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Integration of cancer registry and electronic health record data to construct a childhood cancer survivorship cohort, facilitate risk stratification for late effects, and assess appropriate follow‐up care
Author(s) -
Noyd David H.,
Neely Nigel B.,
Schroeder Kristin M.,
Lantos Paul M.,
Power Steve,
Kreissman Susan G.,
Oeffinger Kevin C.
Publication year - 2021
Publication title -
pediatric blood and cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.116
H-Index - 105
eISSN - 1545-5017
pISSN - 1545-5009
DOI - 10.1002/pbc.29014
Subject(s) - medicine , cohort , survivorship curve , cancer registry , cancer , retrospective cohort study , medical record , subspecialty , pediatric cancer , cohort study , pediatrics , oncology , family medicine
Background This retrospective study harnessed an institutional cancer registry to construct a childhood cancer survivorship cohort, integrate electronic health record (EHR) and geospatial data to stratify survivors based on late‐effect risk, analyze follow‐up care patterns, and determine factors associated with suboptimal follow‐up care. Procedure The survivorship cohort included patients ≤18 years of age reported to the institutional cancer registry between January 1, 1994 and November 30, 2012. International Classification of Diseases for Oncology, third revision (ICD‐O‐3) coding and treatment exposures facilitated risk stratification of survivors. The EHR was linked to the cancer registry based on medical record number (MRN) to extract clinic visits. Results Five hundred and ninety pediatric hematology‐oncology (PHO) and 275 pediatric neuro‐oncology (PNO) survivors were included in the final analytic cohort. Two hundred and eight‐two survivors (32.6%) were not seen in any oncology‐related subspecialty clinic at Duke 5–7 years after initial diagnosis. Factors associated with follow‐up included age ( p = .008), diagnosis ( p < .001), race/ethnicity ( p = .010), late‐effect risk strata ( p = .001), distance to treatment center ( p < .0001), and area deprivation index (ADI) ( p = .011). Multivariable logistic modeling attenuated the association for high‐risk (OR 1.72; 95% CI 0.805, 3.66) and intermediate‐risk (OR 1.23, 95% CI 0.644, 2.36) survivors compared to survivors at low risk of late effects among the PHO cohort. PNO survivors at high risk for late effects were more likely to follow up (adjusted OR 3.66; 95% CI 1.76, 7.61). Conclusions Nearly a third of survivors received suboptimal follow‐up care. This study provides a reproducible model to integrate cancer registry and EHR data to construct risk‐stratified survivorship cohorts to assess follow‐up care.