SAS® for Improved Health Outcomes

avtor: SAS Institute Inc.

AI-driven predictive health analytics that improve clinical and operational insights

SAS Institute Inc. - Global

SAS is the leader in analytics and artificial intelligence. Commercially active since 1976, we’re the founder, and future, of analytics.

Public health agencies, providers and insurers trust SAS to help them make sense of complex health data. SAS solutions support critical health insights in over 3500 health care settings and 640 public health offices in 50 countries. High-quality health care and innovative therapies -informed by analytics- are saving patient lives, optimizing treatment strategies and controlling costs. Our solutions help health payers and providers advance patient outcomes in the age of digital health.

SAS® for Improved Health Outcomes extends patient data with financial, operational and medical device information to leverage insights for faster decision-making and help improve patient outcomes. SAS® Health connects data across systems to generate new predictive insights for optimal care management.

Clinical outcomes

  • Analyze structured and unstructured clinical and operational data, including freeform notes and focus group transcripts, to uncover hidden insights on indications
  • Turn insight into evidence-based knowledge that can help you predict and improve outcomes
  • Use all data available to determine optimal treatment, focused on value-based care
  • Understand the clinical and nonclinical factors that affect readmissions.

Patient safety

  • Avoid medication, surgical and other interaction errors through increased data sharing
  • Analyze diverse data sources to predict and medically investigate patient safety signals
  • Identify patients that have higher risk of infection to optimize discharge planning
  • Predict and prevent avoidable readmissions.

Population / Member Health

  • Optimize prevention programs and patient outreach to mitigate risk of long-term chronic diseases and lower health costs
  • Use clinical data to adjust for acuity within provider populations, thus increasing adoption of a value-based care model
  • Simplify public health reporting & surveillance through modernized data infrastructures

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