ZS Enhanced Provider Opportunity
ZS Enhanced Provider Opportunity is an advanced artificial intelligence and machine learning (AI/ML) solution that overcomes real-world data (RWD) biases and identifies the real potential of physicians and accounts.
ZS Enhanced Provider Opportunity
ZS Enhanced Provider Opportunity is an advanced artificial intelligence and machine learning (AI/ML) solution that overcomes real-world data (RWD) biases and identifies the real potential of physicians and accounts.
WHAT WE DO
Challenges we solve
Helps clients accomplish robust customer prioritization using real world data
WHAT WE DO
Challenges we solve
Helps clients accomplish robust customer prioritization using real world data
Scientifically removed biases
Scientifically removed biases
Mitigating any data capture bias like geographical blind spots or biases based on academic versus community centers
National-and-deeper level projection
National-and-deeper level projection
Projecting up to capture total patient population while mitigating claims under capture
Classification for missing HCP interactions
Classification for missing HCP interactions
Ability to classify patient interactions for HCP without any sales information
Enhanced downstream insights
Enhanced downstream insights
Finding the true potential of each account enables target refinement and robust opportunity assessment
HOW WE DO IT
ZS’s approach
ZS Enhanced Provider Opportunity solution identifies the true potential of each account, enabling better opportunity assessment. These insights are based on multiple data sources, proprietary algorithms and ZS’s pharma domain expertise.
HOW WE DO IT
ZS’s approach
ZS Enhanced Provider Opportunity solution identifies the true potential of each account, enabling better opportunity assessment. These insights are based on multiple data sources, proprietary algorithms and ZS’s pharma domain expertise.
Understanding of data capture biases
Understanding of data capture biases
Compare the patient capture at national, state, and account levels with benchmarks across various datasets to get in-depth understanding of the bias and gaps in patient capture.
Advanced AI to mitigate the data capture bias
Advanced AI to mitigate the data capture bias
Use machine learning techniques and data bias understanding to develop projection factors for each account, filling in the missing patient potential.
Validation mechanisms
Validation mechanisms
Take advantage of robust validation mechanisms for data enrichment at the national level and deeper.
