Assessing the information environment in intensive care units

This paper describes the development and application of a methodology for evaluating how physicians and nurses view the usefulness of various sources of patient information available within a hospital intensive care unit (ICU). The methodology encompasses semi-structured interviews, task analysis, a simulated case study of a critically ill patient, verbal protocol analysis, questionnaire responses based on both past experiences in the ICU and performance on the simulated task, and a post-task interview. Eleven nurses and six physicians participated in the study. Analysis of the questionnaires revealed significant differences in the rankings of the information sources by both the nurses and the physicians on each of seven evaluation criteria. Significant differences were also found among both the physicians and the nurses in rankings of the relative importance of the individual information sources for meeting task requirements. A framework for describing information gathering applicable to critical care environments was proposed as a means for better understanding how information sources are used. Overall, the methodology was found to be useful in terms of providing valuable data regarding the utility and usability of information sources. The importance of using a systematic approach for assessing the usefulness of information sources, particularly from the perspectives of performing design interventions and predicting the effectiveness of new information technologies, as well as the limitations in adopting this type of approach, are also discussed.     

Cerebral blood-flow monitor for use in neonatal intensive care units

The implementation of a real-time multichannel system for monitoring cerebral blood-flow is described. The instrument relies on a completely modular architecture and is based on the principle of measuring the electrical impedance between a number of periodically sensed electrode pairs positioned around the subject's head. The whole setup is controlled by a host computer that performs several functions, such as real-time acquisition, analysis, display and data logging. Two operating options can be chosen by the user: a normal mode that allows continuous monitoring and a triggered mode in which the measurement cycle is automatically started by the occurrence of a preset condition in some other circulatory signal, e.g. the permanently available ECG signal. The design is considerably user-friendly and embodies a number of special safety precautions to take account of the peculiar condition of patients, usually newborn infants hospitalized in intensive care units.     

The evaluation of an information system for intensive care

This paper describes the application of humancomputer interaction (HCI) research methods in critical care medicine. An evaluation of an information system for the support of cardiological intensive care (The Aachen Information System for Intensive Care- AISIC) is outlined. AISIC supports the capturing of diagnostic and therapeutic patient data by nursing staff, the requesting of external diagnostic reports, and the retrieval of information for treatment planning performed by physicians (Popp 1994). It was hypothesized that use of the information system would result in quicker task completion times and a reduction in error-making, when compared to the existing paper-based record-keeping system. The evaluation was carried out using eight different forms of data capture, ranging from interview and questionnaire to automatic keystroke logging. The results of the evaluation revealed problems in the prescribing and recording of medication dosage and administration. The resultant redesign of the medication option is discussed, along with implications for improved patient care through the cognitive engineering of medical information systems. The problems encountered in conducting this type of work in a critical care environment are also discussed.     

Assessing the multi-resolution information content of remotely sensed variables and elevation for evapotranspiration in a tall-grass prairie environment

Understanding the spatial scaling behavior of evapotranspiration and its relation to controlling factors on the land surface is necessary to accurately estimate regional water cycling. We propose a method for ascertaining this scaling behavior via a combination of wavelet multi-resolution analysis and information theory metrics. Using a physically-based modeling framework, we are able to compute spatially distributed latent heat fluxes over the tall-grass prairie in North-central Kansas for August 8, 2005. Comparison with three eddy-covariance stations and a large aperture scintillometer demonstrates good agreement, and thus give confidence in the modeled fluxes. Results indicate that the spatial variability in radiometric temperature (a proxy for soil moisture) most closely controls the spatial variability in evapotranspiration. Small scale variability in the water flux can be ascribed to the small scale spatial variance in the fractional vegetation. In addition, correlation analysis indicates general scale invariance and that low spatial resolution data may be adequate for accurately determining water cycling in prairie ecosystems.     

An architecture for online comparison and validation of processing methods and computerized guidelines in intensive care units

Clinical decision support systems are a combination of software techniques to help the clinicians in their medical decision making process via functionalities ranging from basic signal analysis to therapeutic planning and computerized guidelines. The algorithms providing all these functionalities must be very carefully validated on real patient data and must be confronted to everyday clinical practice. One of the main problems when developing these techniques is the difficulty to obtain high-quality complete patient records, comprising data coming both from the biomedical equipment (high-frequency signals), and from numerous other sources (therapeutics, imagery, clinical actions, etc.). In this paper, we present an infrastructure for developing and testing such software algorithms. It is based on a bedside workstation where testing different algorithms simultaneously on real-time data is possible in the ward. It is completed by a collaborative portal enabling different teams to test their software algorithms on the same patient records, making comparisons and cross-validations more easily.     

Development of a clinical data warehouse from an intensive care clinical information system

There are relatively few institutions that have developed clinical data warehouses, containing patient data from the point of care. Because of the various care practices, data types and definitions, and the perceived incompleteness of clinical information systems, the development of a clinical data warehouse is a challenge.In order to deal with managerial and clinical information needs, as well as educational and research aims that are important in the setting of a university hospital, Erasmus Medical Center Rotterdam, The Netherlands, developed a data warehouse incrementally. In this paper we report on the in-house development of an integral part of the data warehouse specifically for the intensive care units (ICU-DWH). It was modeled using Atos Origin Metadata Frame method. The paper describes the methodology, the development process and the content of the ICU-DWH, and discusses the need for (clinical) data warehouses in intensive care.     

