Inform: Conceptual modelling of intensive care information systems

Summary Intensive care of a patient requires heavy monitoring and versatile therapeutic actions. These produce a huge amount of patient information. A problem exists in managing this data and other information from all supporting activities creating a need for an automated information management system. To have a sound basis for future automated information systems in intensive care unit (ICU), a conceptual model is created to cover both the clinical and other activities of the ICU. The conceptual model consists of data flow diagrams and entity-relationship diagrams with underlying common data dictionary. A modern CASE tool is utilized to build the model. The work forms a part of AIM-INFORM project, which has a purpose to develop information management and decision support systems for high dependency environment.     

Developing a care program to better know the chronically critically ill

Patients requiring prolonged periods of intensive care and mechanical ventilation are termed chronically critically ill. These patients present a challenge to the healthcare team. In the fast-paced environment of the intensive care unit, their slow progress can be a source of frustration. At the University Hospital Geneva, a team, led by a clinical nurse specialist, addressed this problem by implementing a new care program with a goal to better know this patient population and improve their care. Values of emancipatory practice development guided the project, which utilized an action research methodology. Key assessment tools included a nursing focused patient history at admission and weekly nursing rounds, which allowed for periodic holistic assessment and care planning. New interventions focused on communication, physical care, and providing a context of understanding for the patient beyond hospitalisation, operationalised as a patient diary. The structure of the new program allowed the nurses to develop new skills and provided an environment for dynamic reflection. The care of this demanding patient population is beginning to be perceived by nurses as challenging and interesting.     

The impact of computers on patient care and research: the pentobarbital coma experience

Computer applications to patient care in an intensive care unit are examples the potential computers hold for health care, education, and research. The clinical application of a computer system to research and patient care in a selected research population, the pentobarbital coma study group, is described. The computer has been valuable in research for its data collecting and processing capabilities. It has also allowed the nursing staff to devote more time to patient care activities.     

Improving care by understanding the way we work: human factors and behavioural science in the context of intensive care

Effectiveness and efficiency of care of the critically ill patient are subject to a number of systemic influences, including skills of individual physicians/nurses (technical and non-technical), team-working in the intensive care unit (ICU), and the ICU environment. We first discuss the paper of Fackler and colleagues as a contribution to the systems approach to clinical performance in the context of intensive care. We then highlight features of care delivery that are unique to intensive care and discuss the need for better understanding of human and non-human elements of the system of care of the critically ill patient as a driver for improvement of care delivery.     

Patient-related data management

Patient-related data management (PDM) has become an increasingly important and time-consuming task in intensive care medicine. Currently, all data are usually collected in a poorly structured patient chart consisting of forms and pictures, with about 400 manual entries a day. To handle this amount of data, we have designed a three-level patient system: level 1, summarizing the whole patient; level 2, summarizing one organ system or one isolated problem; and level 3, variables describing morphology and function of organ systems. PDM must be adapted to different clinical situations. We observed three different scenarios: (1) Exploratory PDM, where the clinician learns about the patient and builds up an individual patient model in his or her mind. (2) Operational PDM, where in routine care clinicians are part of a feedback control system, in which they use the patient-related model. (3) Summary PDM, where a clinician summarizes all the information gathered during a period when he or she was responsible for the patient. Computing tools based on clinical thinking and adapted to different situations can ensure accurate, clear, and concise patient care communication among the members of the intensive care staff.     

INFORM: Development of information management and decision support systems for high dependency environments

The long-term aim in the INFORM Project is to develop, evaluate and implement a new generation of Information Systems for hospital High Dependency Environments (HDE — Intensive Care Units, Neonatal Units, Burns Units, Operating and Recovery Rooms, and other specialised areas). The distinguishing feature of the HDE is the very large amount of data that is collected through monitors and paper records about the state of critically ill patients; this has made the role of the staff a technical one in addition to a caring one. The INFORM System will integrate Decision Support with on-line, off-line and observed patient data and, in addition, will incorporate and integrate unit management features.In the Exploratory Phase of the Project, functional requirements have been set out. These are based on four components: conceptual model of the HDE; evaluation of existing HDE Information Systems; development of a novel software architecture using a Knowledge-Based Systems (KBS) methodology, and based on a critical review of KBS applied to the HDE; monitoring of appropriate leading-edge technological developments.The conceptual model has two components: a patient-related information model, and a department-related cost model. The patient-related model is identifying key and difficult areas of decision making. A key aspect of INFORM is integration of clinical Decision Support for these areas into the Information System through a layered software architecture. The lower layers are concerned with monitoring and alarming and the higher levels with patient assessment and therapy planning. The functionality and interconnection of these layers are being determined.     

