart: What Are the Leading Health Conditions Targeted by Telehealth and Remote Patient Monitoring Programs?
- Stratifying High-Risk, High-Cost Patients: Benchmarks, Predictive Algorithms and Data Analytics
- Incentive Payments in Upside-only Medicare ACOs Have Increased Federal Costs
- Accountable Care Organizations: Benchmarks and Metrics
- Barbershop-Based Healthcare Study Lowers High Blood Pressure in African-American Men
- Montefiore SDOH Screenings Leverage Learnings from Existing Pilots
- Electronic Health Record Usability Issues Linked to Potential Patient Harm
- Community Health Partnerships: Alliances Aim to Improve Care Access
- Innovative Community Health Partnerships: Clinical Alliances to Reduce Health Disparities in Underserved Populations
- RWJBarnabas Health Creates Social Impact and Community Investment Department To Spearhead System-wide Emphasis on Social Determinants of Health and Local Investment Initiatives
- Nurses Can Play Greater Role in Improving Public Health
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