Wolters Kluwer, Health has announced that its Sentri7 clinical surveillance solution has been enhanced with artificial intelligence (AI) to identify patients at risk for Clostridioides difficile (C. diff) infection. The solution uses a highly advanced and validated algorithm to produce C. diff infection (CDI) risk scores for individual patients, empowering clinicians to proactively alter patient care to reduce risks for infection and improve outcomes.
Patients with C. diff infection are associated with longer lengths of stay, higher readmission rates, and higher mortality, making it a precarious and costly disease for hospitals. With Sentri7’s AI+ technology package, hospitals can now identify at-risk patients days earlier and prevent infection by addressing modifiable risk factors, such as high-risk antimicrobials and acid suppressants.
Wolters Kluwer piloted the technology, and early adopters such as Carilion Clinic quickly saw its value. Sentri7 helps break down data silos that may exist across hospital systems, close patient information gaps and overcome roadblocks that hinder real-time analysis of a patient condition. Sentri7’s predictive CDI algorithm tracks patients’ risk levels and automatically updates the score if a patient’s condition changes. This allows clinicians and pharmacists to address stage-specific risk factors and proactively thwart C. diff infection using established, evidence-based prevention practices.
To cultivate this validated AI model for assessing patient risk of C. diff infection more precisely, Wolters Kluwer assembled a team of physicians, epidemiologists, antimicrobial stewardship experts and data scientists to analyse millions of data inputs. The combination of data science expertise and expansive clinical knowledge at Wolters Kluwer contributed to its recent recognition by Frost & Sullivan as a Frost RadarTM global leader in artificial intelligence for healthcare IT.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.Click here to read the original press release.
Artificial Intelligence (AI) / Machine Learning (ML) / Natural Language Processing (NLP)
More News in this Theme