The University of Oklahoma Health Sciences Center, Oklahoma City, OK
David H Noyd , Amanda Janitz , Ashley Baker , William Beasley , Nancy Etzold , David Kendrick , Kevin C. Oeffinger
Background: Marked improvements in outcomes for children with cancer and robust cohort studies with longitudinal follow-up inform evidence-based guidelines for survivors at risk for late cardiomyopathy. Clinical informatics tools to integrate data from multiple sources have the potential to catalyze population health management. Methods: The Oklahoma Childhood Cancer Survivor cohort was constructed from an institutional cancer registry of survivors diagnosed between 2005 and 2014 (n=382). Data elements (cumulative anthracycline, cumulative chest-directed radiotherapy, alkylator, and platinum exposures) were extracted from Passport for Care (PFC) to implement previously validated late cardiovascular risk prediction modeling from the Childhood Cancer Survivor Study (CCSS) for cardiomyopathy. Risk groups were compared to the Children’s Oncology Group (COG) Long-Term Follow-up Guidelines. Standard query language facilitated extraction of echocardiogram data from the electronic health record to determine adherence, defined as an echocardiogram within 27 months and 63 months from the last day of therapy for high and moderate risk survivors, respectively. Results: Sixty-nine percent (n=264) of survivors from the cancer registry were documented in PFC, of whom 29%, 56%, and 15% were classified as low, moderate, high risk, respectively, based on the CCSS late cardiomyopathy risk calculator. Concordance was modest for high and moderate risk groups (Kappa = 0.42 and 0.46, respectively) and good for the low risk group (Kappa = 0.77) compared to COG risk groups. There was excellent adherence to echocardiogram guidelines with 93% and 81% of moderate and high-risk survivors, respectively. There were significant differences based on risk group (p=0.02) and age at diagnosis (p<0.01). Conclusions: Clinical informatics tools represent a feasible approach to leverage discrete data elements regarding key treatment exposures from PFC to successfully implement previously validated late cardiovascular risk prediction models on a population health level. PFC promotes adherence to echocardiogram surveillance and serves as a platform for future interoperability to generate real-world data to improve survivorship-focused care.
Adherence | P-Value | ||
---|---|---|---|
Yes | No | ||
Total | 233 (88%) | 32 (12%) | |
COG Guideline Every 5 Years Every 2 Years | 167 (72%) 64(28%) | 15 52%) 14 (48%) | 0.02 |
Age, in years (SE) | 6.7 (0.4) | 10.6 (1.2) | <0.01 |
Adolescent at Diagnosis Yes No | 46 (20%) 185 (80%) | 15 (52%) 14 (48%) | <0.01 |
Sex Male Female | 126 (55%) 105 (45%) | 16 (55%) 13 (45%) | 0.95 |
Race White, Non-Hispanic Black, Non-Hispanic Hispanic American Indian Other | 145 (63%) 20 (9%) 38 (16%) 18 (8%) 10 (4%) | 20 (69%) 2 (7%) 5 (17%) 0 (0%) 2 (7%) | 0.58 |
RUCA Urban Large Town Small Town/Isolated Rural | 158 (69%) 33 (14%) 39 (17%) | 17 (61%) 5 (18%) 6 (21%) | 0.69 |
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Abstract Disclosures
Funded by Conquer Cancer
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