Working time distribution and administrative burden in Austrian community health nursing: A cross-sectional survey.

Problem setting. On-call work is today a poorly-investigated by science of labor law form of non-standard employment. Since 2019, there are several draft laws developed in Ukraine that deal with on-call work. These drafts describe it such as employment contract with non-fixing working hour. The latest draft No. 5161 of 25.02.2021 "On Amendments to Certain Legislative Acts of Ukraine on the regulation of some non-standard forms of employment" has been submitted to Parliament. This bill was developed according to the Directive (EU) 2019/1152 of the European Parliament and of the Council of 20 June 2019 on transparent and predictable working conditions in the European Union. However, we believe some provisions of this bill on the establishment of working time need further adaptation. Analysis of resent researches and publications. The issue of legal regulation of non-standard employment has been analysed by V.Venedidikov, N. Vyshnevska, I. Gorgoriev, I. Kiselev, A. Lushnikov, D. Morozov, O. Mozna, N. Nikitina, O. Process, O. Rimkevich, V. Soyfer, M. Sorokishin, O. Yaroshenko. On-call work was the subject of doctor’s and candidate’s thesis of V. Gnidenko, O. Korkin, O.Pilipko, M. Shabanova. At the same time a number of legal problems were arised after the project No. 5161 had been adopted. For instance, peculiarities of the establishment of working time, the legal regulation of new legal categories in an employment contract with non-fixed working time need further adaptation. Аrticle’s main body. In the employment contract with non-fixing working hour the maximum working hours of the employee is determined, fixed in the contract, however the minimum working time is not defined due to the fact that the employer does not have a duty to provide employee work. The minimum duration of working time defined in the draft law depends only on the amount of the wage or compensation for staying in a state of waiting. In order to strengthen the coherence of terminology and better reconcile the typology and character of this non-standard employment form with the provisions of Directive (EU) 2019/1152, the draft law should enter and (or) determine the terms, such as a schedule of work, basic hours and days, mode of operation. Conclusions and prospects for the development. In the contract with non-fixed working hours, the installation and distribution of working time has specific features: maximum duration of the employee's working time is determined, fixed in the contract, and the minimum working time is not determined at all, since the employer does not have a duty in the employer to provide employee work. The minimum duration of working time defined in the draft law depends only on the amount of the wage or compensation for staying in a state of waiting. In such an employment contract basic days and hours should be establishes, that is, a time interval when an employee must perform its labor duties in case of a demand. The employee's calling on work, in turn, must be carried out by the employer in compliance with the conditions established in the contract itself (for example, the method and minimum term of the employee's notice of the start of work). The mode of operation is predictive to the employee, the one can predict "theoretically" that he can be called on in certain days and hours. The schedule of work with each call on work is really unpredictable. This schedule should be agreed between the employee and the employer before the work is started, although we believe such agree does not matter because the schedule is made within the basic days and hours that are already known to the employee.

To examine individual variation in total and direct patient care work hours annually across a decade and identify associations of work hours with pediatrician characteristics and measures of work-life balance. Using data from the American Academy of Pediatrics Pediatrician Life and Career Experience Study (PLACES), a national longitudinal study, we examined total work and direct patient care hours reported by the same pediatricians each year, 2013-2022. Yearly participation ranged from 75% to 94%. We examined work-hour patterns using mixed-effects linear regression for longitudinal data. We also developed pediatrician profiles based on work hours and direct patient care time and explored associations with multiple measures of work-life balance. Analyses included 12 864 observations from 1696 pediatricians. Mean hours per week across years were 42.8 for total and 33.3 for direct patient care work. A mixed-effects model examined total work hours. The largest associations showed men working more than women (B = 7.22; 95% CI, 6.04-8.39) and subspecialists from large subspecialties working more than general pediatricians (B = 7.20; 95% CI, 6.11-8.29). There was a slight decrease in total hours found across years (B = -0.12; 95% CI, -0.21 to -0.03). Pediatricians who worked more hours reported lower work-life balance. Pediatricians working a greater portion of their time in direct patient care did not report worse work-life balance. Direct patient care made up three-fourths of total work hours, and pediatricians reported a slight annual decrease in hours worked. Men, subspecialists, and hospitalists were likely to work more hours, and higher work hours were negatively associated with work-life balance.

