Decision making in high dependency environments — can we learn from modern industrial management models?
| Autor: | S. Konichezky, S. Schraag, W. Friesdorf, F. Groß-Alltag, M. Nathe, D. Geva |
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| Rok vydání: | 1994 |
| Předmět: |
Operations Research
Medical knowledge Systems Analysis Knowledge management Computer science Decision Making Medicine (miscellaneous) Critical Care and Intensive Care Medicine computer.software_genre Patient Care Planning Decision Support Techniques Task (project management) Industrial management Medical Laboratory Science Humans Industry Cybernetics Problem Solving Monitoring Physiologic Probability business.industry Models Theoretical Expert system Patient management Equipment and Supplies Risk analysis (engineering) Management methods business computer Total Quality Management Dependency (project management) |
| Zdroj: | International Journal of Clinical Monitoring and Computing. 11:11-17 |
| ISSN: | 0167-9945 |
| DOI: | 10.1007/bf01132839 |
| Popis: | Increasing complexity and increased restraints affect the task of patient management in High Dependency Environments, which has become intricate and difficult. Medical knowledge alone is not enough any longer for proper patient care. Management ability and facilities are required. Current medical knowledge should be expanded by management methods and techniques. By looking at management models in the industry, we found striking similarities between the industrial management situation and clinical patient management. Both systems share complexity in structure, complexity in interaction and evolutionary character. Clinical patient management can be compared with a navigation process. The patient is steered by a control system, and course information is given by control dimensions. Clinical patient management becomes a succession of steering activities influenced by the surrounding systems. This system can be structured in three interacting layers: an operational level, in which information is collected and actions executed; a strategic level in which strategies based on goal-oriented mental anticipation of a probabilistic system are formulated; and a normative level at which principles and norms are defined. It is possible then, to define the tools which have to be developed and implemented to improve clinical management capabilities. At the operational level these tools are addressed to improve clinical decision making by providing information in an ergonomical way. They include artifact elimination, data reduction, increase in meaningful information and unwanted data filtering. At the strategic level, tools to check the feasibility of the applied strategies have to be developed, such as: ideal patient course plots and increased training in strategic thinking.(ABSTRACT TRUNCATED AT 250 WORDS) |
| Databáze: | OpenAIRE |
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