Impact of machine learning-directed on-treatment evaluations on cost of acute care visits: Economic analysis of SHIELD-RT.

Conference Paper

1509 Background: SHIELD-RT was a randomized controlled quality improvement study (NCT03775265) that implemented electronic health record-based machine learning (ML) to direct supplemental visits for high risk (HR) patients undergoing radiotherapy (RT). Acute care visits (ER visits or hospitalizations) were reduced from 22% to 12%. We evaluated the costs associated with acute visits in this study. Methods: Patients who initiated RT between 1/7/19 and 6/30/19 at a single institution were evaluated by a ML algorithm to identify HR courses (>10% risk of acute visit during RT). HR patients were randomized to standard weekly (S) or intervention of twice weekly (TW) evaluation during RT. Cost data associated with acute visits were obtained and compared between patients who underwent S or TW evaluations. Missing cost data were imputed using disease related groups (DRGs). Mean costs (standard deviation) were compared between arms with non-parametric Wilcoxon Rank Sum tests. Results: 311 HR courses were identified and randomized to either S (n=157) or TW (n=154) evaluations during RT. 85 patients (S: 51; TW: 34) had 121 distinct acute care visits (S: 74; TW: 47). Patients in the TW evaluation arm had fewer hospitalizations (29 vs 41) and ER visits (18 vs 33) than those in the S arm. There were fewer acute visits per patient in the TW arm (0.34) compared to S arm (0.49). Actual cost data was available for 102 visits at our institution, and imputed for 19 outside hospital visits. Mean cost associated with acute visits was lower in the TW arm ($1939, SD $5912) compared with the S arm ($4002, SD $11568; p=0.03). Differences in mean cost between arms are presented in the table. Conclusions: ML-directed evaluations for HR patients undergoing RT resulted in decreased costs of ER visits and hospitalizations. Costs were decreased across revenue centers, with the largest difference related to inpatient room costs. Future analyses will incorporate intervention costs, which are currently bundled with RT reimbursement.[Table: see text]

Full Text

Duke Authors

Cited Authors

  • Natesan, D; Thomas, SM; Eisenstein, E; Eclov, N; Dalal, N; Stephens, SJ; Malicki, M; Shields, S; Cobb, A; Mowery, YM; Niedzwiecki, D; Tenenbaum, J; Palta, M; Hong, JC

Published Date

  • May 20, 2021

Published In

Volume / Issue

  • 39 / 15_suppl

Start / End Page

  • 1509 - 1509

Published By

Electronic International Standard Serial Number (EISSN)

  • 1527-7755

International Standard Serial Number (ISSN)

  • 0732-183X

Digital Object Identifier (DOI)

  • 10.1200/jco.2021.39.15_suppl.1509