Objective To measure nurses' work time distribution in direct nursing, indirect nursing, non-nursing activity and personal activity and effective work hour and walk miles. Methods Observers recorded nurses' work time cost on each activity and walk miles by one-to-one following-up at Department of Gastroenterology and General Surgery in a Grade-A hospital. Results Direct nursing time made up 35. 75 % , indirect time 53. 19 % , non-nursing activity 0. 49 % ; personal activity 10. 56 %. The effective working time among day work nurses was 6.80 and 6.28 in the two Department respectively, while 6. 10 and 5.36 among shift nurses. An average walk miles were about 4. 36 km/d/nurse, 4. 64 km among day work nurses and 3. 67 km among night work nurses. Conclusions Indirect nursing cost too much time while some very important direct nursing items cost too little time. Nurses' actual effective work-hour is higher than the standard one. Nurses' walk miles are positively correlated with workload. Hospital should dynamically deploy nursing human resource according to all kinds of criterion and nosocomial practice. In the meantime, long effective mechanism should be established to ensure that patients can obtain suitable nursing without waste of manpower. Key words: Nursing activities; Time distribution; Work-hour measurement; Nursing human resource

BackgroundLong working hours and unpaid work are possible risk factors for depressive symptoms. However, little is known about how working hours influence the course of depressive symptoms. This study examined...

Improving Japanese Physicians’ Gender-Role Attitudes: Career Education and Adjusted Work Systems

PT. Indonesia Ethanol Industry is one company that operates 24 hours, with the division of labor time in the morning, afternoon, and evening. The system implemented six working days within one week and get one day off. Working time sharing arrangements 1-3-2 pattern. That is two days early, two days nights, and two days late, then one day off. Over time, there are proposals for changes of employees through the management to try to change the division of labor time into a 3-2-1 pattern. Consideration of changes in the pattern so that the holiday is longer so that when you return to work can be more focused. The purpose of this study was to determine the distribution of effective working time seen from side physiology, psychosocial, performance, health and sfety in the PT. Indonesia Ethanol Industry at Jl. Cross East Coast KM 242 Village Sriwijaya District of Bandar Mataram Lampung Tengah. The method used in physiology and psychosocial research is Focus Group Discussion and to study the performance, health and safety using multiple correlation method. To make decisions based on the analysis method of variable ranking physiology, psychosocial, performance, health, and safety unknown variable is thehighest performance. The performance variables known at the time the division of labor pattern 3-2-1 the result of lower production compared with the distribution of working time pattern 1-3-2. Keywords: Distribution of Working Time, Physiology, Psychosocial, Performance, Health, and Work Safety.

Resident work hours have been a recurring source of concern and controversy for many years. From the Spartan origins of the Halsted generic model of the surgical service at Johns Hopkins in 1897 to the present, there have been major tensions between the educational needs of learners and the workload demands of patient care, resulting, at times, in classic labor-management confrontations about work hours and conditions.

Worktime control : theoretical conceptualization, current empirical knowledge, and research agenda

