" RATIONALE AND OBJECTIVES: Duration of weaning from mechanical ventilation may be reduced by the use of a systematic approach. We assessed whether a closed-loop knowledge-based algorithm introduced in a ventilator to act as a computer-driven weaning protocol can improve patient outcomes as compared with usual care. METHODS AND MEASUREMENTS: We conducted a multicenter randomized controlled study with concealed allocation to compare usual care for weaning with computer-driven weaning. The computerized protocol included an automatic gradual reduction in pressure support, automatic performance of spontaneous breathing trials (SBT), and generation of an incentive message when an SBT was successfully passed. One hundred forty-four patients were enrolled before weaning initiation. They were randomly allocated to computer-driven weaning or to physician-controlled weaning according to local guidelines. Weaning duration until successful extubation and total duration of ventilation were the primary endpoints. MAIN RESULTS: Weaning duration was reduced in the computer-driven group from a median of 5 to 3 d (p=0.01) and total duration of mechanical ventilation from 12 to 7.5 d (p=0.003). Reintubation rate did not differ (23 vs. 16%, p=0.40). Computer-driven weaning also decreased median intensive care unit (ICU) stay duration from 15.5 to 12 d (p=0.02) and caused no adverse events. The amount of sedation did not differ between groups. In the usual care group, compliance to recommended modes and to SBT was estimated, respectively, at 96 and 51%. CONCLUSIONS: The specific computer-driven system used in this study can reduce mechanical ventilation duration and ICU length of stay, as compared with a physician-controlled weaning process. "

" In critical care environments important medical and economical challenges are presented by the enhancement of therapeutic quality and the reduction of therapeutic costs. For this purpose several clinical studies have demonstrated a positive impact of the adoption of so-called clinical guidelines. Clinical guidelines represent well documented best practices in health care and are fundamental aspects of evidence-based medicine. However, at the bedside, such clinical guidelines remain difficult to use by the clinical staff. Recently, we have designed and implemented the knowledge-based SmartCare™ system that allows automated control of medical devices in critical care. SmartCare™ constitutes a clinical guideline engine since it executes one or more clinical guidelines on a specific medical device. The underlying methodology comprises two sequential phases and seamlessly combines knowledge engineering with expert system techniques, e.g. rule-based forward chaining and temporal reasoning, for clinical guidelines modelling and software engineering techniques for source code generation and for integration to the target platform. SmartCare™ was initially applied for the automated control of a mechanical ventilator and is currently being evaluated in a European multicentre clinical study started two years ago. Intermediate reports have been extremely positive and suggest a statistically significant reduction in the duration of mechanical ventilation using SmartCare™. The methodology allows SmartCare™ to be implemented effectively with other medical devices and/or with other appropriate guidelines. In this paper we report on the methodology, architecture and the resulting versatility of SmartCare™ for the automated execution of clinical guidelines. Benefits and lessons learned during its development are discussed "

"Introduction: Improving the quality and efficiency of health care delivery are important objectives in critical care. Process engineering approaches to identify, organize and standardize health care workflows have been employed to meet these goals. Evidence-based clinical guidelines (CGs) for critical care are among these approaches. Their impact on outcome measures have been investigated and quantified in several clinical studies, e.g. [1]. Outcome measures that were studied include the reduction of hospital stay, mortality, human errors, medical device induced complications and workload of clinical staff. A logical next step is now the implementation of standardized health care processes into medical technology by allowing CGs to be executed by medical devices. This could provide automated standardized workflow process support. Dräger Medical's SmartCareTM technology is a platform that allows the implementation and automatic execution of various CGs within a wide range of medical devices. The SmartCareTM expert system comprises a universal engine and a set of executable knowledge bases that each reflects a certain critical care process, as described by a CG. An expert system construction suite (Solvatio, iisy AG, Rimpar, Germany) is used to facilitate efficient, visual-oriented knowledge modeling as well as the transition to the runtime environment. It seamlessly combines process-, knowledge- and software-engineering tasks. The core paradigm is that if a medical device allows for reading access to its measurements, settings, and contextual information as well as for writing access to its settings, then every clinical guideline for that medical device is potentially automatable [2]. Currently the automation of a specific process for weaning patients from mechanical ventilation has been implemented in a commercial product. SmartCare™/PS as an add-on for EvitaXL (Dräger Medical, Germany) provides automated control in pressure support ventilation. It implements a weaning CG clinically developed by Dojat and Brochard [3]. Methods. A multi-center, randomized controlled study was carried out in five university hospitals. 144 medico-surgical ICU patients were enrolled in this study. Approximately half of the patients (n=70) were randomized to be weaned following the conventional weaning protocol used in the respective hospital, the other half were weaned using the automated SmartCare™ approach (n=74). Results. In comparison with manual implementation of conventional weaning CGs used in these intensive care units, SmartCare™/PS reduced weaning duration by 50%, total duration of mechanical ventilation by more than 30% and the ICU length of stay by almost 30 % [4]. Conclusion. The automated execution of CGs by medical devices is a logical and beneficial progression of workflow support in health care. The implementation of additional CGs is expected to demonstrate the efficiency of SmartCare™ technology throughout the complex development process from knowledge acquisition to knowledge execution."

" OBJECTIVE: To evaluate the ability of a computer-driven system (CDS) to manage pressure-support ventilation over prolonged periods and to predict weaning readiness compared to intensivists. The system continuously adapts pressure support, gradually decreases ventilatory assistance when possible, and indicates weaning readiness.DESIGN AND SETTING: A two-center, prospective, open, clinical, pilot study in medical ICUs of two university hospitals.PATIENTS AND PARTICIPANTS: 42 consecutive mechanically ventilated patients (60+/-14 years, SAPS II 39+/-15), 9 of whom were excluded.INTERVENTIONS: As soon as patients could tolerate pressure support, they were ventilated with the CDS. The times of weaning readiness determined by the intensivists and CDS were compared.MEASUREMENTS AND RESULTS: Weaning was successful in 25 patients and failed in 7; unplanned extubation occurred in 1 patient. Time on CDS ventilation was 3+/-3 days (maximum, 12 days). The CDS detected weaning readiness earlier than the intensivists in 17 patients, and intensivists earlier than the CDS in 4; in 11 patients detection times coincided.CONCLUSIONS: A CDS was successful in fully managing pressure-support ventilation over prolonged periods and often proposed weaning readiness earlier than the intensivists did. Use of this CDS may reduce the duration of mechanical ventilation. "