BackgroundPoor adherence to medication regimens and medical record inconsistencies result in incomplete knowledge of medication therapy in polypharmacy patients. By quantitatively identifying medications in the blood of patients and reconciling detected medications with the medical record, we have defined the severity of this knowledge gap and created a path toward optimizing medication therapy.Methods and findingsWe validated a liquid chromatography-tandem mass spectrometry assay to detect and/or quantify 38 medications across a broad range of chronic diseases to obtain a comprehensive survey of patient adherence, medical record accuracy, and exposure variability in two patient populations. In a retrospectively tested 821-patient cohort representing U.S. adults, we found that 46% of medications assessed were detected in patients as prescribed in the medical record. Of the remaining medications, 23% were detected, but not listed in the medical record while 30% were prescribed to patients, but not detected in blood. To determine how often each detected medication fell within literature-derived reference ranges when taken as prescribed, we prospectively enrolled a cohort of 151 treatment-regimen adherent patients. In this cohort, we found that 53% of medications that were taken as prescribed, as determined using patient self-reporting, were not within the blood reference range. Of the medications not in range, 83% were below and 17% above the lower and upper range limits, respectively. Only 32% of out-of-range medications could be attributed to short oral half-lives, leaving extensive exposure variability to result from patient behavior, undefined drug interactions, genetics, and other characteristics that can affect medication exposure.ConclusionsThis is the first study to assess compliance, medical record accuracy, and exposure as determinants of real-world treatment and response. Variation in medication detection and exposure is greater than previously demonstrated, illustrating the scope of current therapy issues and opening avenues that warrant further investigation to optimize medication therapy.

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The implementation of the quality-assessment dashboard, educational sessions, and individualized performance feedback significantly improved pharmacist order-verification adherence to institution-derived, medication-related guidelines and policies and the documentation rate of nonadherent orders.

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Introduction Many oncology infusions are provided in hospital-based infusion centers. With hospital-based infusion centers seeing increased volumes, patient wait times continue to be a priority. Extended wait times for oncology infusions have been shown to lead to patient dissatisfaction. Methods Advanced Preparation of oncology infusion medications allows pharmacy to verify and prepare specific medications the day before a patient’s infusion appointment. Our study targeted lower cost, commonly used medications to prepare in advance. Data analyzed included turnaround time (TAT), medication waste, and oncology infusion preparation volumes. Implementation took place in two phases to allow time for the healthcare team to adjust to the new workflow. Phase I medications include a small amount of medications prepared manually by pharmacy technicians. Phase II medications included all phase I medications plus additional medications that were compounded in the intravenous (IV) robotic compounding system. Results Our study demonstrated significant decrease in median TAT for medications prepared in advance. 537 infusions were prepared using the Advanced Preparation module with a median TAT of 24.2 minutes (IQR, 18.0–34.0). The pre-implementation median TAT was 45.0 minutes (IQR, 36.0–56.0), which represents a decrease of 20.8 minutes (46.2%) following implementation of the program, (p<0.001). There were a total of 149 advanced preparation doses that were wasted (21.7% of doses). Conclusion We have seen a statistically significant reduction in TAT for Advanced Preparation medications. Low volume of Advanced Preparation medications compared to total infusion volume limited impact on overall TAT.