Background:Emergency departments (EDs) provide urgent care to diverse patients. Medication-related tasks, crucial for safe diagnosis and treatment, often receive inadequate attention. Clinical pharmacists, experts in medication management, can improve outcomes and reduce costs.Objectives:To investigate how the introduction of clinical pharmacists affects ED junior physicians’ work-time distribution, with particular focus on medication-related tasks.Design:A stepped-wedge design was employed, introducing pharmacists across three Norwegian EDs over a 9-month period, with each ED starting at staggered intervals.Methods:Using the Work Observation Method By Activity Timing (WOMBAT) methodology, we observed junior physicians’ activities in three EDs. The pharmacists were encouraged to adapt to the ED setting, integrate into the team, and identify ways to apply their expertise effectively. Medication reconciliation became their primary focus. We recorded 251 h of observation in the period without pharmacists present and 287 h in the intervention period, with pharmacists present. The proportion of time spent on different tasks was compared between the two periods.Results:Junior physicians spent 81.0% of their work time on non-medication-related tasks, 11.6% on standby/movement, and 8.7% on medication-related tasks. There was no evidence that the overall time distribution was affected by the intervention. However, in ED2, the proportion of time spent on medication-related documentation was reduced from 6.1% to 2.5%, while standby time increased from 6.1% to 13% with pharmacists present. Face-to-face interactions with pharmacists accounted for less than 2% of the junior physicians’ work time in all EDs.Conclusion:In three Norwegian EDs, junior physicians’ work time was predominantly spent on non-medication-related tasks, with only 8.7% dedicated to medication-related tasks. The introduction of clinical pharmacists did not significantly impact junior physicians’ overall work-time distribution. Further research should investigate pharmacists’ impact on ED care quality and efficiency.

BackgroundThe work of teachers has changed due to an increase in the range of tasks. However, there is a lack of current information on working hours, task distribution and the possible health effects.MethodsFor the first time for Germany as a whole, a cross-sectional survey determined how long teachers at upper-level secondary schools work per week, what influences their working hours and how different recording methods affect the total working hours. To this end, 6,109 full-time teachers estimated their working hours based on twelve categories and then documented these daily over 4 weeks. Afterwards, the effects of long working hours on teachers' ability to recover and emotional exhaustion were analysed.ResultsThe article shows the large interindividual variance in the working hours of teachers and a significant influence of sex, age, and subject profile. Self-reported working hours varied substantially by method used to record working time with work time reported via daily diaries totaling 2 h per week more than hours recorded by a single estimation.A substantial proportion of the teachers (36%) work longer per week than European guidelines allow (> 48 h); 15% work even more than 55 h per week. Teachers who work more than 45 h per week suffer more often from inability to recover (46%) and emotional exhaustion (32%) than teachers who work less than 40 h per week (26% and 22% respectively).ConclusionsTaking professional experience and teaching subjects into account could in future contribute to a fairer distribution of workload among teachers. This could protect individual teachers from long working hours, ensure sufficient recovery and also reduce the risk of emotional exhaustion. In order to identify teachers whose health is at risk at an early stage, voluntary preventive care offers would be considerably helpful.

IntroductionWork time control (WTC) is defined as ‘employees´ possibilities to control over the duration and distribution of own work time’. A recent study found shorter sickness spells on wards using...

BackgroundThe emergency department (ED) is a demanding work environment where nurses undertake a variety of clinical and administrative tasks, including medication-related tasks. The integration of a clinical pharmacist into the ED team represents a complex intervention with potential implications for nurses’ distribution of work time, particularly concerning medication-related tasks. This study examined the distribution of work time among ED nurses and assessed the impact of a clinical pharmacist’s presence on this distribution, with an emphasis on medication-related work tasks.MethodsA direct observational time and motion study was conducted to evaluate the work time distribution of nurses in three Norwegian EDs, applying the Work Observation Method By Activity Timing (WOMBAT) methodology. Time distributions were measured for non-medication-related tasks, medication-related tasks, standby and movement, both in the absence and presence of a clinical pharmacist in the same ED.ResultsA total of 298 h of nursing work time were observed, comprising 138 h without pharmacists present and 160 h with pharmacists present. In the absence of a pharmacist, nurses spent 62.7% of their time on non-medication-related tasks, 34.7% on standby and movement, and 3.3% on medication-related tasks. The introduction of a clinical pharmacist did not significantly change the overall distribution of nurses’ work time, although some variations were noted across the EDs.ConclusionED nurses in three Norwegian EDs dedicated only 3.3% of their work time to medication-related tasks. The presence of clinical pharmacists did not substantially affect the distribution of nurses’ work time.

