Completion Time Variables Research Articles

A human centered design approach to define and measure documentation quality using an EHR virtual simulation.

Electronic health record (EHR) documentation serves multiple functions, including recording patient health status, enabling interprofessional communication, supporting billing, and providing data to support the quality infrastructure of a Learning Healthcare System. There is no definition and standardized method to assess documentation quality in EHRs. Using a human-centered design (HCD) approach, we define and describe a method to measure documentation quality. Documentation quality was defined as timely, accurate, user-centered, and efficient. Measurement of quality used a virtual simulated standardized patient visit via an EHR vendor platform. By observing and recording documentation efforts, nurse practitioners (NPs) (N = 12) documented the delivery of an Age-Friendly Health System (AFHS) 4Ms (what Matters, Medication, Mentation, and Mobility) clinic visit using a standardized case. Results for timely documentation indicated considerable variability in completion times of documenting the 4Ms. Accuracy varied, as there were many types of episodes of erroneous documentation and extra time in seconds in documenting the 4Ms. The type and frequency of erroneous documentation efforts were related to navigation burden when navigating to different documentation tabs. The evaluated system demonstrated poor usability, with most participants scoring between 60 and 70 on the System Usability Scale (SUS). Efficiency, measured as click burden (the number of clicks used to navigate through a software system), revealed significant variability in the number of clicks required, with the NPs averaging approximately 13 clicks above the minimum requirement. The HCD methodology used in this study to assess the documentation quality proved feasible and provided valuable information on the quality of documentation. By assessing the quality of documentation, the gathered data can be leveraged to enhance documentation, optimize user experience, and elevate the quality of data within a Learning Healthcare System.

General variable neighborhood search for the parallel machine scheduling problem with two common servers

We address in this paper the parallel machine scheduling problem with a shared loading server and a shared unloading server. Each job has to be loaded by the loading server before being processed on one of the available machines and unloaded immediately by the unloading server after its processing. The objective function involves the minimization of the overall completion time, known as the makespan. This important problem raises in flexible manufacturing systems, automated material handling, healthcare, and many other industrial fields, and has been little studied up to now. To date, research on it has focused on the case of two machines. The regular case of this problem is considered. A mixed integer programming formulation based on completion time variables is suggested to solve small-sized instances of the problem. Due to its mathcal{NP}mathcal{}-hardness, we propose two greedy heuristics based on the minimization of the loading, respectively unloading, server waiting time, and an efficient General Variable Neighborhood Search (GVNS) algorithm. In the computational experiments, the proposed methods are compared using 120 new and publicly available instances. It turns out that, the proposed GVNS with an initial solution-finding mechanism based on the unloading server waiting time minimization significantly outperforms the other approaches.

Factors Affecting Student Time to Examination Completion

Objective. To investigate factors (prior or current knowledge, metacognitive accuracy, and personality) that might impact the time it takes students to complete an examination. Methods. On the final examination, the time to complete the examination was recorded. Prior to the course, students completed the five-factor personality assessment. During the semester, students completed four cumulative assessments that included prospective judgments of performance to improve their metacognitive accuracy. Measures of metacognitive accuracy were calculated from the difference between the students' prospective judgments of performance and their actual assessment performance for the final examination. Two weeks prior to the final examination, students completed a cumulative assessment, which served as prior knowledge; this was similar in content to the final examination. Results. The time to complete the final examination was significantly negatively correlated with examination score and positively correlated with Agreeableness, and degree of metacognitive bias. However, only current knowledge (β=-.35) and Agreeableness (β=.12) predicted the time to complete the final examination. These two factors explained about 14% of the variability in completion times. Examining the scale for the time to complete the examination, there were some regional differences between the slowest, intermediate and fastest completers. Conclusion. Current knowledge and to a lesser extent, pro-social behavior (agreeableness) influenced examination completion time. Metacognitive accuracy had limited predictability in time to complete the examination.

