scholarly journals Defeating information overload in health surveillance using a metacognitive aid innovation from military combat systems

2016 ◽  
Vol 14 (4) ◽  
pp. 371-388 ◽  
Author(s):  
Daniel C McFarlane ◽  
Alexa K Doig ◽  
James A Agutter ◽  
Jonathan L Mercurio ◽  
Ranjeev Mittu ◽  
...  
Keyword(s):  
Decision Making ◽  
Information Overload ◽  
High Volume ◽  
Health Surveillance ◽  
Simulated Patients ◽  
Naval Research ◽  
Hospital Nurses ◽  
Volume Data ◽  
Front Line ◽  
Training Requirement

Modern sensors for health surveillance generate high volumes and rates of data that currently overwhelm operational decision-makers. These data are collected with the intention of enabling front-line clinicians to make effective clinical judgments. Ironically, prior human–systems integration (HSI) studies show that the flood of data degrades rather than aids decision-making performance. Health surveillance operations can focus on aggregate changes to population health or on the status of individual people. In the case of clinical monitoring, medical device alarms currently create an information overload situation for front-line clinical workers, such as hospital nurses. Consequently, alarms are often missed or ignored, and an impending patient adverse event may not be recognized in time to prevent crisis. One innovation used to improve decision making in areas of data-rich environments is the Human Alerting and Interruption Logistics (HAIL) technology, which was originally sponsored by the US Office of Naval Research. HAIL delivers metacognitive HSI services that empower end-users to quickly triage interruptions and dynamically manage their multitasking. HAIL informed our development of an experimental prototype that provides a set of context-enabled alarm notification services (without automated alarm filtering) to support users’ metacognition for information triage. This application is called HAIL Clinical Alarm Triage (HAIL-CAT) and was designed and implemented on a smartwatch to support the mobile multitasking of hospital nurses. An empirical study was conducted in a 20-bed virtual hospital with high-fidelity patient simulators. Four teams of four registered nurses (16 in total) participated in a 180-minute simulated patient care scenario. Each nurse was assigned responsibility to care for five simulated patients and high rates of simulated health surveillance data were available from patient monitors, infusion pumps, and a call light system. Thirty alarms per nurse were generated in each 90-minute segment of the data collection sessions, only three of which were clinically important alarms. The within-subjects experimental design included a treatment condition where the nurses used HAIL-CAT on a smartwatch to triage and manage alarms and a control condition without the smartwatch. The results show that, when using the smartwatch, nurses responded three times faster to clinically important and actionable alarms. An analysis of nurse performance also shows no negative effects on their other duties. Subjective results show favorable opinions about utility, usability, training requirement, and adoptability. These positive findings suggest the potential for the HAIL HSI system to be transferrable to the domain of health surveillance to achieve the currently unrealized potential utility of high-volume data.

scholarly journals Performance Measurement of Complex Event Platforms

2016 ◽  
Vol 40 (2) ◽  
pp. 237-254
Author(s):  
Eva Zámečníková ◽  
Jitka Kreslíková
Keyword(s):  
Decision Making ◽  
High Frequency ◽  
High Volume ◽  
Business Rules ◽  
Volume Data ◽  
Multiple Sources ◽  
Integrated Method ◽  
Pros And Cons ◽  
Platform Independence ◽  
Best Fit

The aim of this paper is to find and compare existing solutions of complex event processing platforms (CEP). CEP platforms generally serve for processing and/or predicting of high frequency data. We intend to use CEP platform for processing of complex time series and integrate a solution for newly proposed method of decision making. The decision making process will be described by formal grammar. As there are lots of CEP solutions we will take the following characteristics under consideration - the processing in real time, possibility of processing of high volume data from multiple sources, platform independence, platform allowing integration with user solution and open license. At first we will talk about existing CEP tools and their specific way of use in praxis. Then we will mention the design of method for formalization of business rules used for decision making. Afterwards, we focus on two platforms which seem to be the best fit for integration of our solution and we will list the main pros and cons of each approach. Next part is devoted to benchmark platforms for CEP. Final part is devoted to experimental measurements of platform with integrated method for decision support.

