Comparing Ventilation Parameters for COVID-19 Patients Using Both Long-Term ICU and Anesthetic Ventilators in Times of Shortage

In the first months of the COVID-19 pandemic in Europe, many patients were treated in hospitals using mechanical ventilation. However, due to a shortage of ICU ventilators, hospitals worldwide needed to deploy anesthesia machines for ICU ventilation (which is off-label use). A joint guidance was written to apply anesthesia machines for long-term ventilation. The goal of this research is to retrospectively evaluate the differences in measurable ventilation parameters between the ICU ventilator and the anesthesia machine as used for COVID-19 patients. In this study, we included 32 patients treated in March and April 2020, who had more than 3 days of mechanical ventilation, either in the regular ICU with ICU ventilators (Hamilton S1), or in the temporary emergency ICU with anesthetic ventilators (Aisys, GE). The data acquired during regular clinical treatment was collected from the Patient Data Management Systems. Available ventilation parameters (pressures and volumes: PEEP, Ppeak, Pinsp, Vtidal), monitored parameters EtCO2, SpO2, derived compliance C, and resistance R were processed and analyzed. A sub-analysis was performed to compare closed-loop ventilation (INTELLiVENT-ASV) to other ventilation modes. The results showed no major differences in the compared parameters, except for Pinsp. PEEP was reduced over time in the with Hamilton treated patients. This is most likely attributed to changing clinical protocol as more clinical experience and literature became available. A comparison of compliance between the 2 ventilators could not be made due to variances in the measurement of compliance. Closed loop ventilation could be used in 79% of the time, resulting in more stable EtCO2. From the analysis it can be concluded that the off-label usage of the anesthetic ventilator in our hospital did not result in differences in ventilation parameters compared to the ICU treatment in the first 4 days of ventilation.

Going the Full Circle: Upgrading the Patient Field Chart and Tag for Electronic Mass Casualty Incidents Solutions in Romania

Objective: Mass casualty incidents and disasters require functional and efficient patient data management systems, as well as smart interconnections with patient tracking applications. Various initiatives developed and tested patient field charts for large-scale events but there is no one definite general format accepted. The current research proposes an upgraded model of the official patient field chart issued by the Romanian Department for Emergency Situations in 2015 to be used for large-scale events.Measures: An upgraded model is created after a thorough content analysis, physical analysis, design upgrade and optimization process. Differences between the official and the upgraded model are measured and compared, and statistical computations are carried out.Results: The main distinctive features of the patient field chart are dynamic triage, unique code identification, QR visual codes, wireless tags and irreversible clear contamination status highlighting. The upgrade process results in almost doubling the available active area without the need to change the document size format of the product. Visual elements and features are included to optimize operation workflow.Conclusions: The upgraded model offers a variety of improvements for both the overall rescue effort as well as the end user of the product. It allows for previously unavailable features like unlimited dynamic triage and enables the use of electronic management solutions.

Organizational and Implementation Issues of Patient Data Management Systems in an Intensive Care Unit

Since the National Health Service reforms were introduced, the NHS has moved towards a greater emphasis on accountability and efficiency of healthcare. These changes rely on the swift delivery of IT systems, implemented into the NHS because of the urgency to collect data to support these measures. This case study details the events surrounding the introduction of a patient data management system into an intensive care unit in a UK hospital. It shows that its implementation was complex and involved organisational issues related to the costing of healthcare, legal and purchasing requirements, systems integration, training and staff expertise, and relationships with suppliers. It is suggested that the NHS is providing an R&D environment which others are benefiting from. The NHS is supporting software development activities that are not recognised, and the true costs of this task are difficult to estimate. It is also argued that introducing PDMS crystallises many different expectations making them unmanageably complex. This could also be due to PDMS being a higher order innovation that attempts to integrate information systems products and services with the core business.

Patient Data Management Systems in Critical Care

Electronic patient data management systems (PDMS) were clinically used for the first time in the 1970s. Their purpose was to automatically document vital parameters sampled by monitors and to replace handwritten medical files. Because of the continuous development of computer technology, however, demands on PDMS have increased immensely. PDMS are currently expected to assist clinicians at every level of intensive care, i.e., at the strategic level of physicians' orders and prescriptions, at the operational level, and at the administrative level. In 1994, a PDMS (CareVue; Agilent Technologies) was installed and further developed in the anesthesiologic intensive care unit of the university hospital in Tübingen. The goals of this article were to describe the current demands on PDMS, to communicate our experiences in implementing a PDMS, to list the costs of purchasing and maintaining the system, and to report on the acceptance among physicians and nursing personnel. This article may assist new users in planning for, purchasing, and implementing a PDMS.