Introduction
Critically ill patients in hospital care usually have higher morbidity and mortality risks, therefore requiring rapid clinical decision-making. Extreme conditions raise the possibility of medical errors in the anesthetic prescription for those patients, which results in increased pain and reduced opportunities for treatment. Among the critically ill patients with the highest risks of mortality and the need for immediate anesthesia, the lack of informational support has strong negative effects on determining their outcomes. Additionally, during perioperative patient care, the standard manual examination does not allow for to identify of such implications as pronounced hypotension, arrhythmia, or hypoxemia are vital for proper adaptation planning.
Intervention (Using Telemedicine and Anaesthesia Information Management System)
Critically ill patients in the intervention group were treated by anaesthesiologists trained in using telemedicine and AIMS during the decision-making process. The patients were regularly monitored using computerized equipment, and anesthetic prescription decisions were made either based on clinical decision support algorithms or remote consultations with specialists from afar. Critically ill patients who had repeated hospitalization were excluded from the study due to the possible influence of treatment errors during previous treatment.
Comparison (Using Manual Diagnostics Strategy)
Critically ill patients in the control group were treated by anesthesiologists who were completely prohibited from using any external sources of information or support except their colleagues from their unit. The patients were monitored manually, and the transcription was made by office staff following the general standardization rules. The anesthesiologists were not offered to have manual access to previous recordings of similar cases. The patients with extreme life-threatening cases who demanded emergency treatment with the help of remote support were excluded from the control group.
Outcomes
With the help of the Anaesthesia Information Management System, anaesthesiologists were offered a significantly more comprehensive evaluation of each patient’s condition. Additionally, it provided information on hidden allergies to entered medications, the need to re-dose, and the reduplicative administration of drugs. Automatic warnings in the decision support system were able to prevent several medical errors in the anesthesia prescription process. The practice of telemedicine for remote consultation both with more experienced colleagues and electronic databases showed an increase in positive outcomes even when emergency help was needed. The electronic databases of condition recordings proved to be efficient for repeated diagnosing and consulting with previous precedents. The mortality rate was significantly reduced, and a noticeable decrease occurred in the percentage of patients transferred to intensive care units.
These intervention results are supported by Seshadri’s study, which examined the efficiency of AIMS in terms of speed and preciseness1(22). This study also proved the necessity of continuous re-testing of patients’ conditions in critical cases, which could only be provided by the electronic monitoring system. The observations made by Seshadri included error detection and correction. Regarding the operation of AIMS, it was noted that troubleshooting occurred immediately after the issue arose, which accelerated treatment and adaptation processes1(29). Overall, the PICOT research results comply with this study, and they both prove the ability of computerized anesthesia management systems to improve outcome statistics among critically ill patients.
Time
Measuring the outcomes was done for 1000 patients during three months period. The data on patients’ conditions were collected daily and sent to the electronic database, and preserved during the whole period of intervention.
Reference List
Seshadri M. Implementation of an Anesthesia Information Management System in an Ambulatory Surgery Center. JMS. 2015;40(1):22-30.