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This paper describes the development and implementation of an anesthesia data warehouse in the Lille University Hospital. We share the lessons learned from a ten-year project and provide guidance for the implementation of such a project. Our clinical data warehouse is mainly fed with data collected by the anesthesia information management system and hospital discharge reports. The data warehouse stores historical and accurate data with an accuracy level of the day for administrative data, and of the second for monitoring data. Datamarts complete the architecture and provide secondary computed data and indicators, in order to execute queries faster and easily. Between 2010 and 2021, 636 784 anesthesia records were integrated for 353 152 patients. We reported the main concerns and barriers during the development of this project and we provided 8 tips to handle them. We have implemented our data warehouse into the OMOP common data model as a complementary downstream data model. The next step of the project will be to disseminate the use of the OMOP data model for anesthesia and critical care, and drive the trend towards federated learning to enhance collaborations and multicenter studies., (© 2022. The Author(s).)

The ANI is a nociception monitor based on the high frequency parts of heart rate variability. Tracheal intubation may induce potentially deleterious hemodynamic disturbances or motor reactions if analgesia is inadequate. We investigated whether ANI modification generated by a standardized moderate short tetanic stimulation performed before laryngoscopy could predict hemodynamic or somatic reactions to subsequent intubation. We designed a prospective, interventional, monocentric, pilot study. Regional ethics board approved the study, written informed consent was obtained from each participant. Before laryngoscopy, under steady-state total intravenous anaesthesia with propofol and remifentanil, the ulnar nerve was stimulated with a 5 s tetanus (70 mA, 50 Hz). After another steady-state period, orotracheal intubation was performed. ANI variation, hemodynamic parameters and somatic reactions associated with tetanus and intubation were collected. To assess the predictability of hemodynamic or somatic reaction during laryngoscopy by tetanus-induced ANI variation, we calculated the area under the corresponding Receiver Operating Characteristic curve (AUCROC) and the 95% confidence intervals. Thirty-five patients were analyzed. ANI decreased by 21 ± 17 after tetanus. Regarding the ability of tetanus-induced ANI variation to predict hemodynamic or somatic reactions during subsequent intubation, the AUCROCs [95% CI] were 0.61 [0.41-0.81] and 0.52 [0.31-0.72] respectively. ANI varied after a short moderate tetanic stimulation performed before laryngoscopy but this variation was not predictive of a hemodynamic or somatic reaction during intubation.Trial registration NCT04354311, April 20th 2020, retrospectively registered., (© 2021. Springer Nature B.V.)

Clinical dashboards summarize indicators of high-volume patient data in a concise, user-friendly visual format. There are few studies of the use of dashboards to improve professional practice in anesthesiology. The objective of the present study was to describe the user-centered development, implementation and preliminary evaluation of clinical dashboards dealing with anesthesia unit management and quality assessment in a French university medical center. User needs and technical requirements were identified in end user interviews and then synthesized. Several representations were then developed (according to good visualization practice) and submitted to end users for appraisal. Lastly, dashboards were implemented and made accessible for everyday use via the medical center's network. After a period of use, end user feedback on the dashboard platform was collected as a system usability score (range 0 to 100). Seventeen themes (corresponding to 29 questions and 42 indicators) were identified. After prioritization and feasibility assessment, 10 dashboards were ultimately implemented and deployed. The dashboards variously addressed the unit's overall activity, compliance with guidelines on intraoperative hemodynamics, ventilation and monitoring, and documentation of the anesthesia procedure. The mean (standard deviation) system usability score was 82.6 (11.5), which corresponded to excellent usability. We developed clinical dashboards for a university medical center's anesthesia units. The dashboards' deployment was well received by the center's anesthesiologists. The dashboards' impact on activity and practice after several months of use will now have to be assessed.

AIMS are optimized to find and display data and curves about one specific intervention but is not retrospective analysis on a huge volume of interventions. Such a system present two main limitation; (1) the transactional database architecture, (2) the completeness of documentation. In order to solve the architectural problem, data warehouses were developed to propose architecture suitable for analysis. However, completeness of documentation stays unsolved. In this paper, we describe a method which allows determining of substitution rules in order to detect missing anesthesia events in an anesthesia record. Our method is based on the principle that missing event could be detected using a substitution one defined as the nearest documented event. As an example, we focused on the automatic detection of the start and the end of anesthesia procedure when these events were not documented by the clinicians. We applied our method on a set of records in order to evaluate; (1) the event detection accuracy, (2) the improvement of valid records. For the year 2010-2012, we obtained event detection with a precision of 0.00 (-2.22; 2.00) min for the start of anesthesia and 0.10 (0.00; 0.35) min for the end of anesthesia. On the other hand, we increased by 21.1% the data completeness (from 80.3 to 97.2% of the total database) for the start and the end of anesthesia events. This method seems to be efficient to replace missing "start and end of anesthesia" events. This method could also be used to replace other missing time events in this particular data warehouse as well as in other kind of data warehouses.

The analgesia nociception index (ANI) is an online heart rate variability analysis proposed for assessment of the antinociception/nociception balance. In this observational study, we compared ANI with heart rate (HR) and systolic blood pressure (SBP) during various noxious stimuli in anaesthetized patients. 15 adult patients undergoing laparoscopic appendectomy or cholecystectomy were studied. Patients received target controlled infusions of propofol (adjusted to maintain the Bispectral index in the range [40-60]) and remifentanil (with target increase in case of haemodynamic reactivity [increase in HR and/or SBP >20% of baseline]), and cisatracurium. Medical staff was blind to the ANI monitor. ANI and haemodynamic data were recorded at predefined times before and during surgery, including tetanic stimulation of the ulnar nerve before start of surgery. Anaesthesia induction decreased HR and SBP, while high ANI values (88 [17]) were recorded, indicating parasympathetic predominance. In 10 out of 11 patients, tetanic stimulation led to a transient (<5 min) decrease in ANI to 48 (40) whereas HR and SBP did not change. After start of surgery, ANI decreased to 60 (39) and decreased further to 50 (15) after the pneumoperitoneum was inflated, while there was no significant change in HR or SBP. When haemodynamic reactivity occurred, ANI had further decreased to 40 (15). After completion of surgery, ANI returned to 90 (34). ANI seems more sensitive than HR and SBP to moderate nociceptive stimuli in propofol-anaesthetized patients. Whether ANI monitoring may allow preventing haemodynamic reactivity to noxious stimuli remains to be demonstrated.