Task Time Distribution Research Articles

Design, application and testing of the Work Observation Method by Activity Timing (WOMBAT) to measure clinicians’ patterns of work and communication

Background Evidence regarding how health information technologies influence clinicians’ patterns of work and support efficient practices is limited. Traditional paper-based data collection methods are unable to capture clinical work complexity and communication patterns. The use of electronic data collection tools for such studies is emerging yet is rarely assessed for reliability or validity. Aim Our aim was to design, apply and test an observational method which incorporated the use of an electronic data collection tool for work measurement studies which would allow efficient, accurate and reliable data collection, and capture greater degrees of work complexity than current approaches. Methods We developed an observational method and software for personal digital assistants (PDAs) which captures multiple dimensions of clinicians’ work tasks, namely what task, with whom, and with what; tasks conducted in parallel (multi-tasking); interruptions and task duration. During field-testing over 7 months across four hospital wards, fifty-two nurses were observed for 250 h. Inter-rater reliability was tested and validity was measured by (i) assessing whether observational data reflected known differences in clinical role work tasks and (ii) by comparing observational data with participants’ estimates of their task time distribution. Results Observers took 15–20 h of training to master the method and data collection process. Only 1% of tasks observed did not match the classification developed and were classified as ‘other’. Inter-rater reliability scores of observers were maintained at over 85%. The results discriminated between the work patterns of enrolled and registered nurses consistent with differences in their roles. Survey data ( n = 27) revealed consistent ratings of tasks by nurses, and their rankings of most to least time-consuming tasks were significantly correlated with those derived from the observational data. Over 40% of nurses’ time was spent in direct care or professional communication, with 11.8% of time spent multi-tasking. Nurses were interrupted approximately every 49 min. One quarter of interruptions occurred while nurses were preparing or administering medications. Conclusions This method efficiently produces reliable and valid data. The multi-dimensional nature of the data collected provides greater insights into patterns of clinicians’ work and communication than has previously been possible using other methods.

Stochastic analysis of real-time systems under preemptive priority-driven scheduling

Exact stochastic analysis of most real-time systems under preemptive priority-driven scheduling is unaffordable in current practice. Even assuming a periodic and independent task model, the exact calculation of the response time distribution of tasks is not possible except for simple task sets. Furthermore, in practice, tasks introduce complexities such as release jitter, blocking in shared resources, etc., which cannot be handled by the periodic independent task set model. In order to solve these problems, exact analysis must be abandoned for an approximated analysis. However, in the real-time field, approximations must not be optimistic, i.e. the deadline miss ratios predicted by the approximated analysis must be greater than or equal to the exact ones. In order to achieve this goal, the concept of pessimism needs to be mathematically defined in the stochastic context, and the pessimistic properties of the analysis carefully derived. This paper provides a mathematical framework for reasoning about stochastic pessimism, and obtaining mathematical properties of the analysis and its approximations. This framework allows us to prove the safety of several proposed approximations and extensions. We analyze and solve some practical problems in the implementation of the stochastic analysis, such as the problem of the finite precision arithmetic or the truncation of the probability functions. In addition, we extend the basic model in several ways, such as the inclusion of shared resources, release jitter or non-preemptive sections.

On the completion time distribution for tasks that must restart from the beginning if a failure occurs

For many systems, failure is so common that the design choice of how to deal with it may have a significant impact on the performance of the system. There are many specific and distinct failure recovery schemes, but they can be grouped into three broad classes: RESUME , also referred to as preemptive resume (prs), or check-pointing; REPLACE , also referred to as preemptive repeat different (prd); and RESTART , also referred to as preemptive repeat identical (pri). The following describes the three recovery schemes: (1) RESUME: when a task is fails, it knows exactly where it stops, and can continue from that point when allowed to resume; (2) REPLACE: given a task fails, then when it begins processing again, it starts with a brand new task sampled from the same task time distribution; and, (3) RESTART: When a task fails, it loses all that it had acquired to up to that point and must start anew when upon continuing later. This is distinctly different from (2) since the task must run at least as long as it did before it failed, whereas a new sample, selected at random, might run for a shorter or longer time.

