Yuval Bitan

Nurses’ reactions to alarms in a neonatal intensive care unit

Neonatal intensive care units (NICUs), like other intensive care units, are intended to provide immediate responses to any change in the patient’s condition. Patient-monitoring alarms and alarms from other medical equipment are very common in these units, and most alarms have no clinical significance. This study addresses the question of how alarms affect nurses’ actions by measuring the occurrence of alarms from different causes in a NICU, recording the nurses’ reactions, and analyzing the relationship between the alarms and the actions. The results show that nurses often do not respond directly to alarms, but, rather, use them as additional sources of information in their ongoing flow of actions. The probabilities for their responding to an alarm depend on the causes of the alarm, its duration, and the characteristics of the patient. These findings support the view that experienced nurses dynamically adjust their activities according to the information they receive from alarm systems and other sources, and that they combine their reactive actions with the periodic performance of routine tasks.

Time to Get Off this Pig's Back? The Human Factors Aspects of the Mismatch Between Device and Real-world Knowledge in the Health Care Environment

Objectives: Automated piggybacks are purported to make drug administration safer and more reliable. We evaluated the human factors of piggyback infusion, investigated the practice in our institution, and analyzed incidents from an anonymous database to better characterize the practice and substantiate these assertions. Methods: To find examples of problems with piggyback, or secondary infusions, we searched the Food and Drug Administrations on-line incident database for incidents involving piggybacks. As part of a task analysis, 19 senior nurses each programmed 2 of 4 different pumps for a simulated piggyback infusion. To characterize infusion practice, we evaluated data logs from 55 infusion devices used in our institution. Results: Incidents from the database provided strong evidence that potential problems existed with piggyback infusions. Nurse behaviors suggested mismatches between the task, user, and devices that can lead to adverse events. Log files showed piggybacks were a common practice, and that available safeguards were not used. Conclusions: Our multiple data sources suggest automated piggyback infusion practice is neither simple nor safe. Incident report analysis suggests these findings contribute to adverse events. Further study is needed to understand and improve the safety of this practice.

Use of colour-coded labels for intravenous high-risk medications and lines to improve patient safety

Problem: Labelling of high-risk drug infusions and lines is a well-recognised safety strategy to prevent medication errors. Although hospital wards characterised by multiple high-risk drug infusions use different types of labelling, little is known about the contribution of a colour-coded label (CCL) to patient safety. Setting: A quality improvement programme audit at a tertiary care facility, the Hadassah University Medical Center Ein Kerem, Jerusalem, Israel. Strategy for change: A CCL for intravenous (IV) high-risk medications and lines was designed to promote safer medication administration at the intensive care unit bedside and in other acute wards. Methods: The purpose of the study was to compare a new CCL method (intervention) with the current labelling method (control). Laboratory simulation, imitating an intensive care unit, was designed. Safety of the medication treatment and overall duration of nurses’ orientation with drugs and lines at the patient’s bedside were measured. Effects of change: The use of the new CCL improved proper identification of IV bags (p<0.0001), reduced the time required for description of overall drugs and lines (p = 0.04), improved identification of errors at the treatment setting—drugs and lines (p = 0.03) and reduced the average performance time for overall tasks (p<0.0001). Lessons learnt: The use of CCLs for IV high-risk medications and lines can improve patient safety and improve medical staff efficiency.

Between choice and chance: the role of human factors in acute care equipment decisions.

Objectives: We report on a human factors evaluation project at a major urban teaching hospital that was intended to use human factors methods to assist the selection of a new infusion device among 4 commercially available models. Methods: The project provided an expert evaluation of the pumps, collected data on programming each pump by a sample of practitioners, tabulated recent adverse event reports in the US Food and Drug Administration Manufacturer and User Device Experience database, and observed actual use in intensive care and hematology/oncology units. Results: Programming by clinicians showed no correlation between clinical experience and ability to program any of the pumps under consideration. Field observations reflected diverse use patterns across services that required ease of use pumps did not offer. Upon review of a final candidate pump, purchasing preferences superceded clinical considerations. Conclusions: Equipment and systems that are intended for use by clinicians must necessarily reflect an understanding of actual clinical practice to be well suited for use at the sharp (operator) end. However, purchase decisions for medical equipment including infusion devices are typically made by hospital staff members who are experienced in administrative and clinical matters but have no expertise in the evaluation of complex equipment. This project demonstrates how collaboration by human factors and clinical professionals can inform equipment decisions and assist clinician performance to improve patient safety. It also reveals how technical decisions that directly influence anesthesia staff performance and patient safety are subject to organizational factors such as social and political pressure.

