Customer-centered careflow modeling based on guidelines.
ABSTRACT In contemporary society, customer-centered health care, which stresses customer participation and long-term tailored care, is inevitably becoming a trend. Compared with the hospital or physician-centered healthcare process, the customer-centered healthcare process requires more knowledge and modeling such a process is extremely complex. Thus, building a care process model for a special customer is cost prohibitive. In addition, during the execution of a care process model, the information system should have flexibility to modify the model so that it adapts to changes in the healthcare process. Therefore, supporting the process in a flexible, cost-effective way is a key challenge for information technology. To meet this challenge, first, we analyze various kinds of knowledge used in process modeling, illustrate their characteristics, and detail their roles and effects in careflow modeling. Secondly, we propose a methodology to manage a lifecycle of the healthcare process modeling, with which models could be built gradually with convenience and efficiency. In this lifecycle, different levels of process models are established based on the kinds of knowledge involved, and the diffusion strategy of these process models is designed. Thirdly, architecture and prototype of the system supporting the process modeling and its lifecycle are given. This careflow system also considers the compatibility of legacy systems and authority problems. Finally, an example is provided to demonstrate implementation of the careflow system.
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ABSTRACT: Medical knowledge management and care process management have become to be considered as valuable strategic assets that can lead to sustained increase in Health Care Organization (HCO) performance. Thus, it is essential to investigate which are the enablers for promoting knowledge-based organizations (people, organization, process, and system perspectives). Although they are essential for a HCO to manage knowledge effectively, it is still unclear how to employ them in more principled fashion. This requires innovative management strategies to determine effective ways of utilizing knowledge resources and capabilities available both within and outside the organization. This paper reviews knowledge and process management theories, methods, and technologies that are potentially effective in building high performance HCOs. They come from a variety of fields behind computer science and medical informatics, e.g. from business and organization sciences to psychological and cognitive sciences, from epistemology to sociology. However, the success in developing future Health Information Systems (HIS) requires their incorporation into a new conceptual framework after recognizing how peculiar are the characteristics of HCOs with respect to other organizations. Investigating the nature of knowledge, in general, and of medical knowledge, in particular, is essential to define which services the future HIS should provide to foster collaboration between patients and health professionals. The knowledge creation process is then described in order to emphasize its dynamic and social characteristics. The potential of workflow technology for building innovative HISs is analyzed together with several basic research issues which are very challenging for researchers in the field. A framework for augmenting the conceptual analysis of theories, methods, tools and effects of knowledge management in building high performance HCOs.Methods of Information in Medicine 02/2004; 43(5):525-35. · 1.60 Impact Factor
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ABSTRACT: An inside look at the components of patient-focused care, an outline of attainable benefits, and the managerial practices affected by this model are discussed. This method of delivery assumes a complete redesign of traditional hospital organization and strives to increase interdisciplinary collaboration, to improve patient care, and to decentralize services.Nursing Management (Springhouse) 03/1994; 25(2):34-6.
- Journal of the Royal Society of Medicine 02/2001; 94(1):6-9. · 1.72 Impact Factor