Strategies for dynamic appointment making by container terminals

We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much

A Primer on Quality Assurance and Performance Improvement for Interprofessional Chronic Kidney Disease Care: A Path to Joint Commission Certification.

Interprofessional care for chronic kidney disease facilitates the delivery of high quality, comprehensive care to a complex, at-risk population. Interprofessional care is resource intensive and requires a value proposition. Joint Commission certification is a voluntary process that improves patient outcomes, provides external validity to hospital administration and enhances visibility to patients and referring providers. This is a single-center, retrospective study describing quality assurance and performance improvement in chronic kidney disease, Joint Commission certification and quality outcomes. A total of 440 patients were included in the analysis. Thirteen quality indicators consisting of clinical and process of care indicators were developed and measured for a period of two years from 2009-2017. Significant improvements or at least persistently high performance were noted for key quality indicators such as blood pressure control (85%), estimation of cardiovascular risk (100%), measurement of hemoglobin A1c (98%), vaccination (93%), referrals for vascular access and transplantation (100%), placement of permanent dialysis access (61%), discussion of advanced directives (94%), online patient education (71%) and completion of office visit documentation (100%). High patient satisfaction scores (94-96%) are consistent with excellent quality of care provided

Reports Of Conferences, Institutes, And Seminars

This quarter\u27s column offers coverage of multiple sessions from the 2016 Electronic Resources & Libraries (ER&L) Conference, held April 3–6, 2016, in Austin, Texas. Topics in serials acquisitions dominate the column, including reports on altmetrics, cost per use, demand-driven acquisitions, and scholarly communications and the use of subscriptions agents; ERMS, access, and knowledgebases are also featured

Appointment reminder systems are effective but not optimal: results of a systematic review and evidence synthesis employing realist principles

Missed appointments are an avoidable cost and resource inefficiency which impact upon the health of the patient and treatment outcomes. Healthcare services are increasingly utilizing reminder systems to manage these negative effects. This study explores the effectiveness of reminder systems for promoting attendance, cancellations and rescheduling of appointments across all healthcare settings and for particular patient groups and the contextual factors which indicate that reminders are being employed sub-optimally. We used three inter-related reviews of quantitative and qualitative evidence. Firstly, using pre-existing models and theories, we developed a conceptual framework to inform our understanding of the Contexts and Mechanisms which influence reminder effectiveness. Secondly, we performed a review following Centre for Reviews & Dissemination (CRD) guidelines to investigate the effectiveness of different methods of reminding patients to attend health service appointments. Finally, to supplement the effectiveness information, we completed a review informed by realist principles to identify factors likely to influence non-attendance behaviors and the effectiveness of reminders. We found consistent evidence that all types of reminder systems are effective at improving appointment attendance across a range of health care settings and patient populations. Reminder systems may also increase cancellation and rescheduling of unwanted appointments. “Reminders plus”, which provide additional information beyond the reminder function, may be more effective than simple reminders at reducing non-attendance at appointments in particular circumstances. We identified six areas of inefficiency which indicate that reminder systems are being used sub-optimally. Unless otherwise indicated, all patients should receive a reminder to facilitate attendance at their healthcare appointment. The choice of reminder system should be tailored to the individual service. To optimize appointment and reminder systems, healthcare services need supportive administrative processes to enhance attendance, cancellation, rescheduling and re-allocation of appointments to other patients

A Review and Characterization of Progressive Visual Analytics

Progressive Visual Analytics (PVA) has gained increasing attention over the past years. It brings the user into the loop during otherwise long-running and non-transparent computations by producing intermediate partial results. These partial results can be shown to the user for early and continuous interaction with the emerging end result even while it is still being computed. Yet as clear-cut as this fundamental idea seems, the existing body of literature puts forth various interpretations and instantiations that have created a research domain of competing terms, various definitions, as well as long lists of practical requirements and design guidelines spread across different scientific communities. This makes it more and more difficult to get a succinct understanding of PVA’s principal concepts, let alone an overview of this increasingly diverging field. The review and discussion of PVA presented in this paper address these issues and provide (1) a literature collection on this topic, (2) a conceptual characterization of PVA, as well as (3) a consolidated set of practical recommendations for implementing and using PVA-based visual analytics solutions

Optical coherence tomography-based consensus definition for lamellar macular hole.

