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Aligning EHR Data for Pediatric Leukemia With Standard Protocol Therapy
Author(s) -
Nicole M. Wood,
Sierra Davis,
Karen Lewing,
Janelle NoelMacDonnell,
Earl F. Glynn,
Doina Caragea,
Mark A. Hoffman
Publication year - 2021
Publication title -
jco clinical cancer informatics
Language(s) - English
Resource type - Journals
ISSN - 2473-4276
DOI - 10.1200/cci.20.00144
Subject(s) - medicine , protocol (science) , guideline , cog , milestone , cohort , medical physics , electronic health record , health care , computer science , alternative medicine , pathology , archaeology , artificial intelligence , economics , history , economic growth
PURPOSE Children with acute lymphoblastic leukemia (ALL) are treated according to risk-based protocols defined by the Children's Oncology Group (COG). Alignment between real-world clinical practice and protocol milestones is not widely understood. Aggregate deidentified electronic health record (EHR) data offer a useful resource to evaluate real-world clinical practice.METHODS A cohort of children with ALL was identified in the Cerner Health Facts deidentified aggregate EHR data. Manual review identified candidate procedural milestones. Automated methods were developed to classify likely standard-risk precursor B-cell ALL patients. Milestone procedures were adjusted relative to initiation of therapy and then aligned to the COG protocols for standard induction therapy.RESULTS We identified 7,728 patients with pediatric ALL with 188,187 encounters. Records for lumbar punctures (LP) and bone marrow biopsies were frequently present in the data and were appropriate targets to evaluate guideline performance. Alluvial graph analysis of 14 health systems indicated that none of the systems have data from all three COG-recommended lumbar procedures for all patients but alignment demonstrated that most systems test at the recommended times.CONCLUSION Source-system variation introduces inconsistency and incompleteness into aggregate EHR data. Data visualization was helpful in characterizing and interpreting the data. Health systems with patients meeting the inclusion criteria demonstrated strong alignment with the recommended milestones for LP. Large-scale aggregate EHR data are useful to evaluate alignment of recommended versus actual clinical milestones in support of treating children with ALL. This work can inform other guideline and protocol driven care.

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