Christian M Sperber, Suren R Samarasinghe, Grace P Lomax Patient Connect Limited, Guildford, UK Background: The Medication Possession Ratio (MPR) is a ubiquitous and central measurement for adherence in the health care industry. However, attempts to standardize its calculation have failed, possibly due to the opacity of a single, static MPR, incapability of directly lending itself to a variety of studies, and challenges of comparing the value across studies. This work shows that the MPR strictly depends on the length of the time interval over which it is measured as well as on the dominant dispense quantity for short time intervals. Furthermore, removing a proportion of the patient cohort based on the number of acquisitions may also have a severe impact on the MPR. Therefore, it is suggested that the MPR is represented as a trend over a range of time intervals. To this end, an upper and lower bound of the MPR trend is developed with an upper bound acknowledging patients who change their treatment and the lower bound acknowledging patients who discontinue their treatment.Purpose: Introducing a representation of the MPR value as a trend rather than a static number by developing a quantitative description of an upper and lower bound of the MPR trend, while shedding light on the impacts on prefiltering the patient cohort.Patients and methods: Anonymized patient-level data was utilized as an example for a suggested calculation of an upper and lower bound of the MPR.Results: Representation of the MPR for a predefined time interval precludes a reliable MPR assessment. A quantitative approach is suggested to generate an upper and lower trend of the MPR while emphasizing the impact on removing patients with a limited number of acquisitions.Conclusion: An upper and lower trend makes the MPR more transparent and allows a better comparison across different studies. Removing patients with a limited number of acquisitions should be avoided. Keywords: MPR, adherence, pharmacy claims, quantitative calculation, compliance, administrative claims data