Medication adherence still remains an unsolved problem in patient care management, especially in chronic diseases, where polypharmacy constitutes an additional issue to manage. To help patients to take their prescribed medications correctly, an appropriate quantification of adherence to medications is of paramount importance, particularly in the case of patients taking multiple medications for the same or multiple conditions. For these patients, measuring adherence is more complex, since medication can be substituted or added over time. Evidence shows that adherence to medications is often misclassified and poorly quantified, and this can lead to erroneous conclusions regarding the efficacy and/or safety of treatments, which will ultimately impact patient care.
Much effort has gone into devising methods for reliably quantifying patients’ adherence to prescribed medications, especially those medications intended for long-term use against various major chronic diseases. Still, different methods differ with regard to their validity, reliability, and sensitivity; and none of them provide fully robust data. Moreover, what is measured is not the same across different methods. Rates of prescription refills, for instance, measure medication acquisition, which is different from medication consumption, measured by pill counts, physiological markers, or electronic medication monitors. Given a set of data, simple variations in the metrics used to measure medication adherence can lead to widely different conclusions. Furthermore, if what is measured is not the same across different methods, and this is not taken into account in the analyses made, conclusions regarding adherence to medications can be erroneous and/or not significant for patient care.
Medication adherence should thus be quantified by using a clear and precise taxonomy, and against meaningful metrics which should be reliable, coherent with the three components of medication adherence, implementable on a large scale, and allow tracking over time. This information can be useful for all of those involved in patient care, by providing a clearer and more accurate picture of how patients are actually taking their prescribed medications, and hence by allowing the design of more effective strategies to help them to overcome the barriers to medication use.
In this Research Topic we are looking for original research and/or reviews where different methods and/or metrics are used to measure medication adherence in the same set of patients, and which analyze the differences in validity, reliability, and sensitivity of such differences in method and/or metrics, and their implications in the conclusions drawn from such analyses. This research can also be translated into other areas of knowledge, where there is a need to improve a particular feature and/or behavior. In addition, we are also looking for experiences from other fields of expertise in research methods that can be overlapped with research on medication adherence, allowing the reduction in the existing gap on what can patients benefit from medications and they’re actually benefiting.
Medication adherence still remains an unsolved problem in patient care management, especially in chronic diseases, where polypharmacy constitutes an additional issue to manage. To help patients to take their prescribed medications correctly, an appropriate quantification of adherence to medications is of paramount importance, particularly in the case of patients taking multiple medications for the same or multiple conditions. For these patients, measuring adherence is more complex, since medication can be substituted or added over time. Evidence shows that adherence to medications is often misclassified and poorly quantified, and this can lead to erroneous conclusions regarding the efficacy and/or safety of treatments, which will ultimately impact patient care.
Much effort has gone into devising methods for reliably quantifying patients’ adherence to prescribed medications, especially those medications intended for long-term use against various major chronic diseases. Still, different methods differ with regard to their validity, reliability, and sensitivity; and none of them provide fully robust data. Moreover, what is measured is not the same across different methods. Rates of prescription refills, for instance, measure medication acquisition, which is different from medication consumption, measured by pill counts, physiological markers, or electronic medication monitors. Given a set of data, simple variations in the metrics used to measure medication adherence can lead to widely different conclusions. Furthermore, if what is measured is not the same across different methods, and this is not taken into account in the analyses made, conclusions regarding adherence to medications can be erroneous and/or not significant for patient care.
Medication adherence should thus be quantified by using a clear and precise taxonomy, and against meaningful metrics which should be reliable, coherent with the three components of medication adherence, implementable on a large scale, and allow tracking over time. This information can be useful for all of those involved in patient care, by providing a clearer and more accurate picture of how patients are actually taking their prescribed medications, and hence by allowing the design of more effective strategies to help them to overcome the barriers to medication use.
In this Research Topic we are looking for original research and/or reviews where different methods and/or metrics are used to measure medication adherence in the same set of patients, and which analyze the differences in validity, reliability, and sensitivity of such differences in method and/or metrics, and their implications in the conclusions drawn from such analyses. This research can also be translated into other areas of knowledge, where there is a need to improve a particular feature and/or behavior. In addition, we are also looking for experiences from other fields of expertise in research methods that can be overlapped with research on medication adherence, allowing the reduction in the existing gap on what can patients benefit from medications and they’re actually benefiting.