2018
DOI: 10.1002/phar.2178
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Investigating the Potential for Bias When Using a Widely Accepted Medication Adherence Measure to Predict Mortality

Abstract: Investigators using PDC or similar proxy measures should carefully consider the temporal relationship between adherence exposure and clinical outcomes when the outcome event affects the adherence measurement.

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Cited by 2 publications
(3 citation statements)
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“…8 Our study advances the current understanding of methods for measuring drug exposure by taking common details such as overlaps in prescriptions and hospital stays into account which has not been well defined previously using administrative data. 6,30,31 As ESRD patients commonly take >7 prescription medications on a single day, are hospitalized frequently (78%) with a median length of hospital stay of 7 days, and have high mortality rate, our methods are particularly more comprehensive than previously reported adherence matrix. Therefore, if a study fails to incorporate frequent and prolonged hospitalizations in adherence measures, outcomes can be falsely misattributed to nonadherence.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…8 Our study advances the current understanding of methods for measuring drug exposure by taking common details such as overlaps in prescriptions and hospital stays into account which has not been well defined previously using administrative data. 6,30,31 As ESRD patients commonly take >7 prescription medications on a single day, are hospitalized frequently (78%) with a median length of hospital stay of 7 days, and have high mortality rate, our methods are particularly more comprehensive than previously reported adherence matrix. Therefore, if a study fails to incorporate frequent and prolonged hospitalizations in adherence measures, outcomes can be falsely misattributed to nonadherence.…”
Section: Discussionmentioning
confidence: 99%
“…32,33 Previous studies, which are used for calculating traditional MPR and PDC values, did not include full adjustments for overlapping refill periods, gaps in refill, and hospital stays. Some studies included hospitalization as a covariate in the final analyses only; 4,10,31,34,35 others adjusted for overlapping coverage days by moving the start date of overlapping prescriptions but failed to address the issue of refills of different strengths. [36][37][38] Only a select few studies attempted to account for hospital/institutional stays.…”
Section: Discussionmentioning
confidence: 99%
“…Calculation methods include medication possession ratio (MPR), proportion of days covered (PDC) or daily polypharmacy possession ratio (DPPR) 16 . The observation window, needed to calculate the adherence rate, can be defined in two ways: a prescription‐based approach, with the observation window starting when the medication is first dispensed and ending before the last dispensing, and an interval‐based approach using a predefined observation window 17 . Overall, a wide variety of methods have been described in literature, but to date there seems to be no golden standard method to quantify adherence using refill data.…”
Section: Introductionmentioning
confidence: 99%