How Predictive Modeling in Healthcare Boosts Patient Care
Topic: How Predictive Modeling in Healthcare Boosts Patient Care
Predictive modeling offers the potential for healthcare organizations to improve service delivery and patient outcomes — but what’s required for effective deployment?
Predictive analytics offers real-world benefits for healthcare providers. According to Health IT Analytics, for example, recent work from the National Minority Quality Forum has produced the COVID-19 Index, a predictive tool designed to help businesses, governments and health agencies anticipate potential pandemic surges.
Other uses include the ability to target prospective clients in critical moments during their healthcare journeys and to deliver truly personalized care that aligns with emerging patient-centric service models. According to Tuan Phan, founder of cybersecurity company Zero Friction and a member of the ISACA Emerging Trends Working Group, however, the biggest benefits of predictive analytics are reduced patient risk and lower overall costs. “If you can detect illnesses early,” he says, “metadata may indicate that the patient’s condition is deteriorating, allowing medical professionals to take action earlier, in turn driving lower risk to the patient and lower costs to the hospital.”
But what exactly is predictive analytics and modeling — and how do healthcare organizations apply this data-driven approach?
Research firm Deloitte offers a straightforward definition: “Predictive analytics can be described as a branch of advanced analytics that is utilized in the making of predictions about unknown future events or activities that lead to decisions.”
Unlike prescriptive analytics, which uses data sets to help streamline existing processes and improve operational performance, predictive frameworks use machine learning and artificial intelligence models to discover correlations across disparate data sources and provide actionable recommendations.
As Phan says, the power of prediction with data analytics is especially critical in medicine. “Medical treatment is an art,” he says. “While there is science behind it, decision-making is an art. An AI-driven model can help support decisions for doctors — and not just the model itself but also the sensors and devices that help collect medical data.”
Topic Discussed: How Predictive Modeling in Healthcare Boosts Patient Care
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