Is P&T Ready to Add Rapid Cycle Analytics to Formulary?

Area of Science:

• Health Informatics
• Pharmacoeconomics
• Clinical Analytics

Background:

• The Pharmacy and Therapeutics (P&T) Committee manages formulary additions, often requiring extensive manual review of drug monographs and patient charts for medication use evaluations (MUEs).
• Traditional MUE processes consume significant clinical resources and time, potentially delaying critical decisions and impacting patient care.
• Optimizing the medication evaluation process is crucial for efficient healthcare management and formulary decision-making.

Purpose of the Study:

• To evaluate a novel approach using rapid cycle analytics and real-world evidence to enhance the medication evaluation process.
• To improve formulary decision-making while reducing the time burden on clinicians.
• To assess the effectiveness of intravenous acetaminophen (IV APAP) for total hip arthroplasty (THA) and total knee arthroplasty (TKA) procedures.

Main Methods:

• Implemented rapid cycle analytics, a new methodology for evaluating medication value.
• Assessed the effectiveness of IV APAP in THA and TKA patients, correlating it with opioid utilization, length of stay, and post-anesthesia care unit (PACU) time.
• Partnered with an external analytics expert to organize and normalize internal data, utilizing a large external dataset (over 130 million patients) for reference.

Main Results:

• The study successfully demonstrated the value of IV APAP in THA and TKA procedures.
• The rapid cycle analytics approach allowed for a robust and time-efficient assessment of medication effectiveness and value.
• Significant clinical resources were freed up from MUEs, allowing for more direct patient care.

Conclusions:

• The novel approach using rapid cycle analytics and real-world evidence significantly improved the medication evaluation process.
• This data-rich analytical model enhances the depth of assessments and optimizes the allocation of clinical resources.
• This methodology provides a foundation for future real-time formulary and drug selection decisions using Artificial or Augmented Intelligence (AI).