~ James Reed, PharmD, Chief Information Officer
Conway Regional Medical Center
Why Customers Choose Sepsis Monitor
Identify
Sophisticated, evidence-based clinical intelligence.
Sepsis Monitor's clinically maintained algorithms and clinical natural language processing (NLP) analyze a broad cross-section of patient data, including clinical notes. Alerts fire only for those patients who truly have sepsis. A study published in a peer-reviewed journal found that by identifying sepsis early and accurately and providing patient-specific guidance at the point of care, hospitals can reduce sepsis-related mortality by 53%.
Alert
Deliver trustworthy alerts directly to your clinical workflow.
Studies show CDS tools integrated with EHR identify patients with symptoms that mimic sepsis to reduce false alerts. Sentri7 Sepsis Monitor uses sophisticated technology to process discrete data from the EHR, including using cNLP processing to extract valuable patient information from unstructured clinical notes. Evidence-based algorithms analyze patient data continuously, monitor trends and assess all data in the context of the patient’s clinical status and co-morbid conditions that mimic sepsis.
Monitor & Respond
Optimize patient care and improve SEP-1 measure performance
Measure
Transform data into action and achieve top-tier SEP-1 performance.
Sepsis Monitor’s analytics provide a comprehensive view of sepsis program performance. Intuitive dashboards showcase CMS quality performance metrics for your organization and help reduce practice variation by identifying gaps in CMS SEP-1 bundle compliance. The solution’s Alert Response dashboard provides a comprehensive view of clinician action so you can educate teams, reduce practice care variation and improve outcomes.
How Sepsis Monitor Works
Empowering care teams to proactively manage sepsis leads to sustained SEP-1 performance and better outcomes.
Sepsis Monitor provides continuous 24/7, automated clinical surveillance of a hospital’s patient population to find patients. Clinically maintained algorithms, clinical Natural Language Processing (cNLP), and evidence-based content are used to detect sepsis and manage patient care throughout their stay and staff transition.
Sepsis Insight Articles
How to build a business case for your hospital's sepsis program
Evaluating which sepsis surveillance solution is right for your hospital