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Integrating data and analytics into a process that promotes compliance and positive patient outcomes

Life science companies are often organized into discrete operational and business functions. Complex infrastructure and disparate reporting systems and platforms encourage a siloed approach to safety mitigation and compliance assurance, inspection, and audit.

Continuous readiness models offer alternative strategies for optimizing compliance effectiveness and efficiency across the enterprise. They help life sciences companies to uncover gaps and adopt proactive strategies that reduce costs and, ultimately, improve patient outcomes.

Migrating to one of these models requires companies to consolidate compliance management functions while also extending necessary program changes to all business and clinical operations. These actions are necessary to create visibility across the entire risk landscape. Until recently, it was easy for status-quo proponents to contend that continuous readiness would be too disruptive and expensive. But those arguments have become less compelling with the advent of new cloud-based platforms.

“Continuous readiness models have major benefits,” says George Pushchinsky, product owner for the ConvergeHEALTH Safety Life Sciences practice at Deloitte. “They help life sciences companies avoid noncompliance and improve operational efficiency while allowing resources to be reallocated to the most value-added tasks.”

Using the cloud allows companies to maintain budgetary discipline while establishing an enterprise-wide view of compliance risk. Affordability provides a competitive advantage for organizations that want to incorporate artificial intelligence, machine learning, predictive analytics, and other advanced technologies into their continuous readiness strategy.

Click here to watch episode 4 of this 4-part series.