Identifying opportunities for improvement at the system level through variability analysis of utilization, outcomes, cost for populations of interest as well as by quantifying the variability
Evaluating and prioritizing proposed new initiatives for process change based on the likely impact on outcomes, cost, social equity etc.
Personalized precision medicine
Evidence-based guidelines – working at the patient and population level to determine which patients meet inclusion criteria for which evidence-based guidelines, tracking compliance with the diagnostic and treatment recommendations for each guideline to determine which patient’s care is compliant, providing feedback to physicians about which patient’s care could be improved
AI-based machine learning predictive modeling – determine which patients are at risk for specific health outcomes of interest so that they can be started on proven treatments or preventative strategies earlier, thereby improving outcomes and reducing downstream healthcare system expenditures