Wolters Kluwer, Health is introducing machine learning and artificial intelligence (AI) technology to its surveillance solution - Sentri7® - to predict healthcare-acquired infections (HAIs) such as Clostridioides difficile, or C. diff. Every day, clinicians are faced with the challenge of rapidly identifying and treating HAIs. As a result, hospitals are turning to advanced technology to meet this challenge and improve patient outcomes.
According to the Centers for Disease Control and Prevention’s Antibiotic Resistance Threats Report, in 2017, there were an estimated 223,900 cases of C. diff in hospitalised patients and 12,800 deaths in the United States. While significant progress has been made to reduce the number of infections and deaths caused by antibiotic-resistant infections, the number of overall people experiencing antibiotic resistance remains high. In addition, health systems are taking a closer look at how to tackle C. diff infections since poor-performing hospitals received reduced reimbursements through CMS Value-Based Purchasing (VBP) and Hospital Acquired Condition Reduction (HACRP) quality programs.
Wolters Kluwer’s Sentri7 clinical surveillance solution technology integrates with leading electronic health record (EHR) solutions to aggregate data and run evidence-based rules and alerts in real-time to provide insights on a patient population.
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