Computers in the ICU: why? What? And so what?

Electronic medical record in the intensive care unit

The EMR in the ICU has the utility of providing the necessary information to make sound clinical decisions for critically ill patients. For it to be optimized, the EMR must be more than just what is being replicated in the written record or merely a documentation tool; it must add value that supports and enhances clinical decision support. The EMR is too expensive a tool just to be a computer designed to ease documentation and retrieve data faster. Gardner and Huff have suggested that the EMR must answer three questions: Why, What, and So What. The "Why" is relatively easy to answer, but the "What" data to use so that the information is meaningful to a provider and the "So What" are more difficult to answer. Provided one can qualitatively assess "What" information is important for a health care provider, then "So What" becomes an important objective in the empirical quantification of the benefits that the EMR provides. It is clear that to analyze some of the outcomes that health care delivery provides, one needs some mechanism to automate the information at the point of care, particularly now that the regulatory agencies are requiring it. Given the fact that there is no single integrated computerized patient record, this becomes the daunting task for the next century. Making it easier for health care providers to interact with the system and providing them with instantaneous feedback that changes their medical decision so they can deliver better care (clinical pathways, clinical practice guidelines) will be the task required of the next generation of CISs.

Computerized ventilator data selection: artifact rejection and data reduction

OBJECTIVE

To determine acceptable strategies for automated data acquisition and artifact rejection from computerized ventilators using the Medical Information Bus.

DESIGN

Medical practitioners were surveyed to establish 'clinically important' ventilator events. A prospective study involving frequent data collection from ventilators was also conducted.

SUBJECTS

Data from 10 adult patients were collected every 10 seconds from a Puritan Bennett 7200A ventilator for a total of 617.1 hours.

INTERVENTIONS

Twelve different computerized data selection and artifact algorithms were tested and evaluated.

MEASUREMENTS AND MAIN RESULTS

Data derived from 12 data selection algorithms were compared with each other and with data manually charted by respiratory therapists into a computerized charting system. Ventilator setting data collected by the algorithms, such as FIO2, reduced the amount of data collected to about 25% compared to manually charted data. The amount of data collected for measured parameters, such as tidal volume, from the ventilator had large variability and many artifacts. Automated data capture and selection generally increased the amount of data collected compared to manual charting, for example for the 3 minute median the increase was a modest 1.2 times.

CONCLUSION

Computerized methods for collecting ventilator setting data were relatively straightforward and more-efficient than manual methods. However, the method for automated selection and presentation of observed measured parameters is much more difficult. Based on the findings and analysis presented here, the authors recommend recording ventilator setting data after they have existed for three minutes and measured parameters using a three minute median data selection strategy. Such an algorithm rejected most artifacts, required minimal computational time, had minimal time-delay, and provided clinically acceptable data acquisition. The results presented here are but a starting point in developing automated ventilator data selection strategies.

Clinical Information Systems for Intensive Care, Pediatric Critical Care, and Neonatology

Computer information systems are expected to soon take the place of current paper charting practices, and they offer great promise to assist management of the considerable amounts of data encountered in the information-rich environment of intensive care units (ICUs). Efforts to create an electronic medical record (EMR) have been underway for more than two decades, and major national organizations, such as the Institute of Medicine, have issued recommendations on standards. Benefits of an EMR include a legible patient record, enhanced communication, provision of timely reminders and alerts to clinicians, reduction of calculation errors, access to data bases for quality assurance and research, reduced healthcare costs, and improved patient outcomes. Despite these benefits, successful EMR implementations have been confined to a few committed institutions, and expensive failures have occurred. Practitioners of neonatology and pediatric intensive care are likely to have substantial difficulty implementing an EMR to fit their specialized needs because most experience in this area has been gained through care of adult patients, and systems being developed are oriented toward nonpediatric patients. It is therefore important to examine experience thus far with the functional components of an EMR so practitioners will be able to evaluate systems better as they become available. System components discussed include nursing charting facilities, lab reporting, physician order entry, physician progress notes, structured reports, decision support systems, and problem list management. Other concerns discussed include research and quality assurance functions, data access and confidentiality issues, and electronic mail. Maximizing the “structured data” content, as opposed to narrative content of an EMR, is an important priority, and progress on developing a uniform medical language is discussed. An approach to evaluating clinical information systems for use in the ICU is presented; it should assist practitioners of pediatric critical care and neonatology in identifying computer-based charting solutions that are optimal for infants and children, while cooperating with medical center-wide needs for compatibility and a common data base.

Data processing in prehospital emergency medicine

Information about the use of data processing systems in prehospital emergency medicine were collected, using a questionnaire sent to all German rescue helicopter bases. Twenty-seven of the 42 German rescue helicopter bases returned the questionnaire. At present, only 15 of them take advantage of electronic data processing. All of them enter their data manually by keyboard, automatic data transfer by means of a bar code reader is available at one base only. The stored data are used for statistical analysis (n = 15), quality assessment (n = 10), administration (n = 10), research (n = 9) and education (n = 7). Based on the data of this survey, one fifth of those who replied use their computer only for administrative purposes, the other also manage patient and mission data with their computer systems. Today, documentation of a rescue mission consists of patient data, vital data, mission data and information about the procedures carried out. The use of a computer system, however, requires more time and work than a handwritten record, when most of the data have to be entered manually using a keyboard. Future developments may include automated data transfer and digitization of handwritten documents to decrease the workload of the staff. For the automation of data transfer, configuration and synchronisation a standardized interface in all medical devices is required. There is a clear need for the use of data processing systems in emergency medicine.

Challenges and opportunities for computerizing the anesthesia record

Most observers would agree that the goal of computerizing the anesthesia record is a worthy one. Despite the fact that several academic groups and vendors have attempted to develop and provide computerized anesthesia charting, the practice is not widespread. In this review article, we attempt to outline the reasons for this reluctance to use computers for anesthesia charting. Where there are problems to be solved, there also are opportunities. We discuss the development of strategies to solve these problems and thus present opportunities for medical informatics professionals and anesthesiologists to work toward joint solutions. Solving these problems includes the development of consensus standards and working out technical, social, and educational difficulties. Details of the approaches recommended are outlined.

Lessons learned while building an integrated ICU workstation

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.

Information transfer in high dependency environments: an ergonomic analysis

We have studied the information flow in HDE (with special focus on the information transfer process) using data provided by a group of experienced health care professionals. A model of the information flow in HDE was built up. It postulates the existence of quanta of information (due to the artificial fragmentation of the information flow produced by the clinical working processes: organization in shifts, demand of simultaneous activities from different staff members, etc.). This fragmentation is described by using the so-called Clinical Information Process Units (CIPUs), which correspond to patient care activities going on in parallely and serially linked blocks, performed by the staff in the specific environments. Due to a transfer in responsibility over the patient the CIPUs are linked by information transfer events which are described using transfer modules (TraMs). We exemplified 32 CIPUs related to the clinical environments (PreOp, Surgery, Recovery Intensive Care, Ward, Diagnostics, Outpatient) and the health care professional groups (Anesthesiologist/Intensivist, Surgeon, Nurse, Physician, Diagnostic Physician, Physical Therapist). A matrix was established providing the transfer situations among the CIPUs enabling a systematic classification of the TraMs. The contents of the TraMs are built up of information link elements, which are assembled according to the specific settings of the transfer situation given by the emitter, receiver and purpose. In summary we modelled the process of information transfer in HDE through CIPUs, TraMs and information links in a way, which may be useful to design information technology applications or to reorganize the information management in HDE.