Table 2.

Comparison of the PPCP unfolding for an individual patient before and after the advent of a learning pharmacy practice

PPCP component	Current pharmacy practice	Learning pharmacy practice
Collect	Common, descriptive, and periodic measures Age Weight Sex Height Race Education Marital status Blood pressure HbA1c Depression score (e.g., PHQ-9)	Adds patient-specific, predictive, and fast-changing measures Disease-relevant pharmacogenes Remote drug and metabolite concentrations Real-time glucose monitoring with longitudinal trends Past 30-d physical activity level Past 30-d social engagement level Predict individual kidney disease risk Predict individual retinopathy risk
Assess	Analyze imprecise patient data Incomplete and out-of-date medication lists Interpret periodic and generic clinical markers Review patient-reported adverse effects Patient-reported efficacy Evaluate refill adherence metrics	Shifts to precise patient assessments Review complete and verifiable medication lists Interpret reliable and valid predictions of clinical outcomes Review adverse effects detected and communicated automatically Evaluate longitudinal patient drug concentrations
Plan	Ad hoc care plans Trying medications to determine what works Making periodic dose changes to titrate effect and minimize adverse effects Setting therapeutic goals on the basis of best-guess estimates of time to effect	Shifts to evidence-based care plans that go beyond medication use Accurately predict which medications are most likely to be safe and effective in advance of their use Dosing and dose titrations computed using evidence-based algorithms with precise tracking of patient-specific outcomes Recommending personalized diet, exercise, and healthy living with patient-specific plans Setting therapeutic goals using predictions and simulation based on detailed medication responses for thousands or more similar patients
Implement	Plans with mostly general and basic instructions Printouts on paper Websites Patient portals E-mail	Shifts to personalized plans with instructions supported by ongoing tailored messaging Automated text message alerts for dose reminders Triggers to measure patient-specific outcomes Motivational messaging focused on patient behaviors, beliefs, and predictions of message effectiveness
Monitoring/follow-up	In-person and infrequent monitoring inconsistent with care plans Periodic patient visits to the pharmacy Periodic surveys Infrequent laboratory testing Prescription refill activity	Shifts to remote, ongoing monitoring driven by care plans Communication with pharmacists triggered by problems detected automatically Automated sensing of key clinical measures (e.g., blood pressure, glucose) Adherence estimates based on continuous drug concentrations or predictions of anticipated effects

Abbreviations used: Hb, hemoglobin; PHQ, patient health questionnaire; PPCP, pharmacists’ patient care process.