By Christine Kern, contributing writer
Solutions integrate patient-level data from EHRs to assess risks and other factors.
At HIMSS17 in Orlando, IBM Watson Health unveiled a series of value-based cloud solutions aimed at helping providers, health plans, and employers better manage their healthcare costs and quality. The solutions integrate patient-level data from EHRs and other sources to create a better picture of patient populations, risk factors, and other red flags at the individual, group, and population level in order to improve patient outcomes under the new value-based payment models.
“Healthcare organizations are operating in a complex and fluctuating business environment, one in which the insights they need to succeed can be hidden amidst an avalanche of disparate and siloed data,” says Deborah DiSanzo, General Manager of IBM Watson Health.
The solution integrates the capabilities of Watson Care Manager, Truven Health Analytics, Phytel, and Explorys. The new applications, available later this year, will include: Provider Performance Manager, Engagement Manager, Bundled Payments Forecasting and Management, and Custom analytics.
“We believe the large scale movement to value-based models for care delivery and reimbursement mean healthcare providers and payers must now adopt different approaches to managing population health risk,” explains Mike Boswood, General Manager of Value-Based Care, IBM Watson Health. “The value-based care solutions we are announcing today are designed to give hospitals, health plans, and self-insured employers the insights they need to understand how any one clinical or administrative decision can cascade throughout an organization and can potentially have dramatic impacts on both the cost and quality of care.”
Watson Health also announced an agreement with Atrius Health to develop a cloud-based service to improve the doctor-patient experience. The non-profit health system has entered into collaboration with IBM Watson Health to conduct research and provide a holistic view of the multiple influences on an individual’s health, including social determinants that could support shared decision making between doctors and patients.