Patient-related data management

Patient-related data management (PDM) has become an increasingly important and time-consuming task in intensive care medicine. Currently, all data are usually collected in a poorly structured patient chart consisting of forms and pictures, with about 400 manual entries a day. To handle this amount of data, we have designed a three-level patient system: level 1, summarizing the whole patient; level 2, summarizing one organ system or one isolated problem; and level 3, variables describing morphology and function of organ systems. PDM must be adapted to different clinical situations. We observed three different scenarios: (1) Exploratory PDM, where the clinician learns about the patient and builds up an individual patient model in his or her mind. (2) Operational PDM, where in routine care clinicians are part of a feedback control system, in which they use the patient-related model. (3) Summary PDM, where a clinician summarizes all the information gathered during a period when he or she was responsible for the patient. Computing tools based on clinical thinking and adapted to different situations can ensure accurate, clear, and concise patient care communication among the members of the intensive care staff.An address delivered on the occasion of the First Annual Meeting of the European Society for Computing in Anesthesia and Intensive Care, Goldegg, Austria, Oct 26, 1990.     

Maximizing a transport platform through computer technology

One of the most recent innovations coalescing computer technology and medical care is the further development of integrated medical component technology coupled with a computer subsystem. One such example is the self-contained patient transport system known as the Life Support for Trauma and Transport (LSTAT(tm)). The LSTAT creates a new transport platform that integrates the most current medical monitoring and therapeutic capabilities with computer processing capacity, creating the first "smart litter". The LSTAT is built around a computer system that is network capable and acts as the data hub for multiple medical devices and utilities, including data, power, and oxygen systems. The system logs patient and device data in a simultaneous, time-synchronized, continuous format, allowing electronic transmission, storage, and electronic documentation. The third-generation LSTAT includes an oxygen system, ventilator, clinical point-of-care blood analyzer, suction, defibrillator, infusion pump, and physiologic monitor, as well as on-board power and oxygen systems. The developers of LSTAT and other developers have the ability to further expand integrative component technology by developing and integrating clinical decision support systems.     

Neonatal physiological trend monitoring by computer

A premature baby born up to four months early is a fragile patient dependent on intensive care. The body systems are physiologically immature and so tolerate stress badly. The tendency of these infants to rapidly deteriorate, has led us to use a cotside computer monitoring system which displays physiological trends. Information from standard neonatal monitors is accessed by individual cotside PC's linked to a central network server and Doctors terminal. Trend graphs can be easily manipulated, displaying from 7 minutes to 3 days of physiological information on a single screen. Pathology may be observed in real time as it occurs. The system has 3 main areas of use, (1) as a real time clinical aid to patient management, e.g. apnoea of the newborn; (b) as a research tool, demonstrating the effects of procedures on physiology; (c) for educating members of staff about how physiological events develop. Data is saved for the whole of each neonates intensive care stay. Assessment of staff and parent attitudes by questionnaire have been favourable.     

Comparison of PathVysion and INFORM fluorescence in situ hybridization kits for assessment of HER-2/neu status in breast carcinoma.