Investigating Functional Impairment in Preclinical Alzheimer's Disease.

Very little is known about functional change in persons in the preclinical stage of AD. As currently conceptualized, functional impairment in Alzheimer’s disease (AD) is the final and somewhat remote downstream outcome of a cascade of preceding pathophysiological and clinical events characterizing AD: amyloid deposition, neurodegenerative cellular, metabolic and network pathway changes, tissue loss and atrophy, and significant cognitive decline. Given this prevailing conceptual framework, possible functional change in preclinical AD, and related clinical trial methodology, have received relatively little attention. For example, the 2013 draft guidance of the FDA for treatment of early stage Alzheimer’s disease anticipates that persons in the preclinical phase will only show subtle cognitive deficits “in the absence of any detectable functional impairment” (1), and that in these circumstances the field may be allowed to pursue valid and reliable cognitive assessments as a single primary efficacy measure (1). This prevailing framework notwithstanding, a new perspective has recently begun to emerge concerning functional change and outcome measures in preclinical AD. The intriguing possibility that detectable functional change actually commences much earlier in the AD disease process, possibly as early as the preclinical stage, has recently been suggested (2, 3). In support of this proposition is the now well-established finding that functional impairment is clearly present in prodromal AD. Prior research by several groups (3–7) has shown that complex functional skills (Independent Activities of Daily Life, or IADLs) show impairment in patients with mild cognitive impairment (MCI) and continue to decline over time (5). In particular, financial capacity is a higher order functional skill that is highly sensitive and vulnerable to MCI and mild AD (4, 5, 8), which raises the possibility that measurable financial decline may also occur in persons with preclinical AD. It should be noted that current diagnostic criteria for preclinical AD explicitly contemplate and posit incipient subtle cognitive changes emerging in the third or “late” stage of the preclinical phase (9). Consistent with this theoretical view, recent studies have shown episodic memory impairments in older individuals with abnormal levels of brain amyloid (10, 11). The presence of detectable albeit subtle cognitive impairments in individuals with preclinical AD raises the possibility that associated subtle changes in complex functional activities may also be present and detectable. A critical factor here is the sensitivity of the functional measure employed. Detection of functional impairment in cognitively normal individuals with preclinical AD will require instruments sensitive to subclinical cognitive and functional changes. Informant report measures commonly used to characterize functional decline in late MCI and AD type dementia likely lack sensitivity to detect these very subtle functional changes. In contrast, performance based assessment measures may have sufficient sensitivity as they can support finely grained quantitative measurement using performance and task completion time variables. In the author’s view, in order to maximize detection of functional impairment in preclinical AD, proposed functional assessment measures should incorporate the following features: Assess cognitively complex functional abilities relevant to independent living and sensitive to early decline in AD. Assess the functional ability using an interval scaled, direct performance measure that evaluates performance variables in a highly detailed and granular manner. Include time limitations for performance items in order to enhance item difficulty. In addition to performance items, include task completion time variables in order to capture subtle processing speed changes.

Evaluating Interaction Techniques for Stack Mode Viewing

Three interaction techniques were evaluated for scrolling stack mode displays of volumetric data. Two used a scroll-wheel mouse: one used only the wheel, while another used a "click and drag" technique for fast scrolling, leaving the wheel for fine adjustments. The third technique used a Shuttle Xpress jog wheel. In a within-subjects design, nine radiologists searched stacked images for simulated hyper-intense regions on brain, knee, and thigh MR studies. Dependent measures were speed, accuracy, navigation path, and user preference. The radiologists considered the task realistic. They had high inter-subject variability in completion times, far larger than the differences between techniques. Most radiologists (eight out of nine) preferred familiar mouse-based techniques. Most participants scanned the data in two passes, first locating anomalies, then scanning for omissions. Participants spent a mean 10.4 s/trial exploring anomalies, with only mild variation between participants. Their rates of forward navigation searching for anomalies varied much more. Interaction technique significantly affected forward navigation rate (scroll wheel 5.4 slices/s, click and drag 9.4, and jog wheel 6.9). It is not clear what constrained the slowest navigators. The fastest navigator used a unique strategy of moving quickly just beyond an anomaly, then backing up. Eight naïve students performed a similar protocol. Their times and variability were similar to the radiologists, but more (three out of eight) students preferred the jog wheel. It may be worthwhile to introduce techniques such as the jog wheel to radiologists during training, and several techniques might be provided on workstations, allowing individuals to choose their preferred method.

