Jvion Releases Top 4 Ways Community Hospitals Can Use Predictive Analytics to Thrive

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Community hospitals are one of the most important providers within the US healthcare system. With new models of care coordination and reimbursement on the horizon, Jvion outlines how these facilities can use predictive analytics as a catalyst to success in the new era of healthcare.

"The advantages that come with being a community hospital can be magnified when predictive analytics are used"

Community hospitals are one of the most important and integral groups within the US healthcare system. These facilities, which tend to be independent, smaller in size, and more likely to include low-income patients in their population, are on the front lines of care for a large portion of the country. Now, with new approaches to care coordination, value-based billing, and at-risk models, these same facilities face the daunting task of accommodating an onslaught of mandates while maintaining operational health.

However, according to Jvion, these facilities are far from doomed. Because community hospitals are smaller and more closely aligned to the population around them, they may be better positioned in some ways to adapt to the latest models of care coordination. And with the emergence of predictive analytic solutions that are affordable, scalable, and accurate, community providers stand a real chance of thriving in this new era of healthcare.

In a recent interview, Jvion’s CEO Shantanu Nigam outlined the four ways community hospitals can apply predictive analytics to address challenges and take advantage of opportunities. According to Shantanu, the advantages that come with being a community hospital can be magnified when predictive analytics are used to prevent waste within the system and reduce patient suffering.

1. Reduce Cost: waste is a big issue for community hospitals. They are always looking for ways to create efficiencies and reduce cost. Additionally, at-risk and value-based models reward hospitals who eliminate waste while improving quality. By applying predictive analytics, these facilities can intervene and prevent adverse events such as hospital acquired conditions and post-operative complications; more effectively apply resources through more targeted infection prevention; and align organizational strategies including capital investments and staffing decisions based on predicted shifts in population health needs

2. Drive Physician Engagement: in general, community hospitals have a hard time recruiting and partnering with physicians. But physician engagement is key to reducing costs and improving health outcomes. Predictive analytics can be used to facilitate discussions with physicians and drive engagement. By providing real-time, patient-level risk insights that fit directly into the existing workflow, physicians can become advocates and a means to facilitate new operational and quality standards. And in some cases, a hospital’s willingness to integrate predictive technologies may help bolster perception among physicians who are looking for more progressive and technologically advanced practice environments.

3. Enable Care Coordination: community hospitals are defined in many ways by the population that they serve. Having access to leading population health predictive analytics can help these organizations target prevention and outreach activities. Predictive analytics can also help facilitate care coordination with local facilities such as nursing homes to help reduce readmissions and drive a patient-centered model of care. Moreover, population health level predictive analytics can provide unique insights into emerging health shifts so that the hospital and care facilities connected to it can better prepare for future health demands

4. Facilitate Better Communication and Standardization: there are advantages to being small. Unlike large systems made up of multiple, sometimes hundreds of facilities, a community hospital can more nimbly adopt new technologies. Because of their relatively small size, community hospitals can more quickly gain alignment and drive standardization across specialties. This is a great environment for predictive analytics because insights can be shared quickly and care coordination can be more efficiently achieved across multiple departments and specialties. Additionally, communication can be streamlined so that identified risks and opportunities can be addressed promptly

To learn more about Jvion and their full suite of Big Data predictive analytic solutions and how they can be applied to community hospitals, please visit http://www.jvion.com.

About Jvion
Jvion is a healthcare technology company that develops software designed to predict and prevent patient-level disease and financial losses leading to increased waste. The company offers a suite of big-data enabled solutions that combine clinical intelligence with deep machine learning to help providers protect their revenues while improving patient health outcomes. Their objective is simple—stop the waste of resources and lives by predicting and stopping losses before they ever happen.


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Allison Alavi
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