Andy Stankus, General Manager, Real World Evidence, Health Division
In May 2019, Kantar launched Claritis™ Solution, a breakthrough approach to real-world data analytics that links patient-reported outcomes (PRO) data and clinical (claims and EHR) data. In today’s highly fluid market environment, life sciences companies need information that’s highly accurate and timely to meet the needs of both patients and their product portfolios. Traditionally, acquiring the necessary data required companies to design and conduct large primary research studies or conduct multiple studies using different secondary data sources.
By utilizing Claritis Solution linked data, companies don’t have to wait for the evidence they need. Claritis provides an opportunity to examine the clinical view alongside the patient’s unique perspective, delivering significant benefits in both insights and efficiencies. And, it offers a HIPAA-certified approach for linking de-identified clinical data with de-identified survey data, highly accurate probabilistic matching, and linking software validated at error rates less than industry standards.
Furthermore, Claritis supports a host of evidence-generation scenarios, including: Providing payer agencies with the required evidence to support reimbursement decisions, supporting regulatory bodies that require evidence of real-world safety and effectiveness, and generating critical information that’s used by other healthcare stakeholders, including healthcare professionals, patients, and caregivers.
For example, one pharma client was able to analyze the effect of social determinants on standard of care in type 2 diabetes. In the past, this analysis only has been performed from patient surveys. However, by linking PRO data on HRQoL with EHR data on HbA1c testing helped to reveal the relationship between diabetes management and HRQoL within a single data source. The results from using Claritis helped to indicate that frequency of HbA1c testing is an indicator of disease burden and may reflect healthcare access, quality of care, and severity of disease.