Abstract
To address the Quintuple Aim of health care improvement, the profession of pharmacy is on the verge of a practice transformation that incorporates continuous learning from medication-related data into existing clinical and dispensing roles. The pharmacists' patient care process (PPCP) enables a learning pharmacy practice through the systematic and standardized collection of real-world medication-related data from pharmacists' patient care activities. A learning pharmacy practice continually generates data-powered discoveries as a byproduct of PPCP interactions. In turn, these discoveries improve our medication knowledge while upgrading our predictive powers, thus helping all people achieve optimal health outcomes. Establishing a practice management system connected to the PPCP means that data are generated from every PPCP interaction, combined with existing data, and analyzed by teams of pharmacists and data scientists. The resulting new knowledge is then incorporated into all future PPCP interactions in the form of predictions coupled to actionable advice. The primary purpose of a learning pharmacy practice is to combine the power of predictive modeling with evidence-based best practices to achieve and sustain population-level health improvements. This purpose is achieved by systematically optimizing individual medication use in an equitable manner on a global scale.