ArticleKorean journal of anesthesiology2024
The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry.
Article in Korean journal of anesthesiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Article
- Establishment of a large-scale oral disease registry (NDCS-ODR) in a national specialty center.PloS one · 2026Article
- Implementing a Rapid Improvement Event with anonymised individual performance reporting on benign hysterectomy care: a retrospective comparative analysis.BMJ open quality · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundTo 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.
methodsSince 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.
resultsAs 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.
conclusionsThe PASAR provides a comprehensive and automated approach to gathering high-quality perioperative patient data.
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