3.9 Article

Can Chemotherapy-Related Acute Care Visits Be Accurately Identified in Administrative Data?

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JOURNAL OF ONCOLOGY PRACTICE
卷 14, 期 1, 页码 40-+

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AMER SOC CLINICAL ONCOLOGY
DOI: 10.1200/JOP.2017.023697

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  1. Institute for Clinical Evaluative Sciences - Ontario Ministry of Health and Long-Term Care
  2. Cancer Care Ontario
  3. Ontario Institute for Cancer Research

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Purpose There is increasing interest in using administrative data to examine treatment-related complications that lead to emergency department (ED) visits or hospitalizations (H). The purpose of this study was to evaluate the reliability of billing codes for identifying chemotherapy-related acute care visits (CRVs) among women with early-stage breast cancer. Materials and Methods The cohort was identified by using deterministically linked health databases and consisted of women who were diagnosed with early-stage breast cancer who started adjuvant chemotherapy between 2007 and 2009 in Ontario, Canada. A random sample of 496 patient cases was chosen as the validation cohort. Sensitivity (SN) and specificity (SP) were calculated for three scenarios: chemotherapy-related ED visit, chemotherapy-related H, and febrile neutropenia (FN)-related visit. For FN-related visits, three definitions were considered: general, moderate, and strict. Results The administrative cohort consisted of 8,359 patients, 43.4% of whom had at least one ED or H, including 1,496 women who had multiple visits that resulted in 6,293 unique visits. Of these, 73.1% were considered CRVs. The algorithm performed well in identifying CRVs that included H either from ED (SN, 90%; SP, 100%) or directly from home (SN, 91%; SP, 93%), but less well for ED visits that did not result in H (SN, 65%; SP, 80%). Depending on which FN algorithm was used, 4.8% to 24% of visits were considered related. The moderate FN algorithm provided the best tradeoff between SN (69% to 97%) and SP (83% to 98%). Conclusion Administrative data can be valuable in evaluating chemotherapy-related serious events. Algorithm validation in other cohorts is needed.

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