Multicentric study of monitoring alarms in the adult intensive care unit (ICU): a descriptive analysis.

OBJECTIVES: To assess the relevance of current monitoring alarms as a warning system in the adult ICU. DESIGN: Prospective, observational study. SETTINGS: Two university hospital, and three general hospital, ICUs. PATIENTS: Hundred thirty-one patients, ventilated at admission, from different shifts (morning, evening, night) combined with different stages of stay, early (0-3 days), intermediate (4-6 days) and late (> 6 days). INTERVENTIONS: Experienced nurses were asked to record the patient's characteristics and, for each alarm event, the reason, type and consequence. MEASUREMENTS AND MAIN RESULTS: The mean age of the patients included was 59.8 +/- 16.4 and SAPS1 was 15.9 +/- 7.4. We recorded 1971 h of care. The shift distribution was 78 mornings, 85 evenings and 83 nights; the stage distribution was 88 early, 78 intermediate and 80 late. There were 3188 alarms, an average of one alarm every 37 min: 23.7% were due to staff manipulation, 17.5% to technical problems and 58.8% to the patients. Alarms originated from ventilators (37.8%), cardiovascular monitors (32.7%), pulse oximeters (14.9%) and capnography (13.5%). Of the alarms, 25.8% had a consequence such as sensor repositioning, suction, modification of the therapy (drug or ventilation). Only 5.9% of the alarms led to a physician's being called. The positive predictive value of an alarm was 27% and its negative predictive value was 99%. The sensitivity was 97% and the specificity 58%. CONCLUSIONS: The study confirms that the level of monitoring in ICUs generates a great number of false-positive alarms.

Introduction of knowledge bases in patient's data management system: role of the user interface.

As the number of signals and data to be handled grows in intensive care unit, it is necessary to design more powerful computing systems that integrate and summarize all this information. The manual input of data as e.g. clinical signs and drug prescription and the synthetic representation of these data requires an ever more sophisticated user interface. The introduction of knowledge bases in the data management allows to conceive contextual interfaces. The objective of this paper is to show the importance of the design of the user interface, in the daily use of clinical information system. Then we describe a methodology that uses the man-machine interaction to capture the clinician knowledge during the clinical practice. The different steps are the audit of the user's actions, the elaboration of statistic models allowing the definition of new knowledge, and the validation that is performed before complete integration. A part of this knowledge can be used to improve the user interface. Finally, we describe the implementation of these concepts on a UNIX platform using OSF/MOTIF graphical interface.