scholarly journals Impact of cardiopulmonary resuscitation on a cannot intubate, cannot oxygenate condition: a randomised crossover simulation research study of the interaction between two algorithms

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e030430
Author(s):  
Thomas Ott ◽  
Jascha Stracke ◽  
Susanna Sellin ◽  
Marc Kriege ◽  
Gerrit Toenges ◽  
...  
Keyword(s):  
Decision Making ◽  
Cardiac Arrest ◽  
Cardiopulmonary Resuscitation ◽  
Primary Outcome ◽  
Research Study ◽  
University Hospital ◽  
Simulated Patients ◽  
Stressful Situation ◽  
Simulation Research ◽  
Simulation Centre

ObjectivesDuring a ‘cannot intubate, cannot oxygenate’ situation, asphyxia can lead to cardiac arrest. In this stressful situation, two complex algorithms facilitate decision-making to save a patient’s life: difficult airway management and cardiopulmonary resuscitation. However, the extent to which competition between the two algorithms causes conflicts in the execution of pivotal treatment remains unknown. Due to the rare incidence of this situation and the very low feasibility of such an evaluation in clinical reality, we decided to perform a randomised crossover simulation research study. We propose that even experienced healthcare providers delay cricothyrotomy, a lifesaving approach, due to concurrent cardiopulmonary resuscitation in a ‘cannot intubate, cannot oxygenate’ situation.DesignDue to the rare incidence and dynamics of such a situation, we conducted a randomised crossover simulation research study.SettingWe collected data in our institutional simulation centre between November 2016 and November 2017.ParticipantsWe included 40 experienced staff anaesthesiologists at our tertiary university hospital centre.InterventionThe participants treated two simulated patients, both requiring cricothyrotomy: one patient required cardiopulmonary resuscitation due to asphyxia, and one patient did not require cardiopulmonary resuscitation. Cardiopulmonary resuscitation was the intervention. Participants were evaluated by video records.Primary outcome measuresThe difference in ‘time to ventilation through cricothyrotomy’ between the two situations was the primary outcome measure.ResultsThe results of 40 participants were analysed. No carry-over effects were detected in the crossover design. During cardiopulmonary resuscitation, the median time to ventilation was 22 s (IQR 3–40.5) longer than that without cardiopulmonary resuscitation (p=0.028), including the decision-making time.ConclusionCricothyrotomy, which is the most crucial treatment for cardiac arrest in a ‘cannot intubate, cannot oxygenate’ situation, was delayed by concurrent cardiopulmonary resuscitation. If cardiopulmonary resuscitation delays cricothyrotomy, it should be interrupted to first focus on cricothyrotomy.

scholarly journals Monoclonal Antibody-Based Immunotherapy and Its Role in the Development of Cardiac Toxicity

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 86
Author(s):  
Mohit Kumar ◽  
Chellappagounder Thangavel ◽  
Richard C. Becker ◽  
Sakthivel Sadayappan
Keyword(s):  
Cancer Patients ◽  
Immune Modulation ◽  
Checkpoint Inhibitors ◽  
Survival Rates ◽  
Induced Pluripotent Stem Cell ◽  
High Volume ◽  
Oncolytic Viruses ◽  
Model Systems ◽  
Volume Data ◽  
Late Cardiotoxicity

Immunotherapy is one of the most effective therapeutic options for cancer patients. Five specific classes of immunotherapies, which includes cell-based chimeric antigenic receptor T-cells, checkpoint inhibitors, cancer vaccines, antibody-based targeted therapies, and oncolytic viruses. Immunotherapies can improve survival rates among cancer patients. At the same time, however, they can cause inflammation and promote adverse cardiac immune modulation and cardiac failure among some cancer patients as late as five to ten years following immunotherapy. In this review, we discuss cardiotoxicity associated with immunotherapy. We also propose using human-induced pluripotent stem cell-derived cardiomyocytes/ cardiac-stromal progenitor cells and cardiac organoid cultures as innovative experimental model systems to (1) mimic clinical treatment, resulting in reproducible data, and (2) promote the identification of immunotherapy-induced biomarkers of both early and late cardiotoxicity. Finally, we introduce the integration of omics-derived high-volume data and cardiac biology as a pathway toward the discovery of new and efficient non-toxic immunotherapy.

