Medication adherence is the process by which patients take their medication as prescribed and is an umbrella term that encompasses all aspects of medication use patterns. Patient adherence is a prerequisite for achieving the therapeutic outcome. Further, precise knowledge of medication intake is crucial for any evaluation of drug effectiveness. With the emergence of electronic records (in hospitals or clinics, at GPs or community pharmacies) and new technologies for electronic monitoring, medical data became electronically available and could deliver surrogate values of medication intake. Consequently, several estimates of adherence were generated with mathematical formulas (so called operationalization) applied to the data at disposal. Up to now, the arbitrary threshold value of 80% has been mostly used to classify patients into adherer and non-adherer, or the categories “good”, “fair” or “poor” adherence have been arbitrarily defined. To be a medical decision tool, cut-off points should be validated against clinical outcome.
In this Research Topic, we will focus on methods that operationalize adherence from electronic data that is, from medical records (prescription data), from pharmacy or administrative records (dispensing data) and from electronic devices (monitoring data). The medication can be single or multiple (polypharmacy) and the research can be theory or practice-based. The studies should investigate the relationship between a degree of adherence and health change in order to support the appropriateness of the cut-offs for a specific medication class or a disease.
Medication adherence is the process by which patients take their medication as prescribed and is an umbrella term that encompasses all aspects of medication use patterns. Patient adherence is a prerequisite for achieving the therapeutic outcome. Further, precise knowledge of medication intake is crucial for any evaluation of drug effectiveness. With the emergence of electronic records (in hospitals or clinics, at GPs or community pharmacies) and new technologies for electronic monitoring, medical data became electronically available and could deliver surrogate values of medication intake. Consequently, several estimates of adherence were generated with mathematical formulas (so called operationalization) applied to the data at disposal. Up to now, the arbitrary threshold value of 80% has been mostly used to classify patients into adherer and non-adherer, or the categories “good”, “fair” or “poor” adherence have been arbitrarily defined. To be a medical decision tool, cut-off points should be validated against clinical outcome.
In this Research Topic, we will focus on methods that operationalize adherence from electronic data that is, from medical records (prescription data), from pharmacy or administrative records (dispensing data) and from electronic devices (monitoring data). The medication can be single or multiple (polypharmacy) and the research can be theory or practice-based. The studies should investigate the relationship between a degree of adherence and health change in order to support the appropriateness of the cut-offs for a specific medication class or a disease.