A Digital Case-Finding Algorithm for Diagnosed but Untreated Hepatitis C: A Tool for Increasing Linkage to Treatment and Cure

Details

• Personal Author:
  Bowman CA ; Branch AD ; Collado F ; Dieterich D ; Dinani A ; Harty A ; Jeon J ; Li L ; Ma N ; Mageras A ; Miller M ; Paulino L ; Perumalswami PV ; Vandromme M ; Wyatt B
• Description:
  Background and aims: Although chronic HCV infection increases mortality, thousands of patients remain diagnosed-but-untreated (DBU). We aimed to (1) develop a DBU phenotyping algorithm, (2) use it to facilitate case finding and linkage to care, and (3) identify barriers to successful treatment. Approach and results: We developed a phenotyping algorithm using Java and SQL and applied it to approximately 2.5 million EPIC electronic medical records (EMRs; data entered January 2003 to December 2017). Approximately 72,000 EMRs contained an HCV International Classification of Diseases code and/or diagnostic test. The algorithm classified 10,614 cases as DBU (HCV-RNA positive and alive). Its positive and negative predictive values were 88% and 97%, respectively, as determined by manual review of 500 EMRs randomly selected from the approximately 72,000. Navigators reviewed the charts of 6,187 algorithm-defined DBUs and they attempted to contact potential treatment candidates by phone. By June 2020, 30% (n = 1,862) had completed an HCV-related appointment. Outcomes analysis revealed that DBU patients enrolled in our care coordination program were more likely to complete treatment (72% [n = 219] vs. 54% [n = 256]; P < 0.001) and to have a verified sustained virological response (67% vs. 46%; P < 0.001) than other patients. Forty-eight percent (n = 2,992) of DBU patients could not be reached by phone, which was a major barrier to engagement. Nearly half of these patients had Fibrosis-4 scores = 2.67, indicating significant fibrosis. Multivariable logistic regression showed that DBUs who could not be contacted were less likely to have private insurance than those who could (18% vs. 50%; P < 0.001). Conclusions: The digital DBU case-finding algorithm efficiently identified potential HCV treatment candidates, freeing resources for navigation and coordination. The algorithm is portable and accelerated HCV elimination when incorporated in our comprehensive program. [Description provided by NIOSH]
• Subjects:
  Digestive System Digestive System Diseases Fibrosis Liver Mortality Occupational Health Safety Viral Diseases
• Keywords:
  Electronic Health Records Hepatitis C Liver Damage Liver Disorders Medical Records Mortality Rates Statistical Analysis Viral Infections
• ISSN:
  0270-9139
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Michigan ; New York ; OSHA Region 2 ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  74
• Issue:
  6
• NIOSHTIC Number:
  nn:20064464
• Citation:
  Hepatology 2021 Dec; 74(6):2974-2987
• Contact Point Address:
  Andrea D. Branch, Ph.D., Division of Liver Medicine, Icahn School of Medicine Mount Sinai, One Gustave L. Levy Place, Box 1123, New York, NY 10029
• Email:
  andrea.branch@mssm.edu
• Federal Fiscal Year:
  2022
• Performing Organization:
  Icahn School of Medicine at Mount Sinai, New York
• Peer Reviewed:
  True
• Start Date:
  20170701
• Source Full Name:
  Hepatology
• End Date:
  20210630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:b5a82fedc62b58a81d555f3f3892ca418ac90461cba67f1d955095389c59eeb51271e78a4ee21b6aa145c479e5b4f28695cc82cc5c420d1e19f9f9868765222d
• Download URL:
  https://stacks.cdc.gov/view/cdc/222917/cdc_222917_DS1.pdf
• File Type:
  [PDF - 644.23 KB ]