The use and non-use of the government financial report by Maltese Members of Parliament

2018 ◽  
Vol 31 (4) ◽  
pp. 1124-1144 ◽  
Author(s):  
Josette Caruana ◽  
Brady Farrugia
Keyword(s):  
Decision Making ◽  
Information Overload ◽  
Qualitative Interviews ◽  
Financial Reports ◽  
Content Type ◽  
Financial Report ◽  
Members Of Parliament ◽  
The Government ◽  
And Performance ◽  
Questionnaire Research

Purpose The purpose of this paper is to examine the use and non-use of the Government Financial Report by Maltese Members of Parliament (MPs). It refers to information overload theory to analyse the gap between financial reports and their relevance for decision making. Design/methodology/approach A mix of qualitative (interviews) and quantitative (questionnaire) research tools are applied, with the Maltese MPs being the research participants. This method is acclaimed to be comprehensive, but this study highlights certain disadvantages when applied in the political arena. Findings The characteristics of the information itself could be the main cause of information overload, resulting in the non-use of the financial report for decision making. Politicians refer to financial data for their decision making, but not to the data presented in the financial report. Irrespective of the politician’s professional background, the data in the financial report is perceived as incomplete and outdated. Practical implications The cause of information overload and its effects are important considerations for preparers of financial information and accounting standard setters, if they wish that their production is relevant for decision makers. Originality/value There is an increase in research concerning politicians’ use of budgetary and performance information, at local and regional levels of government. This study investigates exclusively the use of the financial report by politicians at central level, in a politically stable environment.

scholarly journals THE HOSPITAL EPIDEMIOLOGICAL SURVEILLANCE NETWORK AS NA INSRUMENT FOR THE STRENGTHENING OF COMPULSORY DISEASE AND CONSEQUENTIAL NOTIFICATION, PERNAMBUCO 2018

2021 ◽  
pp. 12
Author(s):  
◽  
Keyword(s):  
Decision Making ◽  
Information System ◽  
Descriptive Study ◽  
Health Surveillance ◽  
Data Sources ◽  
Epidemiological Surveillance ◽  
Surveillance Network ◽  
Study Type ◽  
Compulsory Notification ◽  
Made In

Objetive: Describe the contribution of the State Hospital Epidemiological Surveillance Network of Pernambuco (VEH/PE) for the registration of cases of diseases and conditions of immediate compulsory notification, in Pernambuco, 2018. Methods: Descriptive study, type of experience report, of surveillance of 31 hospitals of the VEH / PE Network, in 2018. The data sources were from the Notifiable Diseases Information System and the data referring to DNCI were from FormSus, available on the Center’s Platform Strategic Health Surveillance Information. The proportions of notifications for Compulsory Notification Disease from the VEH/PE Network were calculated in relation to the total number of notifications made at Sinan. Results: Among the DNC notifications registered by Sinan (Net, Online and Web influenza, 30,1% came from the 31 hospitals of the VEH/PE Network. When analyzed, by information system, the Network was responsible for 28,4% of the records made in Sinan Net by 2.687 reporting units, in Sinan Online, 25,9% in relation to 1.247 reporting units and for Sinan Web Influenza the contribution was 82,3% in relation to the 69 reporting units. Immediate compulsory notification diseases/conditions communicated to CIEVS, 50,2% of the communications came from the Network As for the opportunity for immediate notification of diseases and conditions, 90,7% were communicated in due time by the VEH/PE Network. Conclusion: It is important to strengthen the Network aiming at surveillance, disease/disease control and operationalization of information systems, in order to support the manager in decision making.

