Creating a High-Frequency Electronic Database in the PICU: The Perpetual Patient

Objective: Our objective was to construct a prospective high-quality and high-frequency database combining patient therapeutics and clinical variables in real time, automatically fed by the information system and network architecture available through fully electronic charting in our PICU. The purpose of this article is to describe the data acquisition process from bedside to the research electronic database. Design: Descriptive report and analysis of a prospective database. Setting: A 24-bed PICU, medical ICU, surgical ICU, and cardiac ICU in a tertiary care free-standing maternal child health center in Canada. Patients: All patients less than 18 years old were included at admission to the PICU. Interventions: None. Measurements and Main Results: Between May 21, 2015, and December 31, 2016, 1,386 consecutive PICU stays from 1,194 patients were recorded in the database. Data were prospectively collected from admission to discharge, every 5 seconds from monitors and every 30 seconds from mechanical ventilators and infusion pumps. These data were linked to the patient’s electronic medical record. The database total volume was 241 GB. The patients’ median age was 2.0 years (interquartile range, 0.0–9.0). Data were available for all mechanically ventilated patients (n = 511; recorded duration, 77,678 hr), and respiratory failure was the most frequent reason for admission (n = 360). The complete pharmacologic profile was synched to database for all PICU stays. Following this implementation, a validation phase is in process and several research projects are ongoing using this high-fidelity database. Conclusions: Using the existing bedside information system and network architecture of our PICU, we implemented an ongoing high-fidelity prospectively collected electronic database, preventing the continuous loss of scientific information. This offers the opportunity to develop research on clinical decision support systems and computational models of cardiorespiratory physiology for example. This work was performed at the CHU Sainte Justine, Montreal, QC, Canada. Drs. Brossier, El Taani, Sauthier, and Jouvet built the database. All authors gave input into the database development process and contributed to writing the article. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://ift.tt/2gIrZ5Y). Supported, in part, by grants from the “Fonds de Recherche du Québec-Santé (FRQS),” RONA donation, and Sainte Justine Hospital. Dr. Brossier received funding from Fonds de recherche du Québec - Nature et Technologies, the University of Montreal Faculty of Medicine, and from the foundation Neuro Trauma Marie Robert, and he disclosed that this research and development was supported by grants from the “Fonds de Recherche du Québec-Santé (FRQS),” RONA, and Sainte Justine Hospital. Dr. Emeriaud’s institution received funding from the Fonds de recherche du Québec en Santé (research scholarship). Dr. Jouvet’s institution received funding from RONA, Sainte Justine Hospital, Air Liquide Santé, and Covidien; he disclosed that medical devices were lent by Philips Healthcare, Hamilton Medical, and Maquet; and he disclosed receiving financial support from the public research agency of Quebec (Fonds de recherche Québec-Santé) and funding from the Quebec Ministry of Health. He has been invited to conferences by Covidien, Medunik, and Air Liquid Santé. Medical devices are lent to Dr. Jouvet by Hamilton Medical, Philips Medical, and Maquet. The remaining authors have disclosed that they do not have any potential conflicts of interest. For information regarding this article, E-mail: brossier-d@chu-caen.fr ©2018The Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

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