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This study evaluated the perceptions of clinical pharmacist integration into the PACT model. Respondents perceived clinical pharmacist beneficial.

Purpose To evaluate educational experiences of internal medicine interns before and after maximum shift lengths were decreased from 30 hours to 16 hours. Method The authors compared educational experiences of internal medicine interns at Vanderbilt University Medical Center before (2010, 47 interns) and after (2011, 50 interns) duty hour restrictions were implemented in July 2011. The authors compared number of inpatient encounters, breadth of concepts in notes, exposure to five common presenting problems, procedural experience, and attendance at teaching conferences. Results Following the duty hour restrictions, interns cared for more unique patients (mean 118 versus 140 patients per intern, P = .005) and wrote more history and physicals (mean 73 versus 88, P = .005). Documentation included more total concepts after the 16-hour maximum shift implementation, with a 14% increase for history and physicals (338 versus 387, P < .001) and a 10% increase for progress notes (316 versus 349, P < .001). There was no difference in the median number of selected procedures performed (6 versus 6, P = .94). Attendance was higher at the weekly chief resident conference (60% versus 68% of expected attendees, P < .001) but unchanged at morning report conferences (79% versus 78%, P = .49). Conclusions Intern clinical exposure did not decrease after implementation of the 16-hour shift length restriction. In fact, interns saw more patients, produced more detailed notes, and attended more conferences following duty hour restrictions.

BackgroundAntibiotics are not recommended for treatment of acute uncomplicated bronchitis (AUB), but are often prescribed (85% of AUB visits within the Veterans Affairs nationally). This quality improvement project aimed to decrease antibiotic prescribing for AUB in community-based outpatient centres from 65% to <32% by April 2020.MethodsFrom January to December 2018, community-based outpatient clinics’ 6 months’ average of prescribed antibiotics for AUB and upper respiratory infections was 63% (667 of 1054) and 64.6% (314 of 486) when reviewing the last 6 months. Seven plan–do–study–act (PDSA) cycles were implemented by an interprofessional antimicrobial stewardship team between January 2019 and March 2020. Balancing measures were a return patient phone call or visit within 4 weeks for the same complaint. Χ2 tests and statistical process control charts using Western Electric rules were used to analyse intervention data.ResultsThe AUB antibiotic prescribing rate decreased from 64.6% (314 of 486) in the 6 months prior to the intervention to 36.8% (154 of 418) in the final 6 months of the intervention. No change was seen in balancing measures. The largest reduction in antibiotic prescribing was seen after implementation of PDSA 6 in which 14 high prescribers were identified and targeted for individualised reviews of encounters of patients with AUB with an antimicrobial steward.ConclusionsOperational implementation of successful stewardship interventions is challenging and differs from the traditional implementation study environment. As a nascent outpatient stewardship programme with limited resources and no additional intervention funding, we successfully reduced antibiotic prescribing from 64.6% to 36.8%, a reduction of 43% from baseline. The most success was seen with targeted education of high prescribers.

The goal of this project is to develop an effective system that aids meteorologists in better understanding and predicting severe weather. For the last decade, the average prediction time for tornado genesis has remained at 15 minutes. Unpredictability of tornado supercells creates over prediction cases which causes havoc in communities and can produce unnecessary injuries. There have been significant improvements in analytical models and instrumentation that provide researchers with sufficient methods of decreasing the current prediction times. However, the current warning time and unpredictability of supercell thunderstorms remains the same. Unmanned aircraft systems (UAS) provide an effective and safe platform for advanced weather surveillance and atmospheric data collection. In order to correctly collect the atmospheric data, it is important to ensure that the system is equipped with an effective sensor package for the weather conditions. It is also important to consider the points of interest in the storm system and to understand the ingredients for tornado genesis in order for the data to be meaningful. There are many viable options to consider and this paper will delve into the development of the optimal sensor suite for a storm surveying unmanned air vehicle (UAV).