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.

To accurately model residents' work hours and assess options to forthrightly meet Residency Review Committee-Internal Medicine (RRC-IM) requirements. The requirements limiting residents' work hours are clearly defined by the Accreditation Council for Graduate Medical Education (ACGME) and the RRC-IM: "When averaged over any four-week rotation or assignment, residents must not spend more than 80 hours per week in patient care duties."(1) The call for the profession to realistically address work-hours violations is of paramount importance.(2) Unfortunately, work hours are hard to calculate. We developed an electronic model of residents' work-hours scenarios using Microsoft Excel 97. This model allows the input of multiple parameters (i.e., call frequency, call position, days off, short-call, weeks per rotation, outpatient weeks, clinic day of the week, additional time due to clinic) and start and stop times for post-call, non-call, short-call, and weekend days. For each resident on a rotation, the model graphically demonstrates call schedules, plots clinic days, and portrays all possible and preferred days off. We tested the model for accuracy in several scenarios. For example, the model predicted average work hours of 85.1 hours per week for fourth-night-call rotations. This was compared with logs of actual work hours of 84.6 hours per week. Model accuracy for this scenario was 99.4% (95% CI 96.2%-100%). The model prospectively predicted work hours of 89.9 hours/week in the cardiac intensive care unit (CCU). Subsequent surveys found mean CCU work hours of 88, 1 hours per week. Model accuracy for this scenario was 98% (95% CI 93.2-100%). Thus validated, we then used the model to test proposed scenarios for complying with RRC-IM limits. The flexibility of the model allowed demonstration of the full range of work-hours scenarios in every rotation of our 36-month program. Demonstrations of status-quo work-hours scenarios were presented to faculty as well as real-time demonstrations of the feasibility, or unfeasibility, of their proposed solutions. The model clearly demonstrated that non-call (i.e., short-call) admissions without concomitant decreases in overnight call frequency resulted in substantial increases in total work hours. Attempts to "get the resident out" an hour or two earlier each day had negligible effects on total hours and were unrealistic paper solutions. For fourth-night-call rotations, the addition of a "golden weekend" (i.e., a fifth day off per month) was found to significantly reduce work hours. The electronic model allowed the development of creative schedules for previously third-night-call rotations that limit resident work hours without decreasing continuity of care by scheduling overnight call every sixth night alternating with sixth-night-short-call rotations. Our electronic model is sufficiently robust to accurately estimate work hours on multiple and varied rotations. This model clearly demonstrates that it is very difficult to meet the RRC-IM work-hours limitations under standard fourth-night-call schedules with only four days off per month. We are successfully using our model to test proposed alternative scenarios, to overcome faculty misconceptions about resident work-hours "solutions," and to make changes to our call schedules that both are realistic for residents to accomplish and truly diminish total resident work hours toward the requirements of the RRC-IM.

Long work hours among physicians is a worldwide issue in the healthcare arena. Previous studies have largely focused on the work hours of resident physicians rather than those of attending physicians. The purpose of this study was to investigate total work hours and the composition of those work hours for attending physicians across different hospital settings and across different medical specialties through a nationwide survey. This included examining differences in physician workload and its composition with respect to different hospital characteristics, and grouping medical specialties according to the work similarities. A cross-sectional self-reported nationwide survey was conducted from June to September of 2018, and the two questionnaires were distributed to all accredited hospitals in Taiwan. The number of physician work hours in different types of duty shifts were answered by medical specialty in each surveyed hospital. Each medical specialty in a hospital filled only one response for its attending physicians. The findings reveal that the average total work hours per week of an attending physician is around 69.1 h, but the total work hours and their composition of different duty shifts varied among hospital accreditation levels, geographic locations, emergency care responsibilities, and medical specialties. Because of the variance in the number and composition of attending physicians’ work hours, adjusting physician work hours to a reasonable level will be a major challenge for health authority and hospital managers.