Presentation Details
| Implementation of an Automated Risk-Based Perioperative Triage Tool in a Large Health System: A Quality Improvement Initiative Kenneth C.Cummings1, Maureen Keshock1, Preethi Patel1, Mar-Qilia Kelly1, Stewart Richardson2, Scott Greenwald2, Necolia Huisman1, Angela Angelo1, Nassib Chamoun2. 1Cleveland Clinic, Cleveland, OH, USA.2Health Data Analytics Institute, Dedham, MA, USA |
Abstract
BACKGROUND: Resource allocation is critical to perioperative care. Many institutions create preoperative questionnaires for patient triage. Our existing questionnaire is seldom used despite many efforts. Therefore, an accurate, automated, and streamlined perioperative triage approach is needed. Previously, patients deemed high risk after chart review would be rescheduled to see a hospitalist preoperatively. This process is not sustainable. Conversely, healthy patients are often scheduled for unnecessary in-person preoperative visits, unnecessarily increasing costs. We implemented a risk stratification platform using validated risk models (1). These models use administrative data, patient demographics, and the proposed procedure to predict risks for outcomes such as mortality, length of stay, and readmission.
METHODS: Patients are stratified into 4 groups using a composite of mortality and readmission risks (Table 1). This allows tailored intensity of optimization and identifies patients who should receive postoperative hospitalist care. The central scheduling team contacts patients to make the appropriate appointment based on risk group. A pilot involving orthopedic procedures at our community hospitals triaged patients to in-person versus virtual visits based on this risk stratification process. An economic analysis was conducted to estimate the impact of such a change in practice.
RESULTS: The pilot ran from March 31 through May 31, 2025. Data from a total of 1,975 patients presenting prior to elective orthopedic surgery in our network of community hospitals was collected for analysis. Using this risk stratification process, the virtual visit percentage increased from a baseline of 10% to 29% (Table 1), although many more patients were eligible. With an average cost difference of $98 per patient (in favor of virtual visits), projected economic impact is presented in Table 2.
CONCLUSIONS: Automated identification of high- and low-risk patients is possible, facilitating perioperative triage. It increases access to care for higher-risk patients and provides cost savings in low-risk patients. A large opportunity still exists to expand virtual care.
No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author.
METHODS: Patients are stratified into 4 groups using a composite of mortality and readmission risks (Table 1). This allows tailored intensity of optimization and identifies patients who should receive postoperative hospitalist care. The central scheduling team contacts patients to make the appropriate appointment based on risk group. A pilot involving orthopedic procedures at our community hospitals triaged patients to in-person versus virtual visits based on this risk stratification process. An economic analysis was conducted to estimate the impact of such a change in practice.
RESULTS: The pilot ran from March 31 through May 31, 2025. Data from a total of 1,975 patients presenting prior to elective orthopedic surgery in our network of community hospitals was collected for analysis. Using this risk stratification process, the virtual visit percentage increased from a baseline of 10% to 29% (Table 1), although many more patients were eligible. With an average cost difference of $98 per patient (in favor of virtual visits), projected economic impact is presented in Table 2.
CONCLUSIONS: Automated identification of high- and low-risk patients is possible, facilitating perioperative triage. It increases access to care for higher-risk patients and provides cost savings in low-risk patients. A large opportunity still exists to expand virtual care.
No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, including photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author.
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