MedicalResearch.com Interview with:
CEO of Loopback Analytics
MedicalResearch.com: What is the background for Loopback Analytics? What are the problems Loopback Analytics is attempting to mitigate?
Response: Loopback Analytics (Loopback) is a Software-as-a-Service company that provides event-driven population health management. Founded in 2009, Loopback integrates and manages diverse data sources to support predictive analytics and intervention solutions to address health reform reimbursement challenges with the goal of achieving the Triple Aim – better care, better health and lower costs.
Loopback enabled intervention solutions address key challenges associated with value-based care, such as reducing avoidable hospitalizations, high emergency department utilization, medication adherence and optimization of post-acute care networks.
MedicalResearch.com: How does Loopback Analytics identify at-risk patients? What types of institutions and providers can benefit from your analyses?
Response: Loopback integrates both real-time and historical data across care settings. Our population engine proactively identifies at-risk patients. We collaborate with our clients to leverage their clinical expertise, and extend those insights through the application of machine learning algorithms to generate predictive analytics. In addition to client supplied data, Loopback also leverages third-party medication data, public data and robust historical data sets such as the Standard Analytical Files from CMS to identify care patterns and refine our targeting and prediction models.
Our clients include hospitals, health systems, post-acute care providers, community-based organizations and behavioral health service providers.
MedicalResearch.com: How does the information provided by Loopback Analytics improve patient care and reduce costs?
Response: Pervasive throughout our platform and solutions is the concept of ‘closing the loop in healthcare.’ The data flowing through our platform enables a 4-step learning loop process to drive continuous improvement:
• Identify at-risk patient populations through predictive analytics;
• Match patients with appropriate interventions;
• Engage with patients and/or caregivers; and
• Evaluate the effectiveness of care strategies and interventions through interactive dashboards.
Loopback’s population engine utilizes predictive analytics to identify at-risk populations based on client objectives. Identified patients are then matched to a portfolio of interventions to mitigate those risks. Patient interventions may be managed within Navigator, Loopback’s secure online portal, or managed outside of Navigator in native electronic medical records (EMRs). Through interactive dashboard reporting, outcomes are evaluated relative to clinical, operational and financial objectives to determine the effectiveness of care strategies and drive continuous improvement.
MedicalResearch.com: Is there anything else you would like to add?
Response: We continue to concentrate our efforts on key challenges that are critical to succeeding in the era of value-based care:
• Medication Adherence
• Post-Acute Care Networks / Bundled Payments and
• High Utilizers / Coalitions
BIO: Neil Smiley, Founder and CEO, Loopback Analytics
Neil Smiley, a serial entrepreneur with a passion for transforming industries with data-driven solutions, founded Loopback Analytics in 2009 to deliver an advanced Software-as-a-Service platform healthcare providers can use to prevent costly readmissions. The Loopback Analytics team currently works with the largest pharmacy, hospitalist group, health system, payer and senior housing provider in the nation, providing proven intervention solutions that improve clinical outcomes and reduce the total cost of care. Prior to founding Loopback Analytics, Smiley launched Phytel, a population health solutions company that was successfully sold to a VC firm. Smiley began his career as an Accenture consultant and later as a partner with EY, working with Fortune 1000 clients. Smiley holds a computer science degree from Dartmouth College.
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