Title

Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis: Development and Validation of Computable Phenotypes

Authors

Scott E. Wenderfer, Pediatric Nephrology, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas wenderfe@bcm.edu.
Joyce C. Chang, Pediatric Rheumatology, Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Amy Goodwin Davies, Applied Clinical Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Ingrid Y. Luna, Applied Clinical Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Rebecca Scobell, Pediatric Nephrology, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas.
Cora Sears, Pediatric Rheumatology, Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Bliss Magella, Pediatric Nephrology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Mark Mitsnefes, Pediatric Nephrology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Brian R. Stotter, Pediatric Nephrology, Hypertension and Pheresis, St. Louis Children's Hospital, Washington University in St. Louis, St. Louis, Missouri.
Vikas R. Dharnidharka, Pediatric Nephrology, Hypertension and Pheresis, St. Louis Children's Hospital, Washington University in St. Louis, St. Louis, Missouri.
Katherine D. Nowicki, Pediatric Rheumatology, University of Colorado School of Medicine, Aurora, Colorado.
Bradley P. Dixon, Pediatric Nephrology, University of Colorado School of Medicine, Aurora, Colorado.
Megan Kelton, Pediatrics, University of Washington, Seattle, Washington.
Joseph T. Flynn, Pediatrics, University of Washington, Seattle, Washington.
Caroline Gluck, Pediatric Nephrology, Nemours/Alfred I. DuPont Hospital for Children, Wilmington, Delaware.
Mahmoud Kallash, Center for Clinical and Translational Research, Nationwide Children's Hospital, Columbus, Ohio.
William E. Smoyer, Center for Clinical and Translational Research, Nationwide Children's Hospital, Columbus, Ohio.
Andrea Knight, Pediatric Rheumatology, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
Sangeeta Sule, Pediatric Rheumatology, George Washington University, Children's National Medical Center, Washington, DC.
Hanieh Razzaghi, Applied Clinical Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
L Charles Bailey, Applied Clinical Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Susan L. Furth, Pediatrics, Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Christopher B. Forrest, Applied Clinical Research Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Michelle R. Denburg, Pediatrics, Perelman School of Medicine at the University of Pennsylvania, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
Meredith A. Atkinson, Pediatric Nephrology, Johns Hopkins School of Medicine, Baltimore, Maryland.

Document Type

Journal Article

Publication Date

1-1-2022

Journal

Clinical journal of the American Society of Nephrology : CJASN

Volume

17

Issue

1

DOI

10.2215/CJN.07810621

Keywords

PEDSnet; children; health education; learning health system; lupus nephritis; multi-institutional systems; pediatrics; systemic lupus erythematosus

Abstract

BACKGROUND AND OBJECTIVES: Performing adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Electronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of patients with SLE. The highest-performing phenotypes were then evaluated across institutions in PEDSnet, a national health care systems network of >6.7 million children. Reviewers blinded to case status used standardized forms to review random samples of cases (=350) and noncases (=350). RESULTS: Final algorithms consisted of both utilization and diagnostic criteria. For both, utilization criteria included two or more in-person visits with nephrology or rheumatology and ≥60 days follow-up. SLE diagnostic criteria included absence of neonatal lupus, one or more hydroxychloroquine exposures, and either three or more qualifying diagnosis codes separated by ≥30 days or one or more diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 100% (95% confidence interval [95% CI], 99 to 100), specificity was 92% (95% CI, 88 to 94), positive predictive value was 91% (95% CI, 87 to 94), and negative predictive value was 100% (95% CI, 99 to 100). Lupus nephritis diagnostic criteria included either three or more qualifying lupus nephritis diagnosis codes (or SLE codes on the same day as glomerular/kidney codes) separated by ≥30 days or one or more SLE diagnosis codes and one or more kidney biopsy procedure codes. Sensitivity was 90% (95% CI, 85 to 94), specificity was 93% (95% CI, 89 to 97), positive predictive value was 94% (95% CI, 89 to 97), and negative predictive value was 90% (95% CI, 84 to 94). Algorithms identified 1508 children with SLE at PEDSnet institutions (537 with lupus nephritis), 809 of whom were seen in the past 12 months. CONCLUSIONS: Electronic health record-based algorithms for SLE and lupus nephritis demonstrated excellent classification accuracy across PEDSnet institutions.

Department

Pediatrics

Share

COinS