Travel surveys collect trip data such as origin, destination, mode, duration, distance and purpose of trips, as well as socioeconomic and demographic data for analysis. Transportation planners, policymakers, state departments of transportation, metropolitan planning organisations, industry professionals and academic researchers use survey data to better understand the current demand and performance of the transportation infrastructure, and to plan in preparation for future growth. Next-generation travel surveys will utilise global positioning systems (GPS) to collect trip data with minimal input from survey participants. Owing to their ubiquity, GPS-enabled mobile phones are developing into a promising survey tool. TRAC-IT is a mobile phone application that collects real-time GPS data and requires minimal input from the user for data such as trip purpose, mode and vehicle occupancy. To ease survey burden on participants and enable real-time, modespecific location-based services, new techniques must be explored to derive more information directly from GPS data. As part of travel survey collection, TRAC-IT is able to passively determine trip mode using GPSenabled mobile phones and neural networks. The mode detection technique presented in this article can be optimised using a critical point, pre-processing algorithm to reduce the size of required GPS datasets obtained from GPS-enabled mobile phones, thus reducing data collection costs while conserving precious mobile phone resources such as battery life.
Wireless technology in healthcare has been associated with communication-related improvements in workflow; however, there are barriers to adoption. This study examined predictors of use of wireless communication devices (WCDs) in environments with unique needs (i.e., intensive care unit [ICU]). Nurses were recruited in the ICU to complete a paper questionnaire to assess their willingness to use WCDs. The Theory of Planned Behaviour was used to assess attitudes, subjective norms, perceived control, and behavioral intent. Responses included Likert scale scores and open-ended questions. Data were collected before and following the implementation of WCDs in ICU. The combined effects of attitudes, perceived control and subjective norms on behavioral intent were tested using the general linear model. The narrative data were analyzed using a thematic analysis approach. Attitudes and subjective norms were predictors of behavioral intent to use WCDs preimplementation but not postimplementation. Differences in the factors affecting intent to use WCDs between the ICU and the surgical unit may be related to the unique nature of the critical care environment, and to the lack of a comprehensive preimplementation strategy. A study examining predictors of use on a general inpatient unit where a comprehensive implementation strategy was not employed would provide insight into whether these findings are related to the implementation strategy or the unique nature of the critical care environment. Improved understanding of the function and application of innovative technology at the point of care, and attention to the process of implementation may improve adoption of this potentially beneficial device.
Background: Quality-related events are defined as medication errors that reach the patient (e.g., incorrect drug, dose and quantity), in addition to medication errors that are intercepted before dispensing (i.e., near misses). The aim of this study is to quantify and characterize such events as reported by community pharmacies in a Canadian province. Methods: A retrospective analysis was conducted on quality-related events reported to the Community Pharmacy Incident Reporting system from 301 community pharmacies in Nova Scotia between Oct. 1, 2010, and June 30, 2017. We performed a descriptive analysis on these events with respect to the discoverer, patient outcome, medication system stages and type. Results: We identified 131 031 events reported by community pharmacies in Nova Scotia over the study period, 98 097 of which were quality-related events. Overall, 82.0% (n = 80 488) quality-related events did not reach the patient, and 0.95% (n = 928) were associated with patient harm. Incorrect dose or frequency, incorrect quantity and incorrect drug were the most common types of quality-related events reported. Most of the quality-related events occurred at order entry, followed by preparation and dispensing, and prescribing. Interpretation: Quality-related events reported by community pharmacies differ from those reported in institutional settings with respect to patient outcome, medication system stages and type. This analysis provides valuable information to guide quality improvement initiatives to strengthen medication safety in community pharmacies.
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