Montefiore uses predictive analytics to provide 'whole-person care'
New York-based Montefiore Medical Center serves a population of 3.1 million in the Bronx and Westchester County. A large number of its patients – more than 80% of them – rely on Medicare or Medicaid for care.
Montefiore’s strategic goals include member satisfaction, improving prevention quality indicators, such as emergency department utilization, and preventative care and chronic-condition management, said Vanessa Guzman, then the associate vice president of Quality and Network Management at Montefiore, during a recent HIMSS20 Digital session.
These goals are achieved through the provision of “whole-person care,” as Guzman described it.
“In addition to treating a person’s immediate health needs,” said Guzman during the talk, AI-Supported Population Health’s Impact on Value-Based Care, providers should understand “their health status and interactions with the health system are governed oftentimes by their life circumstances.”
“Patient needs extend far beyond the clinical setting and longitudinally over time,” said Shara Cohen, vice president of customer experience for clinical effectiveness at Wolters Kluwer Health.
Montefiore’s technology infrastructure, Cohen said, “allows them to … support these very personal and individualized activities at scale.”
As Guzman explained, Montefiore uses a predictive analytics tool – based on integrations of claims, electronic health records and self-reported data – to segment populations and look for rising risk among patients.
It also employs navigators in the emergency department to screen patients at that point of care, flagging them in Montefiore’s EHR, Epic, and creating a discharge plan that involves potential connection with community-based providers.
In both models, the patient identification triggers a number of actions. Patients with a high rate of utilization are connected with care managers; functionally ill patients are directed to digital, self-coached programs through tools like Emmi; and the health system automatically calls the so-called worried well, collecting data and using natural language processing to connect them with the appropriate preventative health services.
“Based on that segmentation, [we] deploy our human resources, our technology resources, to manage those segments as [efficiently] as possible,” said Guzman.
The digital interventions, said Guzman, have led to improvements in the numbers of potentially preventable readmissions and preventable emergency department visits. They’ve also spotlighted the need for further improvement in preventable admissions.
“Technology alignment is the key,” she said. “It’s important that there is centralization and governance around the selection … that we pull together to service our patients. We have to prioritize our process.”
“We each have a role in healthcare,” she continued. “It’s important to understand our roles and responsibilities so we can be effective at our work.”
Kat Jercich is senior editor of Healthcare IT News.
Twitter: @kjercich
Healthcare IT News is a HIMSS Media publication.
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