Exact Results for the Barabási Model of Human Dynamics

Human activity patterns display a bursty dynamics with interevent times following a heavy tailed distribution. This behavior has been recently shown to be rooted in the fact that humans assign their active tasks different priorities, a process that can be modeled as a priority queueing system [A.-L. Barabási, Nature (London) 435, 207 (2005)]. In this Letter we obtain exact results for the Barabási model with two tasks, calculating the priority and waiting time distribution of active tasks. We demonstrate that the model has a singular behavior in the extremal dynamics limit, when the highest priority task is selected first. We find that independently of the selection protocol, the average waiting time is smaller or equal to the number of active tasks, and discuss the asymptotic behavior of the waiting time distribution. These results have important implications for understanding complex systems with extremal dynamics.

Time Distribution of Professional Tasks for Academic Staff in Yarmouk University

Time Distribution of Professional Tasks for Academic Staff in Yarmouk University

Effects of Feedback on Task Completion, Time Distribution and Time Allocation of Graduate Students

ABSTRACT The direct effects of private feedback on graduate students' task completion and the indirect effects of this feedback on time allocation and time distribution were examined. The results indicated no effects of either private feedback or public feedback on task completion. Feedback on task completion showed desirable indirect effects on time allocation and time distribution when students were being evaluated on their activities in only one domain.

Improving outpatient clinic staffing and scheduling with computer simulation

Patient flow in an appointment-based, outpatient internal medicine clinic involving multiple, sequential providers-registrar, triage nurse, physician, and discharger-was studied using computer simulation. Provider task time distributions were obtained through a time-motion study and then input into the computer program, which simulated the clinic situation well. Time interval and sensitivity analyses yielded insights into staffing levels, appointment times, and clinic dynamics. A bottleneck provider was shown, and patient time in the clinic was related to the time of appointment and was slowed by having too many doctors in the clinic. Subsequent operational changes significantly decreased the average observed patient total time in clinic from 75.4 (SD 34.2) minutes to 57.1 (SD 30.2) minutes (p < .001, t test).

Micro Saint Modeling of Visual Displays and Controls Consoles

An experiment was conducted to evaluate the feasibility of using a predetermined time system (PTS) with the simulation model Micro SAINT as a method for making design decisions for a navy electronic interactive display and control console. Prototypes for different configurations were created using a Macintosh workstation. Configurations varied across two levels of symbol set, color condition, and screen format for three different target density scenarios. A Micro SAINT simulation model, emulating a single integrated task performed by the operator for all 24 prototype configurations, was constructed. The model was validated by regressing predicted performance scores on actual performance scores obtained from six subjects operating the prototypes. The model also successfully predicted the performance of a second group of six subjects. Although the questions of how to acquire standard deviation data and task time distributions remain, the use of a PTS in network simulation modeling can provide objective data for console designs without incurring the high costs associated with actual prototype construction and testing.

A proposal on improved procedures for estimating task-time distributions in PERT

The objective of using the well-known PERT task-time estimation formulas has two components: (i) to elicit subjective time estimates from an ‘expert’; and (ii) to translate these estimates into ‘something’ that can be used as inputs to probabilistic network analysis. By incorporating the more current techniques in subjective probability elicitation and distribution theory, this paper proposes and justifies a practical and more logical two-step procedure for achieving both components of the objective. The first step uses a seven-point fractile-estimation procedure, the second step determines the parameters of a beta and a Ramberg-Schmeiser distribution function that minimize the mean square deviation between the distribution function and the estimated fractiles. The procedure can be easily implemented by practitioners using a canned program.

