Improving physicians' performance with a stroke CDSS: A cognitive fit design approach

A large body of evidence over many years suggests that clinical decision support systems (CDSSs) can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. CDSSs have however failed to show their effectiveness due to poor ease of use and integration within clinical workflows. This research therefore emphasizes a cognitive fit design approach to developing an effective CDSS to solve those issues. According to the cognitive fit theory CDSS should align with the problem and task representation in order to match the physician's mental model to reduce cognitive effort. Several guidelines based on the cognitive fit design are proposed. A stroke CDSS prototype following the design guidelines is developed to demonstrate its feasibility. The system usability test results showed that the developed stroke CDSS was acceptably accurate, able to lessen the cognitive effort as desired, and preferable for use due to the significant reduction in cognitive load. The developed artifact has shown the potential to benefit physicians. Finally, implications and conclusions are discussed.     

Involving users in the design and usability evaluation of a clinical decision support system

AIM: To design and evaluate a clinical decision support system (CDSS) to support cardiovascular risk prevention in type 2 diabetes. METHODS: A preliminary requirements specification and three prototype CDSS interface designs were developed. Seven patients and seven clinicians conducted 'usability tests' on five different task scenarios with the CDSS prototypes to test its effectiveness, efficiency and 'user-friendliness'. Structured, qualitative questions explored their preferences for the different designs and overall impressions of clinical usefulness. RESULTS: Patients and clinicians were enthusiastic about the CDSS and used it confidently after a short learning period. Some patients had difficulty interpreting clinical data, but most were keen to see the CDSS used to help them understand their diabetes, provided a clinician explained their results. Clinicians' main concern was that the CDSS would increase consultation times. Changes suggested by users were incorporated into the final interface design. CONCLUSION: We have successfully incorporated patients' and clinicians' views into the design of a CDSS, but it was an arduous process.     

Attitude of Iranian physicians and nurses toward a clinical decision support system for pulmonary embolism and deep vein thrombosis

This research project sought to design and implement a computerized clinical decision support system (CDSS) that was able to identify patients who were at risk of pulmonary embolism (PE) and deep vein thrombosis (DVT), as well as produce reminders for prophylactic action for these diseases. The main purpose of the CDSS was to attempt to reduce the morbidity and mortality caused by embolism and thrombosis in patients admitted to hospitals. After implementation of this system in one of the large educational hospitals of Iran, a standard questionnaire was used, and interviews were conducted with physicians and nurses to evaluate the performance of the designed system for reducing the incidence of pulmonary embolism and thrombosis. From physicians and nurses’ point of view, a system which assists the medical staff in making better decisions regarding patient care, and also reminds pulmonary embolism and thrombosis preventive procedures with timely warnings, can influence patient care quality improvement and lead to the improved performance of the medical staff in preventing the incidence of pulmonary embolism and thrombosis.     

Clinical decision support system in medical knowledge literature review

The current study involved methodology and content analyses of abstracts of 30 clinical decision support system (CDSS) related studies with high impact factors. The main aim of the current work was to identify the performance and efficiency of CDSS, and enhance the understanding of CDSS for a better health management among the physicians and the patients. To add structure to the current study, major research areas were categorized based on a multidimensional unfolding analysis. In this regard, eight studies were conducted based on theoretical research, ten studies were related to the system and performance of CDSS, and 12 studies verified the efficacy through analysis and evaluation of CDSS. The results indicated that the above-mentioned studies on improvement in systematic performance. Then, based on the improvement, effectively used evaluations were conducted comparably. Moreover, 14 studies analyzed patients’ data and assessed decision support system (DSS). The related findings denoted that DSS has been mainly used for patient management and a large number of studies have verified its effectiveness, using several data to ensure its accuracy and reliability. In addition, the analyzed results of the abstracts and the titles were compared to find whether the titles of the literature articles reveal their content. Using these methodological studies, the academic outlook of medical informatics could be forecasted and the academic quality could be improved by resolving the problems, arising out of system development and realization processes. Such problems can be solved through analyses and interpretation of multilateral parameters, such as the trend in academic development, research direction, topics and methods.     

