Normative modeling for personalized clinical pathway using organizational semiotics methods

Clinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and reduce the length and cost of hospital stay. However, nowadays most of them are static and nonpersonalized. Our objective is to capture and represent clinical pathway using organizational semiotics method including Semantic Analysis which determines semantic units in clinical pathway, their relationship and their patterns of behavior, and Norm Analysis which extracts and specifies the norms that establish how and when these medical behaviors will occur. Finally, we propose a method to develop clinical pathway ontology based on the results of Semantic Analysis and Norm analysis. This approach will give a contribution to design personalized clinical pathway by defining a set of possible patterns of behavior and theClinical pathways are widely adopted by many large hospitals around the world in order to provide high-quality patient treatment and reduce the length and cost of hospital stay. However, nowadays most of them are static and nonpersonalized. Our objective is to capture and represent clinical pathway using organizational semiotics method including Semantic Analysis which determines semantic units in clinical pathway, their relationship and their patterns of behavior, and Norm Analysis which extracts and specifies the norms that establish how and when these medical behaviors will occur. Finally, we propose a method to develop clinical pathway ontology based on the results of Semantic Analysis and Norm analysis. This approach will give a contribution to design personalized clinical pathway by defining a set of possible patterns of behavior and the norms that govern the behavior based on patient’s condition.

Knowledge-based clinical pathway for medical quality improvement

Clinical pathways have been adopted for various diseases in clinical departments for quality improvement as a result of standardization of medical activities in treatment process. Using knowledge-based decision support on the basis of clinical pathways is a promising strategy to improve medical quality effectively. However, the clinical pathway knowledge has not been fully integrated into treatment process and thus cannot provide comprehensive support to the actual work practice. Therefore this paper proposes a knowledgebased clinical pathway management method which contributes to make use of clinical knowledge to support and optimize medical practice. We have developed a knowledgebased clinical pathway management system to demonstrate how the clinical pathway knowledge comprehensively supports the treatment process. The experiences from the use of this system show that the treatment quality can be effectively improved by the extracted and classified clinical pathway knowledge, seamless integration of patient-specific clinical pathway recommendations with medical tasks and the evaluating pathway deviations for optimization.

Integrated clinical pathway management for medical quality improvement-based on a semiotically inspired systems architecture

Clinical pathway is an approach to standardise care processes to support the implementations of clinical guidelines and protocols. It is designed to support the management of treatment processes including clinical and non-clinical activities, resources and also financial aspects. It provides detailed guidance for each stage in the management of a patient with the aim of improving the continuity and coordination of care across different disciplines and sectors. However, in the practical treatment process, the lack of knowledge sharing and information accuracy of paper-based clinical pathways burden health-care staff with a large amount of paper work. This will often result in medical errors, inefficient treatment process and thus poor quality medical services. This paper first presents a theoretical underpinning and a co-design research methodology for integrated pathway management by drawing input from organisational semiotics. An approach to integrated clinical pathway management is then proposed, which aims to embed pathway knowledge into treatment processes and existing hospital information systems. The capability of this approach has been demonstrated through the case study in one of the largest hospitals in China. The outcome reveals that medical quality can be improved significantly by the classified clinical pathway knowledge and seamless integration with hospital information systems.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

Flavonoids inhibit the platelet TxA(2) signalling pathway and antagonize TxA(2) receptors (TP) in platelets and smooth muscle cells

