In today’s improvement-driven healthcare environment, organizations must ensure that improvement measures help them reach desired outcomes and focus on the opportunities with optimal ROI. With data science-based analysis, health systems leverage machine learning to determine if improvement measures align with specific outcomes and avoid the risk and cost of carrying out interventions that are unlikely to support their goals.
There are four essential reasons that insights from data science help health systems implement and sustain improvement:
Measures aligned with desired outcomes drive improvement.
Improvement teams focus on processes they can impact.
Outcome-specific interventions might impact other outcomes.
Identifies opportunities with optimal ROI.