Using tablets in medical consultations: Single loop and double loop learning processes

ObjectiveThis paper investigates the influence of using tablet in waiting rooms and medical examinations on how physicians give information and how patients learn. It further assesses the factors that impact patient satisfaction.MethodsPatients and physicians in a primary care clinic were given a tablet device to search for health information in the waiting room, and when interacting with the physician, while physicians used the tablet device to share information with patients during the medical consultation. 82 patients completed a ‘pre’ survey on using tablets to search for health related information and a ‘post’ survey after their visit. Structural equation modeling was employed to analyze patient's perceptions.ResultsTablet use during consultation has a negative effect on patients' perceptions of physician information giving, but using the tablet in the waiting room has a positive impact on patient learning, perceptions of physicians' information giving and patient satisfaction.ConclusionsThis study indicates the importance of tablet use in ensuring information giving and patient learning. It further highlights the potential for tablets to promote single-loop learning in the medical encounter by better preparing patients for the physician's information giving. Tablets also enable double-loop learning, which leads to greater patient satisfaction.     

IMPACT OF REFLEXIVE ONTOLOGIES IN SEMANTIC CLINICAL DECISION SUPPORT SYSTEMS

Ontology processing is arguably a time-consuming process with high associated computational costs. Query actions constitute a crucial part of the reasoning process and are a primary source of time consumption. Reflexive ontologies (ROs) is a novel approach intended to reduce time consumption problems while providing a fast reaction from ontology-based applications.

In this article we present the implementation of a knowledge-based clinical decision support system (CDSS) for the diagnosis of Alzheimer's disease, which was the benchmark used to evaluate the impact of RO in the overall performance of the system.

The implementation details and the definition of the implementation methodology are exposed in this article, along with the results of the evaluation. Some novel techniques that aim to optimize the performance of ROs are also presented with highlights of the test application introduced in our previous work.     

Applying a belief rule-base inference methodology to a guideline-based clinical decision support system

Abstract: A critical issue in the clinical decision support system (CDSS) research area is how to represent and reason with both uncertain medical domain knowledge and clinical symptoms to arrive at accurate conclusions. Although a number of methods and tools have been developed in the past two decades for modelling clinical guidelines, few of those modelling methods have capabilities of handling the uncertainties that exist in almost every stage of a clinical decision-making process. This paper describes how to apply a recently developed generic rule-base inference methodology using the evidential reasoning approach (RIMER) to model clinical guidelines and the clinical inference process in a CDSS. In RIMER, a rule base is designed with belief degrees embedded in all possible consequents of a rule. Such a rule base is capable of capturing vagueness, incompleteness and non-linear causal relationships, while traditional IF–THEN rules can be represented as a special case. Inference in such a rule base is implemented using the evidential reasoning approach which has the capability of handling different types and degrees of uncertainty in both medical domain knowledge and clinical symptoms. A case study demonstrates that employing RIMER in developing a guideline-based CDSS is a valid novel approach.     

Healthcare support for underserved communities using a mobile social media platform

Emerging digital technologies for healthcare information support have already contributed to reducing the digital divide among rural communities. Although mobile health (m-health) applications facilitate provision of support for treatment consultation in real-time, their substantial potential has not yet been operationalised for decision support to meet citizen demand in developing nations. Modern healthcare information access, especially in rural areas of developing countries, is critical to effective healthcare, since both information and expert opinions are limited. Mobile phone and social media penetration, however, is often extensive. In this paper, we design and evaluate an innovative mobile decision support system (MDSS) solution for rural citizens healthcare decision support and information dissemination.Developed using a design science approach, the instantiated artifact connects underserved rural patients in Bangladesh to general practitioners (GPs) – allowing GPs, based on queries and information support provided, to evaluate patient conditions virtually and provide answers for further diagnosis or treatment. A cloud platform using social media embodies health record information and is used with a rating technique that matches queries to profiled remote experts, participating asynchronously. A comprehensive evaluation of the MDSS artifact ensures its utility, efficacy, and reliability.     