Staff Actions and Alarms in a Neonatal Intensive Care Unit

Operators of complex systems must perform routine actions while attending to and responding to unexpected events. The current study extends previous laboratory experiments on the performance of such complex tasks to the analysis of the medical staffs actions in a Neonatal Intensive Care Unit (NICU). Observations showed that the attendants usually do not respond directly to warnings given from monitors, but that the sequence and timing of actions is affected by the warnings. The staff initiated most actions. There was no evidence for discrete decision points, but rather a continuous flow of activities. However, the overall pattern of actions corresponds to the predictions from analytical scheduling methods. These results and other observations of the staffs actions were analyzed in terms of “naturalistic decision making” and analytic decision analysis.

Scheduling of Actions and Reliance on Warnings in a Simulated Control Task

Operators of complex systems respond to external signals and events that guide their actions, but they also initiate and schedule the performance of various acts. An experiment was conducted in which the interdependence of scheduling and responding was studied. Participants had to monitor three stations that required different rates of interventions. The experimental conditions differed in the parameters of a warning system that indicated a possible malfunction in a station. The results showed that participants adjusted the frequencies of inspection in accordance with the required frequencies, but the adjustment was much smaller than was actually required. The settings of the warnings sensitivity and criterion threshold affected different aspects of the reliance on the warning system, and a distinction between reliance on warnings and obedience to warnings is suggested. The implications of these findings for the modeling of user actions in complex systems are discussed.

Displaying a boundary in graphic and symbolic “wait” displays: duration estimates and users' preferences

Two experiments assessed the effect of displaying a boundary on duration estimates and preference ratings for dynamic displays that were shown while users waited for the systems response. Displays were either symbolic (changing numbers) or graphic (increasing rectangles) and could contain a boundary that indicated when the interval was expected to be over. Duration estimates were similar for symbolic and graphic displays and for displays with and without a boundary. However, when the displays were encountered successively, participants assessed the graphic displays as having shorter durations than the symbolic displays. Faster rates of change in both types of displays led to increased duration estimates. Although displaying a boundary did not affect duration estimates, participants preferred displays in which a boundary was shown and preferred the graphic displays over the symbolic displays. Hence, bounded graphic displays are recommended as “wait” displays for computerized applications.

Correlating data from different sensors to increase the positive predictive value of alarms: an empiric assessment

Objectives: Alarm fatigue from high false alarm rate is a well described phenomenon in the intensive care unit (ICU). Progress to further reduce false alarms must employ a new strategy. Highly sensitive alarms invariably have a very high false alarm rate. Clinically useful alarms have a high Positive-Predictive Value. Our goal is to demonstrate one approach to suppressing false alarms using an algorithm that correlates information across sensors and replicates the ways that human evaluators discriminate artifact from real signal. Methods: After obtaining IRB approval and waiver of informed consent, a set of definitions, (hypovolemia, left ventricular shock, tamponade, hemodynamically significant ventricular tachycardia, and hemodynamically significant supraventricular tachycardia), were installed in the monitors in a 10 bed cardiothoracic ICU and evaluated over an 85 day study period. The logic of the algorithms was intended to replicate the logic of practitioners, and correlated information across sensors in a way similar to that used by practitioners. The performance of the alarms was evaluated via a daily interview with the ICU attending and review of the tracings recorded over the previous 24 hours in the monitor. True alarms and false alarms were identified by an expert clinician, and the performance of the algorithms evaluated using the standard definitions of sensitivity, specificity, positive predictive value, and negative predictive value. Results: Between 1 and 221 instances of defined events occurred over the duration of the study, and the positive predictive value of the definitions varied between 4.1% and 84%. Conclusions: Correlation of information across alarms can suppress artifact, increase the positive predictive value of alarms, and can employ more sophisticated definitions of alarm events than present single-sensor based systems.

Can a Log of Infusion Device Events Be Used to Understand Infusion Accidents

Objective: This study sought to determine whether infusion device event logs could support accident investigation. Methods: An incident reporting database was searched for information about log file use in investigations. Log file data from devices in clinical use were downloaded and electronically searched for characteristics (signatures) matching specific function queries. Different programming sequences were simulated, and device logs were downloaded for analysis. Results: Database reports mentioned difficulties resolving log file data to the incident report and used log file data to confirm programming failures. Log file search revealed that, aside from alarm types and times, the devices were unable to adequately satisfy functional queries. Different simulated programming scenarios could not be easily differentiated by log file analysis. Conclusions: The device logs we studied collect data that are poorly suited to accident investigation. We conclude that infusion device logs cannot function as black boxes do in aviation accidents. Logs would be better applied to assist routine operations.

Multidisciplinary Approach to Critical Care Design: Information Sources and Utilization During Morning Rounds

The goal of this project is to improve clinical decision-making in the intensive care unit (ICU) environment. Making the optimal decisions depends on the quality and timeliness of the information available to the clinician. We believe that healthcare professionals will make better clinical decisions when the relevant information is collected and organized in a manner appropriate to support in situ decision-making. This is especially important in complex situations such those commonly encountered in the ICU environment. Currently there is no single integrated source of information that presents relevant information to clinicians. This project is developing methods to identify the core information required to engineer the information exchange among medical devices, and the information presentation layer, to support clinical decision-making in the ICU.