Introduction: Favipiravir is a repurposed drug to treat coronavirus 2019 . Due to a lack of available real-world data, we assessed its effectiveness and safety in moderately to critically ill COVID-19 patients. Methods: This retrospective study was conducted in two public/specialty hospitals in Saudi Arabia. We included patients !18 years) admitted April-August 2020 with confirmed SARS-CoV-2 diagnosed by real-time polymerase chain reaction (RT-PCR) from nasopharyngeal swab. Patients received either favipiravir (1800 mg or 1600 mg twice daily loading dose, followed by 800 mg or 600 mg twice daily) or supportive-care treatment. Patients were excluded if they were outside the study period, classified as having a mild form of the disease per WHO criteria, or had an incomplete patient file. Kaplan-Meier (KM) models were used to estimate median time to discharge. Discharge ratios, progression to mechanical ventilation, and mortality outcomes were estimated across the severity spectrum using Cox proportional-hazards models. As a sensitivity analysis, we performed propensity score-matching (PSM) analysis. Results: Overall, median time to discharge was 10 days (95%CI ¼ 9-10) in the favipiravir arm versus 15 days (95%CI ¼ 14-16) in the supportive-care arm. The accelerated discharge benefit was seen across the COVID-19 spectrum of severity. The adjusted discharge ratio was 1.96 (95%CI ¼ 1.56-2.46). Progression to mechanical ventilation was slower with favipiravir (HR adj ¼ 0.10, 95%CI ¼ 0.04-0.29). There was no significant effect on mortality (HR adj ¼ 1.56, 95%CI ¼ 0.73-3.36). There was a statistically non-significant trend toward worse outcomes in the critical category (HR adj ¼ 2.80, 95%CI ¼ 0.99-7.89). Age was an independent risk factor for mortality in mechanically ventilated patients. PSM analyses confirmed these findings. Conclusion: Favipiravir was associated with clinical benefits, including accelerated discharge rate and less progression to mechanical ventilation; however, no overall mortality benefits were seen across the severity spectrum.

Background Electronic prescribing (e-prescribing) technology was introduced as an alternative to handwritten prescriptions allowing health care professionals to send prescriptions directly to pharmacies. While the technology has many advantages, such as improving pharmacy workflow and reducing medication errors, some limitations have been realized. Objective The objective of this study was to examine the frequency, type, and contributing factors of e-prescribing quality-related incidents reported to two national error-reporting databases in the United States. Methods This was a retrospective analysis of voluntarily reports of e-prescribing quality-related incidents. A quantitative and qualitative analysis was conducted of incidents reported between 2011 and 2015 to the Pharmacy Quality Commitment (PQC) and the Pharmacy Provider e-prescribing Experience Reporting Portal (PEER) databases. For the qualitative analysis, events were combined from the PQC and PEER portal and a 10% random sample of events were analyzed. Results A total of 589 events were reported to the PEER Portal. Of these, problems with patient directions were the most frequent incident type (n = 210) of which 10% (n = 21) reached the patient. Quantity selection (n = 158) and drug selection (n = 96) were the next most frequently reported events, 20% of which reached the patient. The PQC system received 550 reports. The most frequent event type reported to this system was incorrect directions (23.3%, n = 128) followed by incorrect prescriber (17%), incorrect drug (15%), and incorrect strength (12%). The most common theme in the qualitative analysis was a perceived increased likelihood of patient receiving incorrect drug therapy due to e-prescribing. Another theme identified included confusion and frustration of pharmacy personnel as result of e-prescription quality-related events. Conclusion The use of qualitative and quantitative incident data revealed that patient directions and quantity selection were the most common quality issues with e-prescribing. In turn, this may increase the likelihood of patients receiving incorrect drug therapy.

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