The computer in the consulting room: a psychological framework

Abstract

The use of an interactive computer system to aid the doctor with history taking and diagnosis is described. The system is developed for dyspepsia cases and is designed to be flexible enough to give the doctor considerable choice in the way it is used in the consulting room. We have observed and analysed its use by doctors in two very different settings; registrars and SHOs in an outpatient clinic, and GP trainers in a simulation exercise. All the doctors found individual ways of using the computer in the consultation, some chose to use it ‘conversationally’, alternating their attention between patient and computer, whilst others attempted to minimize its use while the patient was present. Patients’ reactions to the use of computers in general, and to their experience of this system specifically are described. The ways in which the computer imposes structure on the consultation and seems to influence the doctors’ decision processes are discussed. The complex dynamics of the interaction between patient, doctor and computer are outlined and are related to the cognitive load imposed. We raise ‘human factors’ issues, specific to the medical consultation environment, which need consideration in the design of future systems.     

A fuzzy classification model for myocardial infarction risk assessment

The use of data mining approaches for analyzing patients trace in different medical databases has become an important research field especially with the evolution of these methods and their contributions in medical decision support. In this paper, we develop a new clinical decision support system (CDSS) to diagnose Coronary Artery Diseases (CAD). According to CAD experts, Angiography is most accurate CAD diagnosis technique. However, it has many aftereffects and is very costly. Existing studies showed that CAD diagnosis requires heterogeneous patients traces from medical history while applying data mining techniques to achieve high accuracy. In this paper, an automatic approach to design CDSS for CAD assessment is proposed. The proposed diagnosis model is based on Random Forest algorithm, C5.0 decision tree algorithm and Fuzzy modeling. It consists of two stages: first, Random Forest algorithm is used to rank the features and a C5.0 decision tree based approach for crisp rule generation is developed. Then, we created the fuzzy inference system. The generation of fuzzy weighted rules is carried out automatically from the previous crisp rules. Moreover, a critical issue about the CDSS is that some values of the features are missing in most cases. A new method to deal with the problem of missing data, which allows evaluating the similarity despite the missing information, was proposed. Finally, experimental results underscore very promising classification accuracy of 90.50% while optimizing training time using UCI (the University of California at Irvine) heart diseases datasets compared to the previously reported results.     

Bridging challenges of clinical decision support systems with a semantic approach. A case study on breast cancer

The integration of Clinical Decision Support Systems (CDSS) in nowadays clinical environments has not been fully achieved yet. Although numerous approaches and technologies have been proposed since 1960, there are still open gaps that need to be bridged. In this work we present advances from the established state of the art, overcoming some of the most notorious reported difficulties in: (i) automating CDSS, (ii) clinical workflow integration, (iii) maintainability and extensibility of the system, (iv) timely advice, (v) evaluation of the costs and effects of clinical decision support, and (vi) the need of architectures that allow the sharing and reusing of CDSS modules and services. In order to do so, we introduce a new clinical task model oriented to clinical workflow integration, which follows a federated approach. Our work makes use of the reported benefits of semantics in order to fully take advantage of the knowledge present in every stage of clinical tasks and the experience acquired by physicians. In order to introduce a feasible extension of classical CDSS, we present a generic architecture that permits a semantic enhancement, namely Semantic CDSS (S-CDSS). A case study of the proposed architecture in the domain of breast cancer is also presented, pointing some highlights of our methodology.     