What is already known about this subject center dot Flavonoids are largely recognized as potential inhibitors of platelet function, through nonspecific mechanisms such as antioxidant activity and/or inhibition of several enzymes and signalling proteins. center dot In addition, we, and few others, have shown that certain antiaggregant flavonoids may behave as specific TXA2 receptor (TP) ligands in platelets. center dot Whether flavonoids interact with TP isoforms in other cell types is not known, and direct evidence that flavonoid-TP interaction inhibits signalling downstream TP has not been shown. What this study adds center dot This study first demonstrates that certain flavonoids behave as ligands for both TP isoforms, not only in platelets, but also in human myometrium and in TP-transfected HEK 293T cells. center dot Differences in the effect of certain flavonoids in platelet signalling, induced by either U46619 or thrombin, suggest that abrogation of downstream TP signalling is related to their specific blockage of the TP, rather than to a nonspecific effect on tyrosine kinases or other signalling proteins. Flavonoids may affect platelet function by several mechanisms, including antagonism of TxA(2) receptors (TP). These TP are present in many tissues and modulate different signalling cascades. We explored whether flavonoids affect platelet TP signalling, and if they bind to TP expressed in other cell types. Platelets were treated with flavonoids, or other selected inhibitors, and then stimulated with U46619. Similar assays were performed in aspirinized platelets activated with thrombin. Effects on calcium release were analysed by fluorometry and changes in whole protein tyrosine phosphorylation and activation of ERK 1/2 by Western blot analysis. The binding of flavonoids to TP in platelets, human myometrium and TP alpha- and TP beta-transfected HEK 293T cells was explored using binding assays and the TP antagonist H-3-SQ29548. Apigenin, genistein, luteolin and quercetin impaired U46619-induced calcium mobilization in a concentration-dependent manner (IC50 10-30 mu M). These flavonoids caused a significant impairment of U46619-induced platelet tyrosine phosphorylation and of ERK 1/2 activation. By contrast, in aspirin-treated platelets all these flavonoids, except quercetin, displayed minor effects on thrombin-induced calcium mobilization, ERK 1/2 and total tyrosine phosphorylation. Finally, apigenin, genistein and luteolin inhibited by > 50% H-3-SQ29548 binding to different cell types. These data further suggest that flavonoids may inhibit platelet function by binding to TP and by subsequent abrogation of downstream signalling. Binding of these compounds to TP occurs in human myometrium and in TP-transfected HEK 293T cells and suggests that antagonism of TP might mediate the effects of flavonoids in different tissues.

Variation in the ability of human influenza A viruses to induce and inhibit the IFN-beta pathway

We investigated the ability of a selection of human influenza A viruses, including recent clinical isolates, to induce IFN-beta production in cultured cell lines. In contrast to the well-characterized laboratory strain A/PR/8/34, several, but not all, recent isolates of H3N2 viruses resulted in moderate IFN-beta stimulation. Through the generation of recombinant viruses, we were able to show that this is not due to a loss of the ability of the NS1 genes to suppress IFN-beta induction; indeed, the NS1 genes behaved similarly with respect to their abilities to block dsRNA signaling. Interestingly, replication of A/Sydney/5/97 virus was less Susceptible to pre-treatment with IFN-alpha than the other viruses. In contrast to the universal effect on dsRNA signaling, we noted differences in the effect of NS1 proteins on expression of interferon stimulated genes and also genes induced by a distinct pathway. The majority of NS1 proteins blocked expression From both IFN-dependent and TNF-dependent promoters by an apparent post-transcriptional mechanism. The NS1 gene of A/PR/8/34 NS1 did not confer these blocks. We noted striking differences in the Cellular localization of different influenza A virus NS1 proteins during infection, which might explain differences in biological activity. (C) 2005 Elsevier Inc. All rights reserved.

A novel Bayesian approach to drug design with simple and complex enzymes: Use with lens aldehyde dehydrogenase and the glyoxalase pathway

Purpose: Acquiring details of kinetic parameters of enzymes is crucial to biochemical understanding, drug development, and clinical diagnosis in ocular diseases. The correct design of an experiment is critical to collecting data suitable for analysis, modelling and deriving the correct information. As classical design methods are not targeted to the more complex kinetics being frequently studied, attention is needed to estimate parameters of such models with low variance. Methods: We have developed Bayesian utility functions to minimise kinetic parameter variance involving differentiation of model expressions and matrix inversion. These have been applied to the simple kinetics of the enzymes in the glyoxalase pathway (of importance in posttranslational modification of proteins in cataract), and the complex kinetics of lens aldehyde dehydrogenase (also of relevance to cataract). Results: Our successful application of Bayesian statistics has allowed us to identify a set of rules for designing optimum kinetic experiments iteratively. Most importantly, the distribution of points in the range is critical; it is not simply a matter of even or multiple increases. At least 60 % must be below the KM (or plural if more than one dissociation constant) and 40% above. This choice halves the variance found using a simple even spread across the range.With both the glyoxalase system and lens aldehyde dehydrogenase we have significantly improved the variance of kinetic parameter estimation while reducing the number and costs of experiments. Conclusions: We have developed an optimal and iterative method for selecting features of design such as substrate range, number of measurements and choice of intermediate points. Our novel approach minimises parameter error and costs, and maximises experimental efficiency. It is applicable to many areas of ocular drug design, including receptor-ligand binding and immunoglobulin binding, and should be an important tool in ocular drug discovery.