Population Health Analytics

Get data-driven insights for improving health outcomes and cost-effectiveness aligned with the Triple Aim.

How SAS Helps Improve Population Health

Integrate health and nonhealth data to guide whole person care, as well as community programs that reduce health disparities. Improve quality of care and health outcomes by integrating analytics within your 360-degree view of patients, members and clients. Gain insights at all levels – from individual care, to cohorts, to full populations – to inform policy for better communities. SAS enables you to expand access to care, improve health outcomes and increase patient safety.

Health 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.

Whole person care

  • Provide a more complete, accurate picture of client services and the impact on human and financial outcomes across health and nonhealth services.
  • Understand overall community needs, as well as contextual factors that can become barriers to care.
  • Forecast demand for services needed by high-risk populations, and measure program effectiveness

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 risk

Use predictive analytics to anticipate less-optimal outcomes so you can tailor intervention strategies to the needs of individuals, including patients, members, clients and policymakers.

Communicate with people the way they prefer

Identify patient/member preferences, determine the best message or intervention, and predict the likelihood of adherence.

Provide the best possible care

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

Accelerate intelligent outcomes

Use AI to automate processes, control costs and put the focus on people. 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 University Medical Center Utrecht

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