Key result
Claims data algorithm detects severe post-op GI cancer complications with ~100% sensitivity.
Why the study?
Determining the presence of postoperative complications is complex, prompting evaluation of the accuracy of extracting GI cancer surgery patients and complications from Japanese administrative claims data.
Can an algorithm using Japanese administrative claims data accurately identify patients and postoperative complications requiring interventions after GI cancer surgery compared to chart review?
Observational (n=2,366)
Yes
Can an algorithm using Japanese administrative claims data accurately identify patients and postoperative complications requiring interventions after GI cancer surgery compared to chart review?
Administrative claims data can accurately identify patients and severe postoperative complications requiring interventions after GI cancer surgery.
Answers are grounded in this paper and cite their sources.
Supports claims-based identification of severe post-GI cancer complications for research; leaves open external validation and generalizability.
Background: Recently, real-world data have been recognized to have a significant role for research and quality improvement worldwide. The decision on the existence or nonexistence of postoperative complications is complex in clinical practice. This multicenter validation study aimed to evaluate the accuracy of identification of patients who underwent gastrointestinal (GI) cancer surgery and extraction of postoperative complications from Japanese administrative claims data. Methods: We compared data extracted from both the Diagnosis Procedure Combination (DPC) and chart review of patients who underwent GI cancer surgery from April 2016 to March 2019. Using data of 658 patients at Kyoto University Hospital, we developed algorithms for the extraction of patients and postoperative complications requiring interventions, which included an invasive procedure, reoperation, mechanical ventilation, hemodialysis, intensive care unit management, and in-hospital mortality. The accuracy of the algorithms was externally validated using the data of 1708 patients at two other hospitals. Results: In the overall validation set, 1694 of 1708 eligible patients were correctly extracted by DPC (sensitivity 0.992 and positive predictive value 0.992). All postoperative complications requiring interventions had a sensitivity of >0.798 and a specificity of almost 1.000. The overall sensitivity and specificity of Clavien-Dindo ≥grade IIIb complications was 1.000 and 0.995, respectively. Conclusion: Patients undergoing GI cancer surgery and postoperative complications requiring interventions can be accurately identified using the real-world data. This multicenter external validation study may contribute to future research on hospital quality improvement or to a large-scale comparison study among nationwide hospitals using real-world data.
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Kinoshita et al. (2023) conducted an observational in Gastrointestinal cancer surgery (n=2,366). Diagnosis Procedure Combination (DPC) administrative claims data algorithm vs. Chart review was evaluated on Identification of patients and extraction of postoperative complications requiring interventions. An algorithm using Japanese administrative claims data accurately identified Clavien-Dindo ≥grade IIIb complications after GI cancer surgery with 1.000 sensitivity and 0.995 specificity.
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