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Health organizations are increasingly leveraging data and technology to address population health challenges. Predictive analytics plays a crucial role in this effort, by providing the ability to forecast health outcomes and target interventions accordingly. A new generation of companies are at the forefront of this movement, using data analytics to identify high-risk older adult patients and enable targeted interventions to mitigate both medical and social factors that drive health risks. By analyzing electronic health records, claims data, and other sources, they can predict patient outcomes, such as hospitalization risk, and enable healthcare providers to take proactive steps to prevent adverse events. This data-driven approach has the potential to significantly improve health outcomes, reduce healthcare costs, and enhance the overall quality of care for vulnerable populations.
Though population health has been a concern for a long time, it really became a topic at the forefront of healthcare with the COVID-19 Pandemic. Through the pandemic, we not only put more emphasis on being able to track the spread of illnesses by location but also on identifying the challenges a community faces in staying safe and healthy. For example, our quick push towards a virtual world highlighted the struggles rural communities face with reliable network coverage that is needed to achieve a virtual world.
Continue reading at healthcareittoday.com
For decades, niche automation and piecemeal software solutions have been deployed by health systems to make electronic health records (EHRs) more effective in delivering care, monitoring quality, and …
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