Development of an Automated Endoscopic Retrograde Cholangiopancreatography Quality Report Card Using an Integrated Analytics Suite

Anmol Singh, Eric Swei, Celestina Tolosa, Matthew Alverson, Todd A. Brenner, Avleen Kaur, Aida Metri, Mohammed Rifat Shaik, Nikhil Bush, Branislav Bujnak, Aly Strauss, Mouen Khashab, Eun Ji Shin, Vikesh Singh, Venkata S. Akshintala

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
JournalTechniques and Innovations in Gastrointestinal Endoscopy
DOIs
StateAccepted/In press - 2024

Keywords

  • Electronic health record
  • Endoscopic retrograde cholangiopancreatography
  • Health Level-7
  • Quality indicators
  • Report card
  • Structured data field

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Gastroenterology

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