Abstract
BackgroundThere are numerous mobile apps for tracking work hours, but only a few of them record work hours automatically instead of relying on manual logging. No apps have been customized for medical staff, whose work schedules are highly complicated as they have both regular hours and on-call duties.ObjectiveThe specific aims of this study were to (1) identify the Staff Hours app users’ GPS-defined work hours, (2) examine the overtime work hours from the app-recorded total work hours and the participants’ self-reported scheduled work hours, and (3) compare these app-recorded total work hours among different occupations.MethodsWe developed an app, Staff Hours, to automatically calculate a user’s work hours via GPS background data. Users can enter their scheduled hours, including regular hours and on-call duties. The app automatically generates overtime reports by comparing the app-recorded total work hours with the user-defined scheduled hours. A total of 183 volunteers (60 females and 123 males; mean age 32.98 years, SD 6.74) were included in this study. Most of the participants (162/183, 88.5%) were medical staff, and their positions were resident physicians (n=89), visiting staff (n=38), medical students (n=10), registered nurses (n=25), and non–health care professionals (non-HCPs; n=21).ResultsThe total work hours (mean 55.69 hours, SD 21.34) of the 183 participants were significantly higher than their scheduled work hours (mean 50.67 hours, SD 21.44; P=.01). Medical staff had significantly longer total work hours (mean 57.01 hours, SD 21.20) than non-HCPs (mean 45.48 hours, SD 20.08; P=.02). Residents (mean 60.38 hours, SD 18.67) had significantly longer work hours than visiting staff (mean 51.42 hours, SD 20.33; P=.03) and non-HCPs (mean 45.48 hours, SD 20.08; P=.004).ConclusionsStaff Hours is the first automatic GPS location–based app designed for medical staff to track work hours and calculate overtime. For medical staff, this app could keep complete and accurate records of work hours in real time, reduce bias, and allow for better complying with labor regulations.
Highlights
BackgroundLong work hours and shift work increase the risk of both physiological and psychological distress [1,2,3,4,5,6], including cardiovascular disease [7] and depressive symptoms [8]
One-way analysis of variance was used to compare the differences in total work hours among all 5 categories of workers
We used independent t tests to examine the differences in the total work hours between the medical staff and non–health care professional (non-HCP)
Summary
BackgroundLong work hours and shift work increase the risk of both physiological and psychological distress [1,2,3,4,5,6], including cardiovascular disease [7] and depressive symptoms [8]. Surveying medical interns’ compliance with the 2003 work-hour limits in the United States using a traditional assessment took 2 years; the resulting national survey was published in 2006 [10]. These self-reports do not reflect the fluctuations of work hours in real time, especially for medical staff with frequent on-call duties. Methods: We developed an app, Staff Hours, to automatically calculate a user’s work hours via GPS background data Users can enter their scheduled hours, including regular hours and on-call duties. Conclusions: Staff Hours is the first automatic GPS location–based app designed for medical staff to track work hours and calculate overtime. This app could keep complete and accurate records of work hours in real time, reduce bias, and allow for better complying with labor regulations
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