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Pharmacy Analytics

Comparative Rapid Cycle Analytics

Agilum’s Comparative Rapid Cycle Analytics™ solution enables the leap to value-based care through a proprietary engine that compares treatments, drugs, processes, and costs to help identify the patterns that achieve the best outcomes to reduce the total cost of care.

Patient Data Intelligence Platform™ (PDIP™)

A longitudinal patient database with more than 130 million records that provides clinical insights for treatment and business decisions

P&T Value

An innovative pharmacy executive team that will provide expert guidance to help transform your decision-making process

Comparative Rapid Cycle Analytics™ (CRCA™)

A revolutionary tool that empowers pharmaceutical leaders to make informed decisions based on real-world evidence

Finally. Objective, real-world evidence for your P&T committee

As drug prices have skyrocketed, decisions about which drugs make it on the formulary have become increasingly important — and scrutiny and accountability have increased. Now, there is a solution that takes real-time data and turns it into real-world evidence you can use to make those decisions with confidence.

White Paper

Longitudinal data holds the power to improve care and reduce infection rates in hospitals, aid in accurate diagnosis and treatment decisions, and even reduce the cost and time involved in pharmaceutical research and development — if only we are willing to listen.


When it comes to hospitals deciding which medications to purchase, as well as determining which ones remain on the formularies, and which have the most value, the method is largely static and antiquated, having changed very little since the 1980s. Generally speaking, Pharmacy and Therapeutics committees, consisting of internal hospital leadership, vote to collectively decide which medications should be added or removed.

The problem with this method is that the decisions are largely subjective – influenced by anecdotal evidence about which drugs are most effective, which ones patients “prefer,” group consensus, relationships with sales reps, brand loyalty, and other unscientific factors.