BACKGROUND: Fluorescence in situ hybridization is advocated for precise assessment of HER-2/neu status in breast carcinoma; however, few objective data compare available kits for clinical laboratories contemplating development of the test. METHODS AND RESULTS: Thirty breast carcinomas were analyzed for HER-2/neu amplification with the PathVysion kit (Vysis, Downers Grove, IL) and INFORM kit (Ventana Medical Systems, Tucson, AZ). Each kit was evaluated for morphology, background staining, technical and interpretation time, and cost. PathVysion detected amplification in seven of 30 cases (23.3%); INFORM detected six of 30 cases (20%). A greater percentage of PathVysion cases showed good morphology and lower background staining than INFORM. Technical and interpretation times, as well as cost, were less with PathVysion than INFORM. CONCLUSION: PathVysion is superior to INFORM because it produces better morphology and less background staining and is faster and less expensive than the INFORM kit. It also includes a chromosome 17 probe that serves as an internal control and enables correction for chromosome 17 aneuploidy.     

Computerizing medical records: software criteria for systems to document patient encounters

It is difficult to design and build computer systems to document medical care, especially if the entries are to be made by health care professionals. Not all software approaches are equally well suited to the task. Twenty-one specific software characteristics were identified that promote efficient development and support clinical needs. Using a software tool that satisfied these characteristics, we developed a computerized medical chart system that physicians can use to write notes and document patient encounters. The success of this system was due to a good fit between the basic capabilities of the software approach and the requirements of the project. These criteria can serve as the starting point for evaluating or developing other software applications that depend on physician input of clinical information.     

Patient satisfaction with nursing care: a concept analysis within a nursing framework

Title.  Patient satisfaction with nursing care: a concept analysis within a nursing framework.
Background.  Patient satisfaction is an important indicator of quality of care, and healthcare facilities are interested in maintaining high levels of satisfaction in order to stay competitive in the healthcare market. Nursing care has a prominent role in patient satisfaction. Using a nursing model to measure patient satisfaction with nursing care helps define and clarify this concept.
Data sources.  Rodgers' evolutionary method of concept analysis provided the framework for this analysis. Data were retrieved from the Cumulative Index of Nursing and Allied Health Literature and MEDLINE databases and the ABI/INFORM global business database. The literature search used the keywords patient satisfaction, nursing care and hospital. The sample included 44 papers published in English, between 1998 and 2007.
Results.  Cox's Interaction Model of Client Health Behavior was used to analyse the concept of patient satisfaction with nursing care. The attributes leading to the health outcome of patient satisfaction with nursing care were categorized as affective support, health information, decisional control and professional/technical competencies. Antecedents embodied the uniqueness of the patient in terms of demographic data, social influence, previous healthcare experiences, environmental resources, intrinsic motivation, cognitive appraisal and affective response. Consequences of achieving patient satisfaction with nursing care included greater market share of healthcare finances, compliance with healthcare regimens and better health outcomes.
Conclusion.  The meaning of patient satisfaction continues to evolve. Using a nursing model to measure patient satisfaction with nursing care delineates the concept from other measures of patient satisfaction.     

An automatic data acquisition system for ventilator patients

Computerized patient charting and trended data acquisition are becoming important elements of respiratory and intensive care. Continuous, remote monitoring of a patient's respiratory functions is now accessible with automated data acquisition systems. The system described in this article features real-time data collection from up to eight ventilators, automated patient charting, graphic trending, and configurable modes for viewing graphic trends. These features provide practitioners with continuous graphic presentations of ventilator data, which allows for better recording and understanding of each patient's respiratory progress.     

Monitoring and management of acute circulatory problems: the expanded role of the physiologically oriented critical care nurse.

The intensive care unit is set apart from other hospital patient care areas by (1) physiological instrumentation that permits better assessment and more effective therapy and (2) more intensive nursing. These capabilities allow nurse and physician intensivists to evaluate tissue perfusion and tissue oxygenation by the temporal patterns of oxygen delivery and oxygen consumption, as well as hemodynamics. Such evaluation provides important insight into the functional impairment of hemorrhagic, traumatic, septic, and postoperative shock. Using artificial intelligence-based systems, complex clinical algorithms--tailored to specific patient conditions--have been developed and are described. These algorithms are based on both invasive and noninvasive monitoring systems and on clinical experience with a large series of high-risk surgical patients.     

