Population Health Analytics

Gain deeper population insights for improving care delivery while containing costs.

How SAS Helps You Improve Population Health

High-quality health care is both safer and more cost-efficient. It saves patient lives, reduces the burden on hospitals and enables more patients to receive treatment. SAS helps you deliver better overall quality of care by reducing readmissions, improving health outcomes and increasing patient safety.   

Readmissions

  • Understand the clinical and nonclinical factors that affect readmissions.
  • Predict and prevent avoidable readmissions.
  • Identify patients that have higher risk of infection to optimize discharge planning.

Health outcomes

  • Analyze structured and unstructured clinical and operational data 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.

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 potential issues before they become a reality.

Why SAS® for population health?

Health decisions are becoming societal ones. SAS enables you to combine data from social determinants and the environment with health and genetic data, then apply advanced analytics with embedded AI to get tangible results – results you can act on to improve quality and outcomes, as well as plan health delivery for the future.

Understand individual patient risk

Use predictive analytics to anticipate less-optimal outcomes so you can tailor intervention strategies to specific patient needs.

Communicate with patients the way they prefer

Identify patient preferences, determine the best message or intervention, and predict the likelihood of patient compliance.

Provide the best possible patient care

Integrate clinical and real-world data to holistically evaluate the best care options at each patient interaction.

Accelerate intelligent outcomes

Use AI to automate processes, control costs and put the focus on patients. Image analytics, machine learning and natural language processing extract insights from large volumes of structured and unstructured content.

The aim is to develop multiple models in SAS in order to better inform parents, provide the best possible healthcare for babies for a better long-term neurodevelopmental outcome and to eventually apply it to other intensive care departments. UMC Utrecht logo Manon Benders Professor & Head of Neonatology UMC Utrecht