A maturity model for care pathways

Over the last recent decades, increasing the quality of healthcare services while reducing costs has been among the top concerns in the healthcare landscape. Several healthcare institutions have initiated improvement programs and invested considerably in process orientation and management. Care pathways are receiving increasing attention from clinicians, healthcare managers, and academics, as a way to standardize healthcare processes to improve the safety, quality, and efficiency of healthcare services. Despite considerable literature on the definition of care pathways, to date there is no agreement on their key process characteristics and the way they traverse from an immature to a mature state. Such a model would guide healthcare institutions to assess pathways’ level of maturity and generate a roadmap for improving towards higher levels. In this paper, we propose a maturity model for care pathways that is constructed taking a generic business process maturity model as a basis. The model was refined through a Delphi study with nine domain experts to address healthcare domain specific concerns. To evaluate its validity, we applied it in assessing the maturity of a particular care pathway taking place in 11 healthcare institutions. The results indicate the usefulness of the proposed model in assessing pathway’s maturity and its potential to provide guidance for its improvement

A review of information flow diagrammatic models for product-service systems

A product-service system (PSS) is a combination of products and services to create value for both customers and manufacturers. Modelling a PSS based on function orientation offers a useful way to distinguish system inputs and outputs with regards to how data are consumed and information is used, i.e. information flow. This article presents a review of diagrammatic information flow tools, which are designed to describe a system through its functions. The origin, concept and applications of these tools are investigated, followed by an analysis of information flow modelling with regards to key PSS properties. A case study of selection laser melting technology implemented as PSS will then be used to show the application of information flow modelling for PSS design. A discussion based on the usefulness of the tools in modelling the key elements of PSS and possible future research directions are also presented

Process Mining for Six Sigma

Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges the potential benefits of using process mining techniques in Six Sigma-based process improvement initiatives. However, a guideline that is explicitly dedicated on how process mining can be systematically used in Six Sigma initiatives is lacking. To address this gap, the Process Mining for Six Sigma (PMSS) guideline has been developed to support organizations in systematically using process mining techniques aligned with the DMAIC (Define-Measure-Analyze-Improve-Control) model of Six Sigma. Following a design science research methodology, PMSS and its tool support have been developed iteratively in close collaboration with experts in Six Sigma and process mining, and evaluated by means of focus groups, demonstrations and interviews with industry experts. The results of the evaluations indicate that PMSS is useful as a guideline to support Six Sigma-based process improvement activities. It offers a structured guideline for practitioners by extending the DMAIC-based standard operating procedure. PMSS can help increasing the efficiency and effectiveness of Six Sigma-based process improving efforts. This work extends the body of knowledge in the fields of process mining and Six Sigma, and helps closing the gap between them. Hence, it contributes to the broad field of quality management

Development Of A Fisheye-Based Information Search Processing Aid (FISPA) For Managing Information Overload In The Web Environment

Information technologies have proliferated at an unprecedented rate to provide access to information across geographical boundaries. However, this proliferation has led to an information overload. Information overload has adverse impacts on information use and decision quality. This research focuses on the overload problem resulting from a web search, and proposes a potential remedy. We develop the requirements of a system that makes use of clustering and visualization for browsing the results of a typical web search. Based on this model, we develop a prototype that visualizes search results by first organizing them into a hierarchy according to their individual contents. This system presents a visual overview of the groups in this hierarchy, and lets the users focus (zoom) on specific groups of interest. One general problem with zooming within hierarchical structures is the separation between the details and the context. To address this problem, we implement a fisheye zooming capability in our system. This paper describes a typology of the various components necessary for addressing the problem, and then the proposed solution based upon a fisheye view-based visualization. Next, the specific visualization algorithm and the system implementation are described. We conclude with research questions for further development of such interfaces for presentation of the results from web searches

Location Analytics and Decision Support: Reflections on Recent Avancementa, a Research Framework and the Path Ahead

The expansion in analytics and big data over the past decade has included a rapid growth in locational analytics, spatial analysis, and geographic information systems and science. Although research in Decision Support Systems (DSS) has typically tackled spatial decision problems through connections to geographic information systems (GISs), recent research has focused on the benefits from combining the two bodies of knowledge and research streams in addressing important challenges in delivering quality decisions in settings with locational/ spatial components. Consequently, research in spatial decision support now seeks to take advantage of the advances in analytics, big data and cloud based decision support. This work incorporates spatiotemporal big data, mobile location-based services, 3-D, location in the sharing economy, space-time, and location-based social media. The goal of this special issue is to present explorations and knowledge enhancement on the cutting edges of decision making involving location and place. The work presented includes new problem areas, data sources, methodologies, and applications in today\u27s more complex and data-rich decision-making environments. To provide a context for the ideas and findings in the special issue articles, this editorial reviews and extracts broad themes and categorizations from a selection of over two dozen past articles published in DSS that combine location analytics (LA), non-location analytics (NLA), and decision support (DS).We then propose a generic framework for LA/NLA/DS research, briefly summarize the eight articles in the special issue, and then outline the directions the field of location analytics and decision support is moving towards. Finally we discuss what gaps in the LA/NLA/DS research landscape need to be addressed by future research