A group decision making support system in logistics and supply chain management

PurposeThe paper proposes a decision support system for selecting logistics providers based on the quality function deployment (QFD) and the technique for order preference by the similarity to ideal solution (TOPSIS) for agricultural supply chain in France. The research provides a platform for group decision making to facilitate decision process and check the consistency of the outcomes.MethodologyThe proposed model looks at the decision problem from two points of view considering both technical and customer perspectives. The main customer criteria are confidence in a safe and durable product, emission of pollutants and hazardous materials, social responsibility, etc. The main technical factors are financial stability, quality, delivery condition, services, etc. based on the literature review. The second stage in the adopted methodology is the combination of quality function deployment and the technique for order preference by similarity to ideal solution to effectively analyze the decision problem. In final section we structure a group decision system called GRoUp System (GRUS) which has been developed by Institut de Recherche en Informatique de Toulouse (IRIT) in the Toulouse University.ResultsThis paper designs a group decision making system to interface decision makers and customer values in order to aid agricultural partners and investors in the selection of third party logistic providers. Moreover, we have figured out a decision support system under fuzzy linguistic variables is able to assist agricultural parties in uncertain situations. This integrated and efficient decision support system enhances quality and reliability of the decision making.Novelty/OriginalityThe novelty of this paper is reflected by several items. The integration of group multi-criteria decision tools enables decision makers to obtain a comprehensive understanding of customer needs and technical requirements of the logistic process. In addition, this investigation is carried out under a European commission project called Risk and Uncertain Conditions for Agriculture Production Systems (RUC-APS) which models risk reduction and elimination from the agricultural supply chain. Ultimately, we have implemented the decision support tool to select the best logistic provider among France logistics and transportation companies.     

ENHANCEMENT OF THE CAPABILITIES OF AN NMR IMAGING MACHINE USING EXPERT SYSTEMS

ABSTRACT

Practical effectiveness of NMR imaging in diagnostic medicine can be considerably upgraded by incorporating into the machine high-level intelligent software support. Partly because NMR imaging is a relatively new technology, knowledge acquisition is essentially related to incoming new experience. Therefore an expert system approach to NMR medical applications should rely on rule induction techniques based on a series of example expert decisions. The complete project consists of three main components: (1) a protocol expert system, (2) a diagnosis expert system, and (3) a vision system. Expert system prototypes regarding part 1 and 2 of this study were built indicating preliminary interesting results. These results justify our attempts aimed at the enhancement of NMR capabilities as a diagnostic tool and consequent commercial benefits.     

End user computing in development administration: Importance of decision support systems

Abstract

Effective diffusion of microcomputers, as distinct from quick adoption, is concerned with a demand for applications. It requires a new approach on the part of information system professionals and administrators. Microcomputers will fail to contribute to the extent they should to Development if not accompanied by appropriate institutional reforms. A Decision Support System (DSS) facilitates the increasingly interdependent nature of the process, by linking information flows and organizational changes with improved decision making. The steps in the evolution of a decision support system for district administrators are discussed as a possible methodology for implementation. The paper concludes with practical guidelines for those initiating the process of end user computing, so that costly mistakes can be avoided.     

www.fevertravel.ch: an online study prototype to evaluate the safety and feasibility of computerized guidelines for fever in returning travellers and migrants

Following the paper publication of practice guidelines for the management of febrile patients returning from the tropics, we constructed a consultation website that comprises a decision chart and specific diagnostic features providing medical diagnostic assistance to primary care physicians. We then integrated a research component to evaluate the implementation of these computerized guidelines. This study website has the same interface as the consultation website. In addition, one is able to record: (i) the pathway followed by the physician through the decision chart, (ii) the diagnostic tests performed, (iii) the initial and final diagnoses as well as outcome and (iv) reasons for non-adherence when the physician diverges from the proposed attitude. We believe that Internet technology is a powerful medium to reach physicians of different horizons in their own environment, and could prove to be an effective research tool to disseminate practice guidelines and evaluate their appropriateness. Here we describe the design, content, architecture and system implementation of this interactive study prototype aimed at integrating operational research in primary care practice.     