Optimal parallel evaluation of AND trees

AND-tree evaluation is an important technique in artificial intelligence and operations research. An example is the divide-and-conquer algorithm, which can be considered the evaluation of a precedence graph consisting of two opposing AND trees. In this paper, the optimal degree of parallelism for evaluating any given AND tree is quantitatively analyzed. The efficiency analysis is based on both preemptive and nonpreemptive critical-path scheduling algorithms. It is found that the optimal degree of parallelism depends on the complexity of the problem to be solved, the shape of the precedence graph, and the task-time distribution along each path. The major results consist of showing the optimality of the preemptive critical-path scheduling algorithm for evaluating any given AND tree on a fixed number of processors, and tight bounds on the number of processors within which the number of processors leading to the optimal processor-time efficiency can besought efficiently.

Pre-Earthquake Vulnerability Assessment

AbstractHealth planning for disasters builds on an awareness of ways in which the disaster affects health and on anticipation of tasks to be performed by the health sector.In view of the possibility of an earthquake of significant magnitude in Israel, and in the absence of previous earthquake experience, published data of earthquake health effects were studied, such as causes of death and injury, casualty rates and factors influencing these, distribution of injuries and their severity, effect on health care facilities and on physical, social and psychological environments. Implications of the studied data were applied to relevant conditions in Israel and to an earthquake there. A predisaster vulnerability assessment was thus obtained, pointing to the nature, size, and space and time distribution of tasks the health sector would be expected to perform should an earthquake occur in Israel.On the basis of this assessment some recommendations for the preparation and preparedness of the health sector for such an occurrence are submitted.

A decision support system for the design of unpaced production lines

SUMMARY Consider a realistic unpaced-line problem: there is a set of discrete tasks, whose task-time distributions have diverse shapes. The line designer must (i) decide to which work station to assign each task, and (ii) specify the size of each buffer area in such a way that the configuration has the ‘best’ operating characteristics. This paper describes a decision support package that can efficiently generate the operating characteristics of the many alternative line designs which the line designer may want to try. We also show that the package can be conveniently used to extend earlier results in theoretical unpaced-line research.

Stochastic unpaced line design: Review and further experimental results

AbstractPrevious design studies of unpaced assembly lines that exhibit stochastic task times indicate that an unbalanced allocation of task times results in optimal output rates. In this article, we present a comprehensive review of the previous literature on this topic and discuss the results of simulation experiments that test the bowl distribution for unbalancing unpaced lines. The simulation experiment was designed to test the bowl distribution in more realistic environments than previously tested and illustrates that a balanced line configuration is as good as or better than an unbalanced line configuration when task times are modeled with more typical values of variance.Stochastic unpaced assembly line research employs both simulation and analytical approaches to test the allocation of buffer capacity and task times to work stations. Analytical models are utilized to investigate simple line designs with exponential or Erlang task time distributions. Simulation is used for longer lines and for normal task time distributions. From the review of the previous research using both approaches, we note five major findings: 1) unbalancing task time allocation is optimal when task time variation is large; 2) unbalanced allocation of buffer storage capacity improves line output rate when task time variation is large; 3) output rate of an unpaced line decreases as the number of sequential workstations increases; 4) output rate increases as more buffer storage capacity is available; and 5) output rate decreases as the task time variation increases.Most of the previous research on unpaced lines investigated lines with few workstations and large task time variation. Empirical research by Dudley (6) suggests that variation of task times in practice is much less than variations employed in previous unpaced line studies. We present the results from simulation experiments that model longer unpaced lines with lower levels of task time variance of the magnitude that is likely to occur in practice.The results of our simulation experiments verify the benefits of using the bowl distribution for task time allocation when line lengths are short and task times experience large variance. However, when line lengths are extended or task time variation is reduced, the use of the bowl distribution for unbalancing the line degrades the line's efficiency. In these situations, the optimal task time allocation is a balanced line.Two important implications for managers follow from the results of our experiments: 1) that unpaced line output rate is relatively insensitive to moderate variations from optimal task time allocations when buffer storage is limited; and 2) that perfectly balanced line designs are optimal for most cases in practice.