Matthias Görges

Improving alarm performance in the medical intensive care unit using delays and clinical context.

INTRODUCTION: In an intensive care unit, alarms are used to call attention to a patient, to alert a change in the patients physiology, or to warn of a failure in a medical device; however, up to 94% of the alarms are false. Our purpose in this study was to identify a means of reducing the number of false alarms. METHODS: An observer recorded time-stamped information of alarms and the presence of health care team members in the patient room; each alarm response was classified as effective (action taken within 5 min), ineffective (no response to the alarm), and ignored (alarm consciously ignored or actively silenced). RESULTS: During the 200-h study period, 1271 separate entries by an individual to the room being observed were recorded, 1214 alarms occurred and 2344 tasks were performed. On average, alarms occurred 6.07 times per hour and were active for 3.28 min per hour; 23% were effective, 36% were ineffective, and 41% were ignored. The median alarm duration was 17 s. A 14-s delay before alarm presentation would remove 50% of the ignored and ineffective alarms, and a 19-s delay would remove 67%. Suctioning, washing, repositioning, and oral care caused 152 ignored or ineffective ventilator alarms. DISCUSSION: Introducing a 19-s alarm delay and automatically detecting suctioning, repositioning, oral care, and washing could reduce the number of ineffective and ignored alarms from 934 to 274. More reliable alarms could elicit more timely response, reduce workload, reduce noise pollution, and potentially improve patient safety.

Evaluations of Physiological Monitoring Displays: A Systematic Review

The purpose of this paper is to present the findings from a systematic review of evaluation studies for physiologic monitoring displays, centered on empirical assessments across all available settings and samples. The findings from this review give readers the opportunity to examine past work across studies and set the stage for the design and conduct of future evaluations. A broad literature search of the literature from 1991 to June 2007 on PubMed and PsycINFO databases was completed to locate data-based articles for physiologic monitoring device display evaluations. The results of this search plus several unpublished works yielded 23 publications and 31 studies. Participants were faster detecting an adverse event, making a diagnosis or a clinical decision in 18 of 31 studies. They showed improved accuracy in a clinical decision or diagnosis in 13 of 19 studies and they perceived a decreased mental workload in 3 of 8 studies. Eighteen studies used a within subjects design (mean sample size 16.5), and 9 studies used a between group design (mean group size 7.6). Study settings were usability laboratories for 15 studies and patient simulation laboratories for 6 studies. Study participants were anesthesiologists or anesthesiology residents for 19 studies and nurses for 5 studies. The advent of integrated graphical displays ushered a new era into physiological monitoring display designs. All but one study reported significant differences between traditional, numerical displays and novel displays; yet we know little about which graphical displays are optimal and why particular designs work. Future authors should use a theoretical model or framework to guide the study design, focus on other clinical study participants besides anesthesiologists, employ additional research methods and use more realistic and complex tasks and settings to increase external validity.

University of Queensland vital signs dataset: Development of an accessible repository of anesthesia patient monitoring data for research

BACKGROUND: Data recorded from the devices used to monitor a patients vital signs are often used in the development of displays, alarms, and information systems, but high-resolution, multiple-parameter datasets of anesthesia monitoring data from patients during anesthesia are often difficult to obtain. Existing databases have typically been collected from patients in intensive care units. However, the physical state of intensive care patients is dissimilar to those undergoing surgery, more frequent and marked changes to cardiovascular and respiratory variables are seen in operating room patients, and additional and highly relevant information to anesthesia (e.g., end-tidal agent monitoring, etc.) is omitted from these intensive care databases. We collected a set of high-quality, high-resolution, multiple-parameter monitoring data suitable for anesthesia monitoring research. METHODS: Vital signs data were recorded from patients undergoing anesthesia at the Royal Adelaide Hospital. Software was developed to capture, time synchronize, and interpolate vital signs data from Philips IntelliVue MP70 and MP30 patient monitors and Datex-Ohmeda Aestiva/5 anesthesia machines into 10 millisecond resolution samples. The recorded data were saved in a variety of accessible file formats. RESULTS: Monitoring data were recorded from 32 cases (25 general anesthetics, 3 spinal anesthetics, 4 sedations) ranging in duration from 13 minutes to 5 hours (median 105 min). Most cases included data from the electrocardiograph, pulse oximeter, capnograph, noninvasive arterial blood pressure monitor, airway flow, and pressure monitor and, in a few cases, the Y-piece spirometer, electroencephalogram monitor, and arterial blood pressure monitor. Recorded data were processed and saved into 4 file formats: (1) comma-separated values text files with full numerical and waveform data, (2) numerical parameters recorded in comma-separated values files at 1-second intervals, (3) graphical plots of all waveform data in a range of resolutions as Portable Network Graphics image files, and (4) graphical overview plots of numerical data for entire cases as Portable Network Graphics and Scalable Vector Graphics files. The complete dataset is freely available online via doi:102.100.100/6914 and has been listed in the Australian National Data Service Collections Registry. DISCUSSION: The present dataset provides clinical anesthesia monitoring data from entire surgical cases where patients underwent anesthesia, includes a wide range of vital signs variables that are commonly monitored during surgery, and is published in accessible, user-friendly file formats. The text and image file formats let researchers without engineering or computer science backgrounds easily access the data using standard spreadsheet and image browsing software. In future work, monitoring data should be collected from a wider range and larger number of cases, and software tools are needed to support searching and navigating the database.

Development of mHealth applications for pre-eclampsia triage.

