Increased Healthcare Utilization and Differential Outcomes for Pediatric Cancer Versus Non-Cancer Patients
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Yujie Chen1, Martin Yi1, Catherine C Aftandilian2
1Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada.
Background:
The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) is a data standard that enables multicenter research. Primary objective was to describe the magnitude of healthcare utilization in pediatric cancer versus non-cancer patients. Secondary objective was to compare 6-month clinical outcomes related to abnormal lab tests and mortality.
Methods:
In this multicenter retrospective study, we included pediatric patients 0-18 years at first medication administration. Cancer patients had a malignant neoplastic disease diagnosis and received chemotherapy. Index date was the first chemotherapy date. Non-cancer patients were assigned analogous index dates based on randomly sampled first medication to chemotherapy intervals. Outcomes were measured within 6 months of index date. Healthcare utilization included encounters, procedures, radiology, lab tests, and medications.
Results:
Among 2810 cancer and 11,240 non-cancer patients, all evaluated healthcare utilization measures were significantly more common in cancer patients. The largest relative differences were observed for long inpatient stay (risk ratio [RR] 26.32, 95% confidence interval [CI] 15.00-46.17), computed tomography (RR 23.59, 95% CI 19.24-28.92), blood culture (RR 37.04, 95% CI 9.58-143.14), and intravenous medication (RR 17.69, 95% CI 8.75-35.75). Death within 6 months was higher for cancer versus non-cancer patients (RR 38.37, 95% CI 12.91-114.04).
Conclusions:
Using the OMOP CDM, we found greater healthcare utilization and worse clinical outcomes among pediatric cancer patients than non-cancer patients, with the largest relative differences observed for inpatient stay, computed tomography, blood culture, and intravenous medication. These findings provide insight into resource utilization patterns and illustrate the OMOP CDM research potential for multicenter studies.
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