Lower bounds for minimizing total completion time in a two-machine flow shop

For the $$\mathcal{NP}$$ -hard problem of scheduling n jobs in a two-machine flow shop so as to minimize the total completion time, we present two equivalent lower bounds that are computable in polynomial time. We formulate the problem by the use of positional completion time variables, which results in two integer linear programming formulations with O(n 2) variables and O(n) constraints. Solving the linear programming relaxation renders a very strong lower bound with an average relative gap of only 0.8% for instances with more than 30 jobs. We further show that relaxing the formulation in terms of positional completion times by applying Lagrangean relaxation yields the same bound, no matter which set of constraints we relax.

Single-Machine Scheduling with Precedence Constraints

We discuss the problem of sequencing precedence-constrained jobs on a single machine to minimize the average weighted completion time. This problem has attracted much attention in the mathematical programming community since Sidney’s pioneering work in 1975 (Sidney, J. B. 1975. Decomposition algorithms for single machine scheduling with precedence relations and deferral costs. Operations Research 23 283–298). We look at the problem from a polyhedral perspective and uncover a relation between Sidney’s decomposition theorem and different linear programming relaxations. More specifically, we present a generalization of Sidney’s result, which particularly allows us to reason that virtually all known 2-approximation algorithms are consistent with his decomposition. Moreover, we establish a connection between the single-machine scheduling problem and the vertex cover problem. Indeed, in the special case of series-parallel precedence constraints, we prove that the sequencing problem can be seen as a special case of the vertex cover problem. We also argue that this result is true for general precedence constraints if one can show that a certain integer program represents a valid formulation of the sequencing problem. Finally, we give a 3/2-approximation algorithm for two-dimensional partial orders, and we also provide a characterization of the active inequalities of a linear programming relaxation in completion time variables.

Single Machine Scheduling with Precedence Constraints

We discuss the problem of sequencing precedence-constrained jobs on a single machine to minimize the average weighted completion time. This problem has attracted much attention in the mathematical programming community since Sidney's pioneering work in 1975. We look at the problem from a polyhedral perspective and uncover a relation between Sidney's decomposition theorem and different linear programming relaxations. More specifically, we present a generalization of Sidney's result, which particularly allows us to reason that virtually all known 2-approximation algorithms comply with his decomposition. Moreover, we establish a connection between the single-machine scheduling problem and the vertex cover problem. Indeed, in the special case of series-parallel precedence constraints, we prove that the sequencing problem can be seen as a special case of the vertex cover problem. We also argue that this result is true for general precedence constraints if one can show that a certain integer program represents a valid formulation of the sequencing problem. Finally, we give a 3/2-approximation algorithm for two-dimensional partial orders, and we also provide a characterization of the active inequalities of a linear programming relaxation in completion time variables.

The Impact of Task-Related Information on Performance Variability

The focus of this study was regulation/control. One hundred and fifty subjects participated in a laboratory experiment in which they were given varying amounts of task-related information, in the form of instructions, on how to complete an assembly procedure. This resulted in the subjects completing the experimental task with a low, moderate, or high degree of task information prescribed for them. Generally, the findings of the study demonstrated that subjects in the less-controlled experimental groups have considerably greater variability of performance times, while participants given maximum task information had only a minimum degree of variability in completion times. The findings suggest that as the amount and appropriate timing of task information is optimized, variability among individuals completing the task decreases.