The development of mobile applications for the diagnosis and management of pregnant women with pre-eclampsia is described. These applications are designed for use by community-based health care providers (c-HCPs) in health facilities and during home visits to collect symptoms and perform clinical measurements (including pulse oximeter readings). The clinical data collected in women with pre-eclampsia are used as the inputs to a predictive model providing a risk score for the development of adverse outcomes. Based on this risk, the applications provide recommendations on treatment, referral, and reassessment. c-HCPs can access patient records across multiple visits, using multiple devices that are synchronized using a secure Research Electronic Data Capture server. A unique feature of these applications is the ability to measure oxygen saturation with a pulse oximeter connected to a smartphone (Phone Oximeter). The mobile health application development process, including challenges encountered and solutions are described.

Identifying a rapid bolus dose of dexmedetomidine (ED50) with acceptable hemodynamic outcomes in children

Dexmedetomidine is a highly sensitive, specific α2 adrenoceptor agonist with anxiolytic, sedative, and analgesic effects. Administration is recommended as a loading dose infused over 10 min. Clinical experience and a previous study suggested a shorter time frame might be used without causing adverse hemodynamic effects.

Experience report: functional programming of mHealth applications

A modular framework for the development of medical applications that promotes deterministic, robust and correct code is presented. The system is based on the portable Gambit Scheme programming language and provides a flexible cross-platform environment for developing graphical applications on mobile devices as well as medical instrumentation interfaces running on embedded platforms. Real world applications of this framework for mobile diagnostics, telemonitoring and automated drug infusions are reported. The source code for the core framework is open source and available at: https://github.com/part-cw/lambdanative.

A retrospective audit to examine the effectiveness of preoperative warming on hypothermia in spine deformity surgery patients.

Hypothermia (core body temperature <36°C) during surgery has been associated with surgical site infection, a major risk in all spine deformity surgeries. Forced air warming is an important method of intraoperative temperature maintenance in children. In mid‐2010, we empirically introduced preoperative warming as a strategy to reduce intraoperative hypothermia.

An evaluation of an expert system for detecting critical events during anesthesia in a human patient simulator: a prospective randomized controlled study.

BACKGROUND: Perioperative monitoring systems produce a large amount of uninterpreted data, use threshold alarms prone to artifacts, and rely on the clinician to continuously visually track changes in physiological data. To address these deficiencies, we developed an expert system that provides real-time clinical decisions for the identification of critical events. We evaluated the efficacy of the expert system for enhancing critical event detection in a simulated environment. We hypothesized that anesthesiologists would identify critical ventilatory events more rapidly and accurately with the expert system. METHODS: We used a high-fidelity human patient simulator to simulate an operating room environment. Participants managed 4 scenarios (Anesthetic Vapor Overdose, Tension Pneumothorax, Anaphylaxis, and Endotracheal Tube Cuff Leak) in random order. In 2 of their 4 scenarios, participants were randomly assigned to the expert system, which provided trend-based alerts and potential differential diagnoses. Time to detection and time to treatment were measured. Workload questionnaires and structured debriefings were completed after each scenario, and a usability questionnaire at the conclusion of the session. Data were analyzed using a mixed-effects linear regression model; Fisher exact test was used for workload scores. RESULTS: Twenty anesthesiology trainees and 15 staff anesthesiologists with a combined median (range) of 36 (29–66) years of age and 6 (1–38) years of anesthesia experience participated. For the Endotracheal Tube Cuff Leak, the expert system caused mean reductions of 128 (99% confidence interval [CI], 54–202) seconds in time to detection and 140 (99% CI, 79–200) seconds in time to treatment. In the other 3 scenarios, a best-case decrease of 97 seconds (lower 99% CI) in time to diagnosis for Anaphylaxis and a worst-case increase of 63 seconds (upper 99% CI) in time to treatment for Anesthetic Vapor Overdose were found. Participants were highly satisfied with the expert system (median score, 2 on a scale of 1–7). Based on participant debriefings, we identified avoidance of task fixation, reassurance to initiate invasive treatment, and confirmation of a suspected diagnosis as 3 safety-critical areas. CONCLUSION: When using the expert system, clinically important and statistically significant decreases in time to detection and time to treatment were observed for the Endotracheal Tube Cuff Leak scenario. The observed differences in the other 3 scenarios were much smaller and not statistically significant. Further evaluation is required to confirm the clinical utility of real-time expert systems for anesthesia.

Changes in cardiac index and blood pressure on positioning children prone for scoliosis surgery

In this prospective observational study we investigated the changes in cardiac index and mean arterial pressure in children when positioned prone for scoliosis correction surgery. Thirty children (ASA 1–2, aged 13–18 years) undergoing primary, idiopathic scoliosis repair were recruited. The cardiac index and mean arterial blood pressure (median (IQR [range])) were 2.7 (2.3–3.1 [1.4–3.7]) l.min−1.m−2 and 73 (66–80 [54–91]) mmHg, respectively, at baseline; 2.9 (2.5–3.2 [1.7–4.4]) l.min−1.m−2 and 73 (63–81 [51–96]) mmHg following a 5‐ml.kg−1 fluid bolus; and 2.5 (2.2–2.7 [1.4–4.8]) l.min−1.m−2 and 69 (62–73 [46–85]) mmHg immediately after turning prone. Turning prone resulted in a median reduction in cardiac index of 0.5 l.min−1.m−2 (95% CI 0.3–0.7 l.min−1.m−2, p = 0.001), or 18.5%, with a large degree of inter‐subject variability (+ 10.3% to − 40.9%). The changes in mean arterial blood pressure were not significant. Strategies to predict, prevent and treat decreases in cardiac index need to be developed.

Preoperative warming and undesired surgical and anesthesia outcomes in pediatric spinal surgery—a retrospective cohort study

Underbody forced air warming is a method commonly used for intraoperative temperature maintenance in children. We previously reported that preoperative forced air warming of children undergoing spinal surgery substantially reduces the incidence and duration of intraoperative hypothermia (<36°C).