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논문 기본 정보

자료유형
학술저널
저자정보
Abdullah Hairil Rizal (Duke-NUS Medical School) Lim Daniel Yan Zheng (Duke-NUS Medical School) Ke Yuhe (Department of Anesthesiology and Perioperative Medicine, Singapore General Hospital) Salim Nur Nasyitah Mohamed (Health Services Research Unit, Singapore General Hospital) Lan Xiang (Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore) Dong Yizhi (Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore) Feng Mengling (Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore)
저널정보
대한마취통증의학회(구 대한마취과학회) Korean Journal of Anesthesiology Korean Journal of Anesthesiology Vol.77 No.1
발행연도
2024.2
수록면
58 - 65 (8page)
DOI
10.4097/kja.23580

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Background: To enhance perioperative outcomes, a perioperative registry that integrates high-quality real-world data throughout the perioperative period is essential. Singapore General Hospital established the Perioperative and Anesthesia Subject Area Registry (PASAR) to unify data from the preoperative, intraoperative, and postoperative stages. This study presents the methodology employed to create this database.Methods: Since 2016, data from surgical patients have been collected from the hospital electronic medical record systems, de-identified, and stored securely in compliance with privacy and data protection laws. As a representative sample, data from initiation in 2016 to December 2022 were collected.Results: As of December 2022, PASAR data comprise 26 tables, encompassing 153,312 patient admissions and 168,977 operation sessions. For this period, the median age of the patients was 60.0 years, sex distribution was balanced, and the majority were Chinese. Hypertension and cardiovascular comorbidities were also prevalent. Information including operation type and time, intensive care unit (ICU) length of stay, and 30-day and 1-year mortality rates were collected. Emergency surgeries resulted in longer ICU stays, but shorter operation times than elective surgeries.Conclusions: The PASAR provides a comprehensive and automated approach to gathering high-quality perioperative patient data.

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