Background: The American Society of Anesthesiologists (ASA) score is generated based on patients' clinical status. Accurate ASA classification is essential for the communication of perioperative risks and resource planning. Literature suggests that ASA classification can be automated for consistency and time-efficiency.
View Article and Find Full Text PDFBackground: Technological advances in healthcare have enabled patients to participate in digital self-assessment, with reported benefits of enhanced healthcare efficiency and self-efficacy. This report describes the design and validation of a patient-administered preanaesthesia health assessment digital application for gathering medical history relevant to preanaesthesia assessment. Effective preoperative evaluation allows for timely optimization of medical conditions and reduces case cancellations on day of surgery.
View Article and Find Full Text PDFPreanaesthesia health assessment is gradually transitioning from paper-based, face-to-face assessment to digitized assessment, self-administered by the patient. This transition could potentially optimize the various goals of assessment, notably facilitating the efficient collection of the patient's health information. We have previously developed and validated a tablet application (PreAnaesThesia Computerized Health assessment application or "PATCH") for patients to conduct preanaesthesia self-assessment.
View Article and Find Full Text PDFPurpose: Epidural analgesia provides safe and effective labor pain relief. However, labor episodic pain can occur during epidural analgesia, requiring epidural top-ups, and may result in decreased patient satisfaction. The primary aim of our study was to investigate the factors associated with labor episodic pain during epidural analgesia.
View Article and Find Full Text PDF