Interactive Multi-Modal Visualization Environment for Complex System Decision Making

2008 ◽  
Author(s):  
Jung Leng Foo ◽  
Eliot Winer
Keyword(s):  
Complex System ◽  
Decision Making ◽  
Three Dimensional ◽  
Image Data ◽  
Detailed Examination ◽  
Surgical Instruments ◽  
Input Device ◽  
Volume Data ◽  
Evaluation Tool ◽  
Standard Format

Decision making in a complex system requires a large amount of data, and real time interaction and visualization tools become effective solutions. Constant improvement in computer graphics technology has encouraged the research of developing better and more efficient ways of interacting and visualizing complex three-dimensional image data. This paper presents a unique software framework for interacting and visualizing complex volume image data in a virtual environment. For efficient user interactions, a wireless gamepad controller is used as the main input device. The buttons and joysticks on the gamepad controller are intuitively mapped to perform different functions depending on the feature mode that the software is currently in. Apart from the general viewer, an extension of the software also reads in standard format patient medical images such as CT/MRI scans. As an effective decision making tool, the software allows the user to apply fast pseudo-coloring and multiple interactive oblique clipping planes for an immersive detailed examination of any 3D model. In the medical imaging extension of this software, it features the ability for the user to select a specific range of tissue densities to render and an endosurgery planning mode that allows a surgeon to place simulated laparoscopic surgical instruments in a virtual model of the patient. The developed software allows for better interaction with complex volume data for use as a decision making and evaluation tool.

Enhancing Citizens' Participation via Recommender Systems

2020 ◽  
pp. 624-650
Author(s):  
Luis Terán
Keyword(s):  
Decision Making ◽  
Semantic Web ◽  
Private Sector ◽  
Web 2.0 ◽  
Recommender Systems ◽  
Search Engines ◽  
Information Overload ◽  
Relevant Information ◽  
Research Topic ◽  
Government Services

With the introduction of Web 2.0, which includes users as content generators, finding relevant information is even more complex. To tackle this problem of information overload, a number of different techniques have been introduced, including search engines, Semantic Web, and recommender systems, among others. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. In this chapter, the use of recommender systems on eParticipation is presented. A brief description of the eGovernment Framework used and the participation levels that are proposed to enhance participation. The highest level of participation is known as eEmpowerment, where the decision-making is placed on the side of citizens. Finally, a set of examples for the different eParticipation types is presented to illustrate the use of recommender systems.

Intelligent Agents in Decision Support Systems

2011 ◽  
pp. 857-866 ◽  
Author(s):  
Gloria E Phillips-Wren
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Intelligent Agents ◽  
Intelligent Systems ◽  
Information Overload ◽  
Support Systems ◽  
Distributed Decision Making ◽  
Intelligent Decision ◽  
Intelligent Decision Support Systems

Internet-based, distributed systems have become essential in modern organizations. When combined with artificial intelligence (AI) techniques such as intelligent agents, such systems can become powerful aids to decision makers. These newer intelligent systems have extended the scope of traditional decision support systems (DSSs) to assist users with real-time decision making, multiple information flows, dynamic data, information overload, time-pressured decisions, inaccurate data, difficult-to-access data, distributed decision making, and highly uncertain decision environments. As a class, they are called intelligent decision support systems (IDSSs).

Transforming data into information

2003 ◽  
Vol 47 (2) ◽  
pp. 43-51 ◽  
Author(s):  
M.B. Beck ◽  
Z. Lin
Keyword(s):  
High Volume ◽  
Recursive Estimation ◽  
Data Sets ◽  
Monitoring Networks ◽  
Volume Data ◽  
Demand Pull ◽  
Variable Character ◽  
History Of ◽  
On Line ◽  
Automated Instruments

In spite of a long history of automated instruments being deployed in the water industry, only recently has the difficulty of extracting timely insights from high-grade, high-volume data sets become an important problem. Put simply, it is now relatively easy to be “data-rich”, much less easy to become “information-rich". Whether the availability of so many data arises from “technological push” or the “demand pull” of practical problem solving is not the subject of discussion. The paper focuses instead on two issues: first, an outline of a methodological framework, based largely on the algorithms of (on-line) recursive estimation and involving a sequence of transformations to which the data can be subjected; and second, presentation and discussion of the results of applying these transformations in a case study of a biological system of wastewater treatment. The principal conclusion is that the difficulty of transforming data into information may lie not so much in coping with the high sampling intensity enabled by automated monitoring networks, but in coming to terms with the complexity of the higher-order, multi-variable character of the data sets, i.e., in interpreting the interactions among many contemporaneously measured quantities.

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