BackgroundA consensus on an optical coherence tomography definition of lamellar macular hole (LMH) and similar conditions is needed.MethodsThe panel reviewed relevant peer-reviewed literature to reach an accord on LMH definition and to differentiate LMH from other similar conditions.ResultsThe panel reached a consensus on the definition of three clinical entities: LMH, epiretinal membrane (ERM) foveoschisis and macular pseudohole (MPH). LMH definition is based on three mandatory criteria and three optional anatomical features. The three mandatory criteria are the presence of irregular foveal contour, the presence of a foveal cavity with undermined edges and the apparent loss of foveal tissue. Optional anatomical features include the presence of epiretinal proliferation, the presence of a central foveal bump and the disruption of the ellipsoid zone. ERM foveoschisis definition is based on two mandatory criteria: the presence of ERM and the presence of schisis at the level of Henle's fibre layer. Three optional anatomical features can also be present: the presence of microcystoid spaces in the inner nuclear layer (INL), an increase of retinal thickness and the presence of retinal wrinkling. MPH definition is based on three mandatory criteria and two optional anatomical features. Mandatory criteria include the presence of a foveal sparing ERM, the presence of a steepened foveal profile and an increased central retinal thickness. Optional anatomical features are the presence of microcystoid spaces in the INL and a normal retinal thickness.ConclusionsThe use of the proposed definitions may provide uniform language for clinicians and future research

Acoustic, psychophysical, and neuroimaging measurements of the effectiveness of active cancellation during auditory functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is one of the principal neuroimaging techniques for studying human audition, but it generates an intense background sound which hinders listening performance and confounds measures of the auditory response. This paper reports the perceptual effects of an active noise control (ANC) system that operates in the electromagnetically hostile and physically compact neuroimaging environment to provide significant noise reduction, without interfering with image quality. Cancellation was first evaluated at 600 Hz, corresponding to the dominant peak in the power spectrum of the background sound and at which cancellation is maximally effective. Microphone measurements at the ear demonstrated 35 dB of acoustic attenuation [from 93 to 58 dB sound pressure level (SPL)], while masked detection thresholds improved by 20 dB (from 74 to 54 dB SPL). Considerable perceptual benefits were also obtained across other frequencies, including those corresponding to dips in the spectrum of the background sound. Cancellation also improved the statistical detection of sound-related cortical activation, especially for sounds presented at low intensities. These results confirm that ANC offers substantial benefits for fMRI research

Managerial Intervention Strategies to Reduce Patient No-Show Rates

High patient no-show rates increase health care costs, decrease healthcare access, and reduce the clinical efficiency and productivity of health care facilities. The purpose of this exploratory qualitative single case study was to explore and analyze the managerial intervention strategies healthcare administrators use to reduce patient no-show rates. The targeted research population was active American College of Healthcare Executives (ACHE), Hawaii-Pacific Chapter healthcare administrative members with operational and supervisory experience addressing administrative patient no-show interventions. The conceptual framework was the theory of planned behavior. Semistructured interviews were conducted with 4 healthcare administrators, and appointment cancellation policy documents were reviewed. Interpretations of the data were subjected to member checking to ensure the trustworthiness of the findings. Based on the methodological triangulation of the data collected, 5 common themes emerged after the data analysis: reform appointment cancellation policies, use text message appointment reminders, improve patient accessibility, fill patient no-show slots immediately, and create organizational and administrative efficiencies. Sharing the findings of this study may help healthcare administrators to improve patient health care accessibility, organizational performance and the social well-being of their communities

Effect of Neural Network on Reduction of Noise for Edge Detection

Processing photographic images is important in many applications, among them the development of automated driver assistance systems (ADAS) and autonomous vehicles. Many techniques are used for processing images, including neural networks, other types of machine learning, and edge detection. One common issue with processing these photos is the presence of noise, whether caused by the camera itself or by physical conditions (e.g., weather conditions or dirt on road signs). In this paper, a neural network is used for noise reduction to improve edge detection results and tested with two kinds of noise, Gaussian and salt & pepper noise, and three different edge detection algorithms, Canny, Sobel, and Zhang. Results showed that the noise reduction process was effective in improving performance of the edge detection process, with the exception of conditions where the noise was originally very minimal