Guide Research Priorities by Accessing Raw Patient Data and Machine Learning Analytics
Capturing Objective Patient Data to Inform
Academic researchers can access raw, de-identified, GxP-compliant data for patient and population health studies with Innovative Precision Health (IPH). By leveraging IPH’s cloud-based analytics solution, researchers can retrieve invaluable quantitative measurements documenting patient performance and perceptions – all captured through a proprietary network of independent examiners conducting objective, multi-dimensional digital assessments.
Applications for Use in Designing Clinical Trials
IPH’s data analytics leverages quantitative, raw data for evaluating therapies, assessing value-based care plans, and maximizing the entire pharmaceutical lifecycle to deliver value at each stage across the continuum of care. By capitalizing on comparative efficacy research, both novel and existing therapies stand to benefit from outpatient-focused, data-driven decision-making to optimize value-based care.
Leverage Real-World Data for
Comparative Efficacy Research
By leveraging IPH’s real-world datasets and machine learning algorithms, researchers can analyze multi-domain patient performance data and explore actionable insights that can help optimize patient outcomes and quality of care.
Backed by evidence-based support for preemptive intervention, IPH’s algorithms and data can enable the identification of unmet patient needs through machine learning models that chart disease trajectories, and can provide recommendations for the long-term success of therapies.