A strategy for development of computerized critical care decision support systems

It is not enough to merely manage medical information. It is difficult to justify the cost of hospital information systems (HIS) or intensive care unit (ICU) patient data management systems (PDMS) on this basis alone. The real benefit of an integrated HIS or PDMS is in decision support. Although there are a variety of HIS and ICU PDMS systems available there are few that provide ICU decision support. The HELP system at the LDS Hospital is an example of a HIS which provides decision support on many different levels. In the ICU there are decision support tools for antibiotic therapy, nutritional management, and management of mechanical ventilation. Computer protocols for the management of mechanical ventilation (respiratory evaluation, ventilation, oxygenation, weaning and extubation) in patients with adult respiratory distress syndrome ((ARDS) have already been developed and clinically validated at the LDS Hospital. These protocols utilize the bedside intensive care unit (ICU) computer terminal to prompt the clinical care team with therapeutic and diagnostic suggestions. The protocols (in paper flow diagram and computerized form) have been used for over 40,000 hours in more than 125 adult respiratory distress syndrome (ARDS) patients. The protocols controlled care for 94% of the time. The remainder of the time patient care was not protocol controlled was a result of the patient being in states not covered by current protocollogic (e.g. hemodynamic instability, or transport for X-Ray studies). 52 of these ARDS patients met extra corporal membrane oxygenation (ECMO) criteria. The survival of the ECMO criteria ARDS patients was 41%, four times that expected (9%) from historical data (p<0.0002). The success of these computer protocols and their acceptance by the clinical staff clearly establishes the feasibility of controlling the therapy of severely ill patients.Over the last four years we have refined the process which we use for generating computerized protocols. The purpose of this paper is to present the six step development strategy which we are successfully using to produce computerized critical care protocols.     

Factors affecting the use of nursing information systems in Taiwan

AIM: This paper reports a study to test a proposed model of factors (demographic variables, computer experience and perceived technology characteristics) influencing the efficient use of a computerized nursing care planning system by hospital clinical nurses. BACKGROUND: Although nursing information systems have been used in health care institutions, little research has explored the efficiency of computer use in nurses' daily practice. METHOD: A secondary data analysis was applied to focus on clinical nurses' daily computer use. The original data were collected from a medical centre in Taiwan to establish the reliability and validity of a scale to evaluate computerized nursing care plan systems. RESULTS: Younger nurses with more education, less computer knowledge and less usage pressure, and who perceived that they had less usage benefit, more education training and usability regarding system use, spent less time on the computerized nursing care plan. CONCLUSION: The results can be used for further organization of education programmes and as a reference for training strategies. Further examination and analysis of item content are suggested.     

The benefits and challenges of the computerized electronic medical record.

Data from aggregate individual patient records can be gathered to answer many clinical and nursing research questions about quality assurance and resource allocation, assisting in the measurement and evaluation of patient care outcomes. The use of standardized nursing language, large integrated computer databases, and information management processes provide for the use of patient-specific data and information to facilitate patient care. The use of aggregated data can also facilitate the comparison of nursing practice across populations, demonstrate and project nursing care trends, serve as a financial and legal record, aid in clinical research, support decision analysis, and guide professional and organization performance improvement.     

Computers in the ICU: panacea or plague?

The introduction of the intensive care unit (ICU) in the 1960s with its demands for management of large volumes of patient data drove the initial introduction of computers into the ICU. Since the mid-1960s computer systems for the ICU have evolved into the highly sophisticated bedside workstations commercially available today. Despite all of the technologic advances in computers, their application in ICUs in the United States continues to spread very slowly. One of the largest problems is justifying the cost of systems primarily designed to automate data charting and generation of care plans. Although the existing commercial systems do an excellent job, few conclusive studies prove that these systems have a favorable cost-to-benefit ratio. Research systems have demonstrated that if one extends these systems to incorporate a fully integrated database, decision-support tools, automation of data acquisition, and more sophisticated display and user-interface technology, then these ICU computer systems can have a significant impact on improving the quality and reducing the costs of patient care. For computers to be embraced in the ICU environment, commercial systems of the future must move beyond merely gathering and displaying information. They must help the clinician at the bedside assimilate the vast array of ICU data and help him to make more effective decisions.