Utilizing architectural styles to enhance the adaptation support of middleware platforms

ContextModern middleware platforms provide the applications deployed on top of them with facilities for their adaptation. However, the level of adaptation support provided by the state-of-the-art middleware solutions is often limited to dynamically loading and off-loading of software components. Therefore, it is left to the application developers to handle the details of change such that the system’s consistency is not jeopardized.ObjectiveWe aim to change the status quo by providing the middleware facilities necessary to ensure the consistency of software after adaptation. We would like these facilities to be reusable across different applications, such that the middleware can streamline the process of achieving safe adaptation.MethodOur approach addresses the current shortcomings by utilizing the information encoded in a software system’s architectural style. This information drives the development of reusable adaptation patterns. The patterns specify both the exact sequence of changes and the time at which those changes need to occur. We use the patterns to provide advanced adaptation support on top of an existing architectural middleware platform.ResultsOur experience shows the feasibility of deriving detailed adaptation patterns for several architectural styles. Applying the middleware to adapt two real-world software systems shows the approach is effective in consistently adapting these systems without jeopardizing their consistency.ConclusionWe conclude the approach is effective in alleviating the application developers from the responsibility of managing the adaptation process at the application-level. Moreover, we believe this study provides the foundation for changing the way adaptation support is realized in middleware solutions.     

A rule-based control method for a multi-loop production system

A multi-loop integrated-circuit production system is difficult to control due to the complex process flow and the dynamic changing environment. The search for the best control strategy is a multi-objective problem subject to a variety of constraints.This paper describes a rule-based decision support system (RBDSS) for finding the best solution for various needs in order to satisfy the user's multiple goals. This method stores coefficients of equations of regression between the performance measure and a set of the control variables, and searches for the best performances on an interactive basis.The performance of RBDSS is compared with that of a non-AI method (CDSS) in the same experimental case.     

Leveraging decision‐making tools in capacity building planning: The Indonesian scientific network case

Abstract

The development of investment alternatives for the Government of Indonesia's proposed scientific network forms the background to this case. The goal was to rationalize a structure for developing and sustaining a broad‐based network capable of serving scientists throughout the country, including very remote areas. It became clear that one approach could combine both technological as well as entrepreneurial elements, since the data communications linkages for serving scientists could also be available for private customers. The process of defining and costing out this approach was a textbook example of a bottom‐up analysis, beginning with customer needs and working toward structures to satisfy the needs. The World Bank and the Government of Indonesia are in the process of implementing several features of the recommended system. The proposed approach can ultimately pay for itself through private sector revenues for user services. While the context of the decision is telecommunications, the methodology is appropriate for many decision‐making situations. Samples of actual data and bottom‐line results are discussed.     

Fuzzy cognitive map software tool for treatment management of uncomplicated urinary tract infection

Uncomplicated urinary tract infection (uUTI) is a bacterial infection that affects individuals with normal urinary tracts from both structural and functional perspective. The appropriate antibiotics and treatment suggestions to individuals suffer of uUTI is an important and complex task that demands a special attention. How to decrease the unsafely use of antibiotics and their consumption is an important issue in medical treatment. Aiming to model medical decision making for uUTI treatment, an innovative and flexible approach called fuzzy cognitive maps (FCMs) is proposed to handle with uncertainty and missing information. The FCM is a promising technique for modeling knowledge and/or medical guidelines/treatment suggestions and reasoning with it. A software tool, namely FCM-uUTI DSS, is investigated in this work to produce a decision support module for uUTI treatment management. The software tool was tested (evaluated) in a number of 38 patient cases, showing its functionality and demonstrating that the use of the FCMs as dynamic models is reliable and good. The results have shown that the suggested FCM-uUTI tool gives a front-end decision on antibiotics’ suggestion for uUTI treatment and are considered as helpful references for physicians and patients. Due to its easy graphical representation and simulation process the proposed FCM formalization could be used to make the medical knowledge widely available through computer consultation systems.