1,720,977 research outputs found
Integrating the internet of things and big data analytics into decision support models for healthcare management
No full textPurpose – This paper presents formulations of decision models for the innovative management of healthcare systems
through the application of the Internet of Things (IoT) and Big Data Analytics (BDA). By integrating the technology of IoT
and the intelligence of BDA we derive service designs that amplify the personalized, co-creative nature of effective health
care. Capturing and interpreting data about patients’ needs and desires, resource availabilities (doctors, nurses, medical
equipment, medical supplies and others), treatment options and potential outcomes enables a smart and adaptive health
management system for planning, scheduling and coordinating service activities in a jointly managed, co-creative system.
From a service-system point of view (Maglio et al., 2009), healthcare systems are configurations of people, information,
organizations, and technologies operating together for mutual benefit and common objectives. The traditional approaches to
the design of these service system take one of two perspectives: a patient-centric view, oriented to patient health (Polese,
2013) in terms of quality and speed of care; and a provider view, focused on resource utilization and efficiency (patient
waiting time or service level is the only consideration given to the patient - Sarno and Nenni, 2016). In the new digitization
era, the design and management of healthcare services should structurally incorporate both perspectives under the awareness
that service itself means value co-creation among the involved actors (Vargo and Lusch, 2004), personalizing the health care
experience for each patient and adapting organizational and planning processes to context variability.
Large investments in fixed assets and highly trained staffs severely limit the flexibility in capacity of every healthcare
service system. The inertia of the supply chain limits its ability to respond to the non-stationary nature of demand that is
driven by individual patient needs. Therefore, resource allocations that are typically used in other service industries to
respond to variable demand are not effective in healthcare systems. The use of IoT and BDA to generate more accurate and
dynamic updates of parameters that affect demand and resource availability enables a different approach known as demand
response (DR). Electric utilities are a good example of an inertia-constrained supply chain that uses IoT and BDA to enable
DR (Siano and Sarno, 2016). Although healthcare service systems presently do not adopt the practice of DR, the necessary
technologies are in place to do so. An essential requirement of DR is also an innovative feature of this practice – DR
requires co-creation. Through the application of finite capacity scheduling (FCS) a healthcare system can utilize real-time
data about patient locations, medical conditions and desires to dynamically assign patients and healthcare resources to
medical procedures for improved efficiency in the use of healthcare resources and the personalization of patient care. This
research formulates the key decision models that will support DR in healthcare systems and take advantage of IoT and BDA.
We identify the unique tradeoffs that DR presents to the design and management of healthcare systems, specify the data
requirements of the predictive models that are recommended, formulate the mathematical structure of the decision models
and describe the changes to the management and culture of the healthcare ecosystem that will be necessary.
Design/Methodology/approach – The formulation of adaptive, intelligent decision models for planning, scheduling and
controlling health care services will be accomplished through application of the techniques of operations research guided by
the perspective of Service Dominant Logic (SDL) and the Viable Systems Approach (VSA). Although these decision
models can trace their pedigree to classic resource planning and scheduling models of goods-dominant research, they
embody distinctive and essential features of co-creative systems. Our formulations of these models will expose these
features. The state of the art in the application of IoT and BDA in healthcare enables the acquisition of massive amounts of
detailed data from patient electronic medical records; real-time patient condition monitors; location devices for patients,
healthcare personnel, medical equipment; social networks’ comments; resource status reports and schedules; and intelligent
medical knowledge bases. Furthermore, cognitive assistants are now providing medical professionals with up-to-date
knowledge to support diagnosis and treatment. Our model formulations will be directed at defining the specific model
constructs that take advantage of the recent advances in IoT and BDA. Specifically, we will develop a hierarchy of models
that exhibit the benefits of utilizing increasing penetrations of big data sources and increasing degrees of decision adaptation
(homeostasis).
Findings – 1) How can big data inform us about the needs and desires of all of the players in the health care system? 2)
How can big data analytics be used in predicting patient needs and desires as well as the intentions of healthcare providers?
3) How can IoT enable the beneficial usage of big data for co-creative healthcare management?
Research limitations/implications - This research represents the first step of a wider research project aimed at assessing the
feasibility and the convenience of new forms of value co-creation in healthcare management. The suite of models that this
research creates will initiate a quantitative evaluation of the relative performance of the models in the suite. However, this
evaluation, which will be done via computer simulation, is outside the scope of the current paper.
Ultimately, our models will demonstrate the specific ways in which BDA and IoT can be used effectively in healthcare
management. Service innovators in the healthcare industry will be able to use the results of this stream of research to see
beyond the hype of these new technologies and learn how to leverage them effectively.
Originality/value – The advances in the engineering of IoT devices and the development of statistical methods for BDA
have been very impressive. The applications of these technologies have been heavily promoted, but there has been very
little research into the integration of IoT and BDA into model-based decision support systems. This study will be original in
its foundation in decision modeling
Approximating probability density functions and their convolutions using orthogonal polynomials
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Availability Analysis for the Quasi-Renewal Process with an Age-Dependent Preventive Maintenance Policy
No full textA quasi-renewal process is more realistic in modeling the behavior of a repairable system than traditional models such as perfect repair and minimal repair since it reflects the deterioration process of the system over time while traditional models do not. The quasi-renewal parameter is set to a value between 0 and 1 to indicate the rate of deterioration. Moreover, a quasi-renewal process can also be used to model the increasing time of maintenance actions due to the increasing difficulty of maintaining an aging system by setting the parameter to a value larger than 1. We construct a model where the operating times follow a quasi-renewal process and the corrective/preventive maintenance times follow another quasi-renewal process. A quasi-renewal function and two equivalent point availability expressions are developed for the model described by a quasi-renewal process with and age-dependent preventive maintenance policy. In addition, numerical results from various theoretical distributions are obtained to illustrate the behavior of the models. The two equivalent point availability functions each contains an infinite sum and must be truncated to obtain a numerical approximation. The two approximated point availability functions form upper and lower bounds on the real value. The bounds are useful for determining the result accuracy, which can be arbitrarily increased by adding more terms to the truncated summation. Our framework provides a new time-dependent availability model for a non-stationary process with a preventive maintenance policy without any cost structure or optimization problem.Ph. D
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