The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry
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 preoperat...
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| Format: | Article |
| Language: | English |
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Korean Society of Anesthesiologists
2024-02-01
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| Series: | Korean Journal of Anesthesiology |
| Subjects: | |
| Online Access: | http://ekja.org/upload/pdf/kja-23580.pdf |
| _version_ | 1797335306366615552 |
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| author | Hairil Rizal Abdullah Daniel Yan Zheng Lim Yuhe Ke Nur Nasyitah Mohamed Salim Xiang Lan Yizhi Dong Mengling Feng |
| author_facet | Hairil Rizal Abdullah Daniel Yan Zheng Lim Yuhe Ke Nur Nasyitah Mohamed Salim Xiang Lan Yizhi Dong Mengling Feng |
| author_sort | Hairil Rizal Abdullah |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T08:35:04Z |
| format | Article |
| id | doaj.art-2cbc782d12044fdd85bd165e0344a797 |
| institution | Directory Open Access Journal |
| issn | 2005-6419 2005-7563 |
| language | English |
| last_indexed | 2024-03-08T08:35:04Z |
| publishDate | 2024-02-01 |
| publisher | Korean Society of Anesthesiologists |
| record_format | Article |
| series | Korean Journal of Anesthesiology |
| spelling | doaj.art-2cbc782d12044fdd85bd165e0344a7972024-02-02T01:33:48ZengKorean Society of AnesthesiologistsKorean Journal of Anesthesiology2005-64192005-75632024-02-01771586510.4097/kja.235808941The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registryHairil Rizal Abdullah0Daniel Yan Zheng Lim1Yuhe Ke2Nur Nasyitah Mohamed Salim3Xiang Lan4Yizhi Dong5Mengling Feng6 Department of Anesthesiology, Singapore General Hospital, Singapore Duke-NUS Medical School, Singapore Department of Anesthesiology, Singapore General Hospital, Singapore Health Services Research Unit, Singapore General Hospital, Singapore Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore, Singapore Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore, Singapore Saw Swee Hock School of Public Health and Institute of Data Science, National University of Singapore, SingaporeBackground 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.http://ekja.org/upload/pdf/kja-23580.pdfanesthesiabig datadata scienceintraoperative careperioperative carepostoperative carepreoperative carestatistical data interpretation |
| spellingShingle | Hairil Rizal Abdullah Daniel Yan Zheng Lim Yuhe Ke Nur Nasyitah Mohamed Salim Xiang Lan Yizhi Dong Mengling Feng The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry Korean Journal of Anesthesiology anesthesia big data data science intraoperative care perioperative care postoperative care preoperative care statistical data interpretation |
| title | The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry |
| title_full | The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry |
| title_fullStr | The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry |
| title_full_unstemmed | The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry |
| title_short | The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry |
| title_sort | singhealth perioperative and anesthesia subject area registry pasar a large scale perioperative data mart and registry |
| topic | anesthesia big data data science intraoperative care perioperative care postoperative care preoperative care statistical data interpretation |
| url | http://ekja.org/upload/pdf/kja-23580.pdf |
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