Improving Patient Medication Adherence Metrics

Best Practices, LLC undertook this research to establish industry benchmarks around patient medication adherence rates. This report provides benchmarks for core performance metrics such as Fill Rates, Time to Fill, and Reimbursement Rates, as well as complex indicators like Adherence, Persistence, and Compliance Rates. This vital report also provides a special industry case study around oral adherence.

Study Snapshot

Best Practices, LLC engaged 27 leaders from 20 pharmaceutical and biotech companies in this research through a benchmarking survey.

Key topics covered in this report include:

• Tracking Basic and Complex Patient Medication Adherence Metrics
• Average Adherence Rates and Zone of Competitive Effectiveness
• Effective Data Sources for Adherence Metrics
• Oral Adherence Industry Case Studies

• Time to Fill Least Tracked: Of the raw metrics investigated in this study, Time to Fill was the least tracked metric behind Reimbursement Rate and Fill Rate.

• Average Adherence Rates: Average adherence rates for brands typically fall between 60% and 90%.

• Primary therapeutic area of the brands represented in the study
• Rare disease area representation in the study
• Dosing frequency of brands or treatments represented in the study
• Number of years the represented products or treatments have been approved in the market
• Methods of administration of represented brands
• Methods of distribution of represented brands or treatments
• Most critical challenges in improving adherence
• Total number of direct and indirect competitors for represented products
• Average annual list price (in USD) for represented brands
• Patient support hub readiness of represented brands
• Support provided to patients to help them overcome adherence barriers

• Adherence metrics tracked by benchmark participants – Fill Rate
• Adherence metrics tracked by benchmark participants – Time to Fill
• Adherence metrics tracked by benchmark participants – Reimbursement Rate
• Whether definition of Fill Rate metrics align with that of standard definitions used in this study
• Whether definition of Time to Fill metrics align with that of standard definitions used in this study
• Whether definition of Reimbursement Rate metrics align with that of standard definitions used in this study
• Average Fill Rates during launch phase and zone of competitive effectiveness
• Average Fill Rates during post-launch phase and zone of competitive effectiveness
• Current average Fill Rates and zone of competitive effectiveness
• Determination of prevalent factors for decisions not to fill
• Average Reimbursement Rates during launch phase and zone of competitive effectiveness
• Average Reimbursement Rates during post-launch phase and zone of competitive effectiveness
• Current average Reimbursement Rates and zone of competitive effectiveness
• Average Time to Fill (in weeks) during first 3 months of launch and zone of competitive effectiveness
• Average Time to Fill (in weeks) 1-year post-launch and zone of competitive effectiveness
• Current average Time to Fill (in weeks) and zone of competitive effectiveness
• Effective techniques to develop patient trust
• Average Fill Rates during each of the launch phases
• Data collection means for Fill Rate, Reimbursement Rate, and Time to Fill metrics – Total benchmark class
• Data collection means for Fill Rate metrics – Rare disease segment
• Data collection means for Reimbursement Rate metrics – Rare disease segment
• Data collection means for Time to Fill metrics – Rare disease segment
• Effectiveness of data sources in providing accurate data – Total benchmark class
• Effectiveness of data sources in providing accurate data – Rare disease segment

• Tracking of Adherence metrics and the alignment of these metrics with that of standard definitions used in this study
• Tracking of Persistence metrics and the alignment of these metrics with that of standard definitions used in this study
• Tracking of Compliance metrics and the alignment of these metrics with that of standard definitions used in this study
• Types of adherence metrics collected by benchmark participants
• Average Adherence Rates and zone of competitive effectiveness
• Interview narrative around attributions to low adherence rates
• Persistence levels
• Interview narrative around strategies to make HCPs aware of barriers
• Average Compliance Rates and zone of competitive effectiveness
• Interview narrative around solutions for reducing patient-driven noncompliance

• Oral agents for cancer treatment
• Case example around increasing patient connection using digital medicine technology
• Case example around open digital diabetes ecosystem that revolves entirely around people with diabetes
• Case example around helping patients adhere to treatment plans by combining smart digital design with existing inhalers
• Case example around a three-step approach to improve patient adherence