Case Study: Harmonized Lab Data Analysis Helps Pharma Company Fight Rare Disease

Answering these key questions can take a considerable amount of time and resources using traditional methods. Multiple data sources must be contracted and managed while significant manual effort is required to ensure disparate data sets are harmonized, standardized, and compliant. All this must be completed before any analysis can be applied or insights derived.

Challenge: 

Traditional data analysis methods that relied solely on medical and prescription claims made identifying and targeting patients early in the disease cycle difficult.

Solution: 

Prognos Factor^Ⓡ repository of harmonized lab data and medical and prescription claims provided:

• Diagnostic specificity to identify and target rare disease patients more quickly and accurately
• Time savings and speed to data value from a single data source
• Weekly data updates for current patient insights

Results: 

Timelier and more granular data-driven insights enabled faster identifying and targeting potential rare disease patients and treating HCPs.