{"title":"利用综合分析套件开发自动内镜逆行胰胆管造影质量报告单","authors":"","doi":"10.1016/j.tige.2024.03.007","DOIUrl":null,"url":null,"abstract":"<div><h3>BACKGROUND AND AIMS</h3><p>Quality indicators (QIs) are essential for evaluating the safety and effectiveness of endoscopy but are difficult to measure accurately for endoscopic retrograde cholangiopancreatography (ERCP). We developed a fully automated, real-time endoscopy analytics tool using Health Level-7 standards that collects ERCP QIs from an endoscopy reporting system to generate an ERCP quality report card in a third-party analytics suite.</p></div><div><h3>METHODS</h3><p>ERCP report data were collected between June 2021 and December 2022 from 4 referral centers. Discrete data elements from endoscopy reports generated in the EndoPro reporting platform were imported into the Qlik analytics suite, and QI data were aggregated into a report card. The collected data were manually validated to confirm accuracy.</p></div><div><h3>RESULTS</h3><p>Pooled data were successfully used to generate a comprehensive institutional ERCP quality report card comprising a total of 2146 ERCPs performed by 12 endoscopists. Manual review confirmed high accuracy (96.5%-100%) of automatic extraction of ERCP QIs from endoscopy reports. Multiple procedural data elements were successfully extracted, including cannulation difficulty, success rate, and administration of post-ERCP pancreatitis prophylaxis for procedures with biliary and pancreatic indication. Generation of the report card required minimal additional work on the part of the performing endoscopist and was updated in real time.</p></div><div><h3>CONCLUSION</h3><p>We developed an automated ERCP analytics tool that accurately and automatically extracts QI data into a succinct ERCP quality report card without the need for manual data extraction or natural language processing. The use of the Health Level-7 standard provides a framework for the creation of similar tools in other electronic health records. This tool allows for accurate ERCP quality and performance data evaluation at individual and institutional levels.</p></div>","PeriodicalId":36169,"journal":{"name":"Techniques and Innovations in Gastrointestinal Endoscopy","volume":"26 3","pages":"Pages 230-236"},"PeriodicalIF":1.2000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590030724000217/pdfft?md5=d5468471c598744e8a9f817bc39b143e&pid=1-s2.0-S2590030724000217-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Development of an Automated Endoscopic Retrograde Cholangiopancreatography Quality Report Card Using an Integrated Analytics Suite\",\"authors\":\"\",\"doi\":\"10.1016/j.tige.2024.03.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>BACKGROUND AND AIMS</h3><p>Quality indicators (QIs) are essential for evaluating the safety and effectiveness of endoscopy but are difficult to measure accurately for endoscopic retrograde cholangiopancreatography (ERCP). We developed a fully automated, real-time endoscopy analytics tool using Health Level-7 standards that collects ERCP QIs from an endoscopy reporting system to generate an ERCP quality report card in a third-party analytics suite.</p></div><div><h3>METHODS</h3><p>ERCP report data were collected between June 2021 and December 2022 from 4 referral centers. Discrete data elements from endoscopy reports generated in the EndoPro reporting platform were imported into the Qlik analytics suite, and QI data were aggregated into a report card. The collected data were manually validated to confirm accuracy.</p></div><div><h3>RESULTS</h3><p>Pooled data were successfully used to generate a comprehensive institutional ERCP quality report card comprising a total of 2146 ERCPs performed by 12 endoscopists. Manual review confirmed high accuracy (96.5%-100%) of automatic extraction of ERCP QIs from endoscopy reports. Multiple procedural data elements were successfully extracted, including cannulation difficulty, success rate, and administration of post-ERCP pancreatitis prophylaxis for procedures with biliary and pancreatic indication. Generation of the report card required minimal additional work on the part of the performing endoscopist and was updated in real time.</p></div><div><h3>CONCLUSION</h3><p>We developed an automated ERCP analytics tool that accurately and automatically extracts QI data into a succinct ERCP quality report card without the need for manual data extraction or natural language processing. The use of the Health Level-7 standard provides a framework for the creation of similar tools in other electronic health records. This tool allows for accurate ERCP quality and performance data evaluation at individual and institutional levels.</p></div>\",\"PeriodicalId\":36169,\"journal\":{\"name\":\"Techniques and Innovations in Gastrointestinal Endoscopy\",\"volume\":\"26 3\",\"pages\":\"Pages 230-236\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2590030724000217/pdfft?md5=d5468471c598744e8a9f817bc39b143e&pid=1-s2.0-S2590030724000217-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Techniques and Innovations in Gastrointestinal Endoscopy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2590030724000217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Techniques and Innovations in Gastrointestinal Endoscopy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590030724000217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Development of an Automated Endoscopic Retrograde Cholangiopancreatography Quality Report Card Using an Integrated Analytics Suite
BACKGROUND AND AIMS
Quality indicators (QIs) are essential for evaluating the safety and effectiveness of endoscopy but are difficult to measure accurately for endoscopic retrograde cholangiopancreatography (ERCP). We developed a fully automated, real-time endoscopy analytics tool using Health Level-7 standards that collects ERCP QIs from an endoscopy reporting system to generate an ERCP quality report card in a third-party analytics suite.
METHODS
ERCP report data were collected between June 2021 and December 2022 from 4 referral centers. Discrete data elements from endoscopy reports generated in the EndoPro reporting platform were imported into the Qlik analytics suite, and QI data were aggregated into a report card. The collected data were manually validated to confirm accuracy.
RESULTS
Pooled data were successfully used to generate a comprehensive institutional ERCP quality report card comprising a total of 2146 ERCPs performed by 12 endoscopists. Manual review confirmed high accuracy (96.5%-100%) of automatic extraction of ERCP QIs from endoscopy reports. Multiple procedural data elements were successfully extracted, including cannulation difficulty, success rate, and administration of post-ERCP pancreatitis prophylaxis for procedures with biliary and pancreatic indication. Generation of the report card required minimal additional work on the part of the performing endoscopist and was updated in real time.
CONCLUSION
We developed an automated ERCP analytics tool that accurately and automatically extracts QI data into a succinct ERCP quality report card without the need for manual data extraction or natural language processing. The use of the Health Level-7 standard provides a framework for the creation of similar tools in other electronic health records. This tool allows for accurate ERCP quality and performance data evaluation at individual and institutional levels.