We recommend the following structure: (1) Addressing the patient by saying "hello"; (2) presentation of information related to case history, acute status (findings and strategy) (including the function of the main organ systems), infection status, and nursing problems; (3) patient-related discussion; and (4) discussion of general treatment rules, triggered by individual patient condition.
Computerized record keeping promises complete, accurate and legible documentation. Reliable measurements are a prerequisite to fulfill these expectations. We analyzed the physiological variables provided by bedside monitoring devices in 657 bedside visits performed by an experienced Intensive Care nurse during 75 Intensive Care rounds. We registered which variables were displayed. If a variable was displayed, we assessed whether it could be used for documentation or should be rejected. If a value was rejected the reason was registered as: the measurement was not intended (superfluous display), the current clinical situation did not allow proper measurement, or other reasons. Basic variables (vital signs and respiration related variables) were displayed in more then 90%, specific variables (e.g. intracranial pressure) were displayed in less than 50% of the situations. Displayed variables were superfluous on an average of 11% because measurement was not intended. Variables like heart rate, temperature, airway pressure, minute volume of ventilation, arrhythmia, pulmonary arterial pressure, non-invasive blood pressure, and intracranial pressure provide high quality measured values (acceptance of more than 90%). Invasive arterial pressure, central venous pressure, respiration rate and oxygen saturation (via pulse oximetry) provided lower quality values with a rejection rate higher than 10%. Inappropriate sensor technology to match the clinical environment seems to be the root cause. In future the request for automatic documentation will increase. In order to avoid additional staff workload and to ensure reliable documentation, sensor technology especially related to respiration rate, blood pressure measurements, and pulse oximetry should be improved.
For almost 100 years, the anaesthesia record has been the sole information tool trying to fulfill an ample catalogue of functions related to the anaesthesia information processes. Automated anaesthetic record systems have evolved around data being available online, as an imitation of the handwritten record. None has developed an information tool capable of an efficient utilization of the wide range of resources provided by modern technology to fulfill the information requirements of the anaesthetic environment. We used a system ergonomic analysis trying to find the best solutions. As a result of it we drafted an Anaesthesia Information Concept (AIC) in which the complexity of data & information (D&I) processes is broken down to modules called Clinical Information Process Units (CIPUs). A CIPU is mainly defined by the responsibility of a staff member and focuses on the basic system patient, staff and machine (all devices). The internal functions of a CIPU are treatment control and medicolegal documentation. The external functions are fulfilled by transferring required sets of D&I for subsequent treatment control (next CIPU), audit, quality control, cost calculation, etc. Using such an approach, an Anaesthesia Information Concept (AIC) can be realized by a wide range of modular and hybrid systems (combination of different tools such as paper records, computers, etc), as opposed to universal and single automated documentation systems, which up to now have failed to fulfill the information demands of the anaesthetic environment.
The project LUCY (Linked Ulm Care sYstem) is described. The goal of this project was to build a research workstation in an Intensive Care Unit which enables evaluation of data/information processing and presentation concepts. Also evaluation of new devices and functions considering not only one device but the workplace as an entirety was an aim of the project. We describe the complete process of building from the stage of design until its testing in clinical routine. LUCY includes a patient monitor, a ventilator, 4 infusion pumps and 8 syringe pumps. All devices are connected to a preprocessing computer via serial interfaces. A high performance graphic workstation is used for central display of physiological and therapeutic variables. A versatile user interface provides touch screen, keyboard and mouse interaction. For fluid administration a bar code based control and documentation facility was included. While our scheduled development efforts were below 4 man-years, the overall man-power needed until the first routine test amounts to 8 man-years. Costs of devices and software sum up to 160,000 US$. First experiences in clinical routine show good general acceptance of the workplace concept. Analysing the recorded data we found 90% of the items to be redundant: individual filtering algorithms are necessary for each of nowaday's devices. The flexibility of the system concerning the implementation of new features is far from our expectations. Technical maintenance of the system during clinical operation requires continuous effort which we cannot afford in the current situation.
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)
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