Coordination in information exchange between organizationaldecision units

The information technology (IT) infrastructure of today's organization is often one of distributed networked computing, with a flexible architecture to incorporate diverse software and hardware components to meet the needs of different user groups. One problem that may be encountered in this environment is the lack of information exchange across user groups or teams because of incompatible data definitions, diversity of formats, and differences in information processing capabilities and IT resource allocation across the organization. Successful information flows involve a user group providing information attribute levels (e.g., levels of precision or detail, timeliness, etc.), data definitions, formats and presentation styles required by the recipient group(s). When information exchange occurs without a fit between the attribute required and that provided, we have the problem of “information coordination.” It is thus critical to design and implement a set of organizational mechanisms which will encourage units within an organization to share relevant information in a coordinated manner. We develop a stylized model of coordination based information exchange between two decision units, and show that structured communication regarding the units' intended information sharing choices can partly mitigate the problem of coordination. When there is uniformity in information management capability and IT resources across the organization, the positive impact of such communication is reinforced, These results imply an emerging role of MIS, where the latter functions as a coordinator of communication and understanding between interdependent derision units, and a facilitator of equity in information processing capability across the units     

Assessing realized information systems strategy

This research developed and validated a tool to measure realized information systems strategy or existing uses of information technology in organizations. It was recognized that intended uses of technology often differ from actual uses. The objective of the study was to determine a valid and reliable way of quantifying how information technology is actually used by organizations to provide support for business operations.     

Assessing event correlation in non-process-aware information systems

Many present-day companies carry out a huge amount of daily operations through the use of their information systems without ever having done their own enterprise modeling. Business process mining is a well-proven solution which is used to discover the underlying business process models that are supported by existing information systems. Business process discovery techniques employ event logs as input, which are recorded by process-aware information systems. However, a wide variety of traditional information systems do not have any in-built mechanisms with which to collect events (representing the execution of business activities). Various mechanisms with which to collect events from non-process-aware information systems have been proposed in order to enable the application of process mining techniques to traditional information systems. Unfortunately, since business processes supported by traditional information systems are implicitly defined, correlating events into the appropriate process instance is not trivial. This challenge is known as the event correlation problem. This paper presents an adaptation of an existing event correlation algorithm and incorporates it into a technique in order to collect event logs from the execution of traditional information systems. The technique first instruments the source code to collect events together with some candidate correlation attributes. Based on several well-known design patterns, the technique provides a set of guidelines to support experts when instrumenting the source code. The event correlation algorithm is subsequently applied to the data set of events to discover the best correlation conditions, which are then used to create event logs. The technique has been semi-automated to facilitate its validation through an industrial case study involving a writer management system and a healthcare evaluation system. The study demonstrates that the technique is able to discover an appropriate correlation set and obtain well-formed event logs, thus enabling business process mining techniques to be applied to traditional information systems.     

A data model for managing drug therapy within a patient data management system for intensive care units

The major intent of this article was to describe the design principles of the drug-therapy documentation module of the Patient Data Management System (PDMS) ICUData, in routine use at the intensive care unit (ICU) of the Department of Anesthesiology and Intensive Care Medicine at the University Hospital of Giessen, Germany, since February 1999. The new drug management system has been in routine use since March 2000. Until 8 January 2001, 1140 patients have been documented using this approach. It could be demonstrated that it was possible to transform the formerly unstructured text-based documentation into a detailed and structured model. The mediated benefit resulted in the automatic calculation of fluid balance. Further, detailed statistical analyses of therapeutic behavior in drug administration are now possible.     

The internet and the information environment

The Internet has changed the information environment in which people involved in scientific work live in slightly over ten years. The purpose of this article is to trace the vector of these changes using several examples, first of all, by the example of linguistics, using the LINGUIST List system as an example. In this paper, different principles of organizing information interaction in science are discussed, which are “vertical information,” principles, being implemented in our country by VINITI RAS and other information services, and the information self-organization of the scientific community, which relies on the network information infrastructure of the Internet.     

Context-based information analysis for the Web environment

Finding the relevant set of information that satisfies an information request of a Web user in the availability of today’s vast amount of digital data is becoming a challenging problem. Currently, available Information Retrieval (IR) Systems are designed to return long lists of results, only a few of which are relevant for a specific user. In this paper, an IR method called Context-Based Information Analysis (CONIA) that investigates the context information of the user and user’s information request to provide relevant results for the given domain users is introduced. In this paper, relevance is measured by the semantics of the information provided in the documents. The information extracted from lexical and domain ontologies is integrated by the user’s interest information to expand the terms entered in the request. The obtained set of terms is categorized by a novel approach, and the relations between the categories are obtained from the ontologies. This categorization is used to improve the quality of the document selection by going beyond checking the availability of the words in the document by analyzing the semantic composition of the mapped terms.