EVALUATING DIAGNOSES , TREATMENT AND INFERENCE ACTIVITIES IN THE INFORMATION SYSTEMS PROFESSION

Information systems (IS) is a field that influnces and is influnced by the work of many different academics and practitioners. The influnce of IS to other areas of knowledge (i.e. management) has led some people to argu in favor and against the idea that IS has become a reference field of knowledge. Focusing on either knowledge elements or knowledge activities of a reference field leaves out consideration of relationships and interactions through time between both. \ Following Abbott´s sociology of professional knowledge, this paper proposes a triad of analytical categories: ˜Diagnoses´, ˜Treatments´ and ˜Inferences´ to examine and advance a more comprehensive understanding of the development of IS. Our analysis, based on a pilot survey of five IS journals, suggests that the key focus of IS activity has been on refining methodologies (treatments). The field has been less explicit and inclusive in generating and disseminating diagnoses and inferences. \ Those people working in the field can and should make available untapped stocks of knowledge in relation to these two elements whilst attempting to expand the jurisdiction (ownership) of IS over different problems. They can do so by relating more strongly methodologies to how IS problems can be defined and theorized upon. As this is work in progress, we propose a number of implications that we intend to explore in further research.

Formal nursing terminology systems: a means to an end

In response to the need to support diverse and complex information requirements, nursing has developed a number of different terminology systems. The two main kinds of systems that have emerged are enumerative systems and combinatorial systems, although some systems have characteristics of both approaches. Differences in the structure and content of terminology systems, while useful at a local level, prevent effective wider communication, information sharing, integration of record systems, and comparison of nursing elements of healthcare information at a more global level. Formal nursing terminology systems present an alternative approach. This paper describes a number of recent initiatives and explains how these emerging approaches may help to augment existing nursing terminology systems and overcome their limitations through mediation. The development of formal nursing terminology systems is not an end in itself and there remains a great deal of work to be done before success can be claimed. This paper presents an overview of the key issues outstanding and provides recommendations for a way forward

Emergent Frameworks for Decision Support Systems

Knowledge is generated and accessed from heterogeneous spaces. The recent advances in in-formation technologies provide enhanced tools for improving the efficiency of knowledge-based decision support systems. The purpose of this paper is to present the frameworks for developing the optimal blend of technologies required in order to better the knowledge acquisition and reuse in large scale decision making environments. The authors present a case study in the field of clinical decision support systems based on emerging technologies. They consider the changes generated by the upraising social technologies and the challenges brought by the interactive knowledge building within vast online communities.Knowledge Acquisition, CDDSS, 2D Barcodes, Mobile Interface

Intelligent Systems for Sustainable Person-Centered Healthcare

This open access book establishes a dialog among the medical and intelligent system domains for igniting transition toward a sustainable and cost-effective healthcare. The Person-Centered Care (PCC) positions a person in the center of a healthcare system, instead of defining a patient as a set of diagnoses and treatment episodes. The PCC-based conceptual background triggers enhanced application of Artificial Intelligence, as it dissolves the limits of processing traditional medical data records, clinical tests and surveys. Enhanced knowledge for diagnosing, treatment and rehabilitation is captured and utilized by inclusion of data sources characterizing personal lifestyle, and health literacy, and it involves insights derived from smart ambience and wearables data, community networks, and the caregivers’ feedback. The book discusses intelligent systems and their applications for healthcare data analysis, decision making and process design tasks. The measurement systems and efficiency evaluation models analyze ability of intelligent healthcare system to monitor person health and improving quality of life

THE POWER OF REASONING: HOW STUDENT NURSES DEVELOP CONFIDENCE IN REASONING

Background Clinical Reasoning (CR) is the intellectual capacity to understand the value of patient data related to current knowledge, skills, and experiences within a dynamic domain of patient care with reflective analysis relating the new experience and understanding into new knowledge to be applied in future clinical situations. Poorly developed CR skills inhibit effective problem-solving abilities of nursing students producing levels of unexpected confusion and loss of confidence impeding their adaptability and effectiveness in dynamic healthcare environments. This study explored the effectiveness of human patient simulation (HPS) as an innovative method to facilitate the development of CR in undergraduate nursing students. Method A two-group crossover experimental design testing the hypothesis that Baccalaureate Student Nurses (BSN) experiencing patient simulations will have higher Health Sciences Reasoning Test (HSRT) scores as compared to students without these experiences. The 33 item HSRT is a multiple choice test using health science situational mini-case vignettes assessing the takers clinical reasoning capacity. Participants were randomly assigned to treatment groups that received HPS or case studies. Pre and posttest HSRT scores were measured to measure CR of each participant. Data analysis through the Grizzle Model included a mixed linear approach that included fixed effects of treatment, sequence, period, base score, and experience. Results The residual effect value was very large signifying the absence of carryover effect (p=0.840) indicating further analysis for treatment effects could continue. The best-fit final mixed linear model selected for analysis with the Grizzle Model produced insignificant treatment results with significant (p Conclusion There were no significant treatment effects of HPS on the acquisition of CR yet the outcome illuminated additional considerations to explore with further research adding to the understanding of this complex concept. Additional considerations for future research should include investigating an effective timetable for the development of CR through HPS and consider a more sensitive evaluation tool. New research designs should also consider increasing the realism and designing HPS through best practice methods while respecting the effect of academic, clinical, and external student stressors

Collaborative group reasoning in ward rounds: A critical realist case study

The thesis explored the group reasoning occurring between practitioners during hospital ward rounds. A model of the reasoning was constructed, focused on information gathering, sense-making and decision making. The model explained the role of group reasoning and generated suggestions for evaluating ward rounds, improving medical education and redesigning rounds

Clinical judgements : research and practice

This paper explores issues that are relevant to the judgements routinely made by clinical psychologists. It first considers the relative merits of clinical and statistical approaches to decision making and notes that although much of the empirical evidence demonstrates the greater accuracy of statistical approaches to making judgements (where appropriate methods exist), they are rarely routinely used. Instead, clinical approaches to making judgements continue to dominate in the majority of clinical settings. Second, common sources of errors in clinical judgement are reviewed, including the misuse of heuristics, clinician biases, the limitations of human information-processing capacities, and the overreliance on clinical interviews. Finally, some of the basic strategies that can be useful to clinicians in improving the accuracy of clinical judgement are described. These include advanced level training programs, using quality instruments and procedures, being wary of overreliance on theories, adhering to the scientist-practitioner approach, and being selective in the distribution of professional efforts and time.<br /

Emergent Frameworks for Decision Support Systems

Knowledge is generated and accessed from heterogeneous spaces. The recent advances in in-formation technologies provide enhanced tools for improving the efficiency of knowledge-based decision support systems. The purpose of this paper is to present the frameworks for developing the optimal blend of technologies required in order to better the knowledge acquisition and reuse in large scale decision making environments. The authors present a case study in the field of clinical decision support systems based on emerging technologies. They consider the changes generated by the upraising social technologies and the challenges brought by the interactive knowledge building within vast online communities