Primary medication nonadherence calculation method specifications impact resulting rates.

BACKGROUND: Previous literature has illustrated a wide range of primary medication nonadherence (PMN) rates due to inconsistent calculation methods and parameters, but the impact of parameter specifications on PMN rates has not been assessed. OBJECTIVES: The objective of this study was to evaluate the impact of lookback window (LBW), duplicate window (DW), and fill window (FW) specifications on PMN rates in patients prescribed specialty self-administered oncology medications. METHODS: This was a single-center, retrospective cohort analysis. Patients receiving a new electronic specialty oncology prescription January-December 2018 were included; excluded if re-routed to an external pharmacy within 2 days, fell within a DW, or cancelled within a FW. Twenty-four methods were used to calculate PMN based on combinations of the following parameters: (i) absence of prior specialty self-administered oncology medication fill within LBW (90, 180 days); (ii) absence of a duplicate prescription within DW (2, 7, 30 days); and (iii) sold status within FW (14, 30, 60, 90 days). For each method, PMN was calculated as the number of unsold prescriptions within the FW divided by all eligible prescriptions. RESULTS: We evaluated 4,482 prescriptions, resulting in PMN ranging from 16% to 23%. Patients were commonly male (53%) and white (83%), with a median age of 64 years (interquartile range, IQR, 54, 72). Increasing the LBW from 90 to 180 days resulted in exclusion of 72 (2%) prescriptions and minimally impacted PMN rates. Most duplicate prescriptions (87%) occurred within two days of original prescription and PMN rates were minimally affected by DW. Most fulfilled prescriptions were filled within FW 30 days, 98% with a method of LBW 180, DW 2, and FW 30. Adjusting the FW consistently impacted PMN rates. CONCLUSIONS: Because various PMN definitions can significantly impact results, a thorough explanation of all parameter specifications should be reported in research using PMN.

Preformulation Studies on Piperlongumine.

Piperlongumine is a natural alkaloid extracted from piper plants which has been used traditionally for the treatment of certain diseases. This compound shows interesting in vitro pharmacological activity such as selective anticancer activity and higher cytotoxicity than methotrexate, cyclophosphamide and adriamycin on breast, colon, and osteosarcoma cancers, respectively. However, the physicochemical properties for this compound have not been well characterized. In this research, preformulation studies for piperlongumine have been performed to determine factors which influence solubility and stability which, in turn, can be used to assist future formulation development. The solubility of piperlongumine in water was found to be approximately 26 µg/ml. Using 10% polysorbate 80 as a surfactant resulted in a 27 fold increase in solubility. Cosolvents and cyclodextrins afforded concentrations of 1 mg/ml and higher. The pH degradation rate profile for piperlongumine at various temperatures shows significant instability of the drug at pH values ≥ 7 and 3, and maximum stability around pH 4. It was estimated that it would take approximately 17 weeks for piperlongumine to degrade by 10% at 25°C, pH 4. Additionally, piperlongumine showed marked photo-degradation upon exposure to an ultraviolet light source, especially in aqueous media.

E-prescription errors and their resolution in a community compounding pharmacy.

Despite apparent benefits, electronic prescribing systems still face numerous challenges. Errors associated with electronic prescriptions can often lead to workflow disruptions. This may be particularly disruptive in smaller, independent community pharmacies that may not have the staffing resources to adequately cope with an increase in required correspondence with prescriber offices. The objective of this study was to follow-up on a 2012 quality-improvement project evaluating electronic prescription error type, error rate, and time between error discovery and resolution in an independent compounding pharmacy. The study design was quality improvement with descriptive data. Data were collected over a four-week period during which time the pharmacists completed a data collection form for each electronic prescription received that contained an error. Percentages were calculated for error type, error rate, and error resolution type. Using range, mean, and standard deviation, time until error resolution was reported. In the four-week study period an e-prescribing error rate of 23.2% was identified (32 errors identified in 138 e-prescriptions). The most frequent error was an invalid electronic prescription signature for a controlled substance (31.3%, n = 10). The most commonly used error resolution method was a phone call to the physician (59%, n = 19). The average time to resolve the most frequent error type was 10.30 hours with a standard deviation of 18.18 hours. The results show a 40% decrease in the number of e-prescription errors identified compared to the quality-improvement evaluation done in the same pharmacy one year ago. E-prescription errors continue to disrupt workflow and impede patient care but perhaps at a lower rate. Pharmacies should implement a quality-improvement review process to help identify solutions to systems issues.