Hannes Hagström1,2,3, Leon A Adams4, Alina M Allen5, Christopher D Byrne6,7, Yoosoo Chang8, Henning Grønbaek9, Mona Ismail10,11, Peter Jepsen9, Fasiha Kanwal12, Jennifer Kramer12, Jeffrey V Lazarus13, Michelle T Long14, Rohit Loomba15, Philip N Newsome16,17, Ian A Rowe18, Seungho Ryu8,19, Jörn M Schattenberg20, Marina Serper21, Nick Sheron22, Tracey G Simon23,24, Elliot B Tapper25, Sarah Wild26, Vincent Wai-Sun Wong27, Yusuf Yilmaz28,29, Shira Zelber-Sagi30, Fredrik Åberg31,32. 1. Division of Hepatology, Department of Upper GI, Karolinska University Hospital, Stockholm, Sweden. 2. Clinical Epidemiology Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden. 3. Department of Medicine, Huddinge, Karolinska Institutet, Stockholm, Sweden. 4. Medical School, University of Western Australia, Perth, WA, Australia. 5. Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN. 6. Nutrition and Metabolism, Faculty of Medicine, University of Southampton, Southampton, United Kingdom. 7. Southampton National Institute for Health Research Biomedical Research Centre, University Hospital Southampton, Southampton General Hospital, Southampton, United Kingdom. 8. Center for Cohort Studies, Total Healthcare Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 9. Department of Hepatology and Gastroenterology, Aarhus University Hospital, Aarhus, Denmark. 10. Division of Gastroenterology, Department of Internal Medicine, King Fahad Hospital of the University, Al-Khobar, Saudi Arabia. 11. College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia. 12. Baylor College of Medicine and Michael E. DeBakey VA Medical Center, Houston, TX. 13. Barcelona Institute for Global Health (ISGlobal), Hospital Clínic, University of Barcelona, Barcelona, Spain. 14. Department of Medicine, Section of Gastroenterology, Boston University School of Medicine, Boston, MA. 15. NAFLD Research Center, Division of Gastroenterology and Epidemiology, University of California at San Diego, La Jolla, CA. 16. National Institute for Health Research Biomedical Research Centre at University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, United Kingdom. 17. Centre for Liver and Gastrointestinal Research, Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, United Kingdom. 18. Leeds Institute for Medical Research, University of Leeds, Leeds, United Kingdom. 19. Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea. 20. Metabolic Liver Research Program, I. Department of Medicine, University Medical Center of the Johannes Gutenberg-University, Mainz, Germany. 21. Division of Gastroenterology and Hepatology, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 22. Foundation for Liver Research, London, United Kingdom. 23. Division of Gastroenterology and Hepatology, Massachusetts General Hospital, Boston, MA. 24. Harvard Medical School, Boston, MA. 25. Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, MI. 26. Usher Institute, University of Edinburgh, Edinburgh, United Kingdom. 27. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong. 28. Liver Research Unit, Institute of Gastroenterology, Marmara University, Istanbul, Turkey. 29. Department of Gastroenterology, School of Medicine, Marmara University, Istanbul, Turkey. 30. School of Public Health, University of Haifa, Haifa, Israel. 31. Transplantation and Liver Surgery Clinic, Helsinki University Hospital, Helsinki, Finland. 32. University of Helsinki, Helsinki, Finland.
Abstract
BACKGROUND AND AIMS: Electronic health record (EHR)-based research allows the capture of large amounts of data, which is necessary in NAFLD, where the risk of clinical liver outcomes is generally low. The lack of consensus on which International Classification of Diseases (ICD) codes should be used as exposures and outcomes limits comparability and generalizability of results across studies. We aimed to establish consensus among a panel of experts on ICD codes that could become the reference standard and provide guidance around common methodological issues. APPROACH AND RESULTS: Researchers with an interest in EHR-based NAFLD research were invited to collectively define which administrative codes are most appropriate for documenting exposures and outcomes. We used a modified Delphi approach to reach consensus on several commonly encountered methodological challenges in the field. After two rounds of revision, a high level of agreement (>67%) was reached on all items considered. Full consensus was achieved on a comprehensive list of administrative codes to be considered for inclusion and exclusion criteria in defining exposures and outcomes in EHR-based NAFLD research. We also provide suggestions on how to approach commonly encountered methodological issues and identify areas for future research. CONCLUSIONS: This expert panel consensus statement can help harmonize and improve generalizability of EHR-based NAFLD research.
BACKGROUND AND AIMS: Electronic health record (EHR)-based research allows the capture of large amounts of data, which is necessary in NAFLD, where the risk of clinical liver outcomes is generally low. The lack of consensus on which International Classification of Diseases (ICD) codes should be used as exposures and outcomes limits comparability and generalizability of results across studies. We aimed to establish consensus among a panel of experts on ICD codes that could become the reference standard and provide guidance around common methodological issues. APPROACH AND RESULTS: Researchers with an interest in EHR-based NAFLD research were invited to collectively define which administrative codes are most appropriate for documenting exposures and outcomes. We used a modified Delphi approach to reach consensus on several commonly encountered methodological challenges in the field. After two rounds of revision, a high level of agreement (>67%) was reached on all items considered. Full consensus was achieved on a comprehensive list of administrative codes to be considered for inclusion and exclusion criteria in defining exposures and outcomes in EHR-based NAFLD research. We also provide suggestions on how to approach commonly encountered methodological issues and identify areas for future research. CONCLUSIONS: This expert panel consensus statement can help harmonize and improve generalizability of EHR-based NAFLD research.
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