Artificial Intelligence Predicts Cost After Ambulatory Anterior Cruciate Ligament Reconstruction

Identifying Modifiable Cost Drivers of Outpatient Unicompartmental Knee Arthroplasty With Machine Learning

BACKGROUND

Implementing tools that identify cost-saving opportunities for ambulatory orthopaedic surgeries can improve access to value-based care. We developed and internally validated a machine learning (ML) algorithm to predict cost drivers of total charges after ambulatory unicompartmental knee arthroplasty (UKA).

METHODS

We queried the New York State Ambulatory Surgery and Services database to identify patients who underwent ambulatory, defined as <24 hours of care before discharge, elective UKA between 2014 and 2016. A total of 1,311 patients were included. The median costs after ambulatory UKA were $14,710. Patient demographics and intraoperative parameters were entered into 4 candidate ML algorithms. The most predictive model was selected following internal validation of candidate models, with conventional linear regression as a benchmark. Global variable importance and partial dependence curves were constructed to determine the impact of each input parameter on total charges.

RESULTS

The gradient-boosted ensemble model outperformed all candidate algorithms and conventional linear regression. The major differential cost drivers of UKA identified (in decreasing order of magnitude) were increased operating room time, length of stay, use of regional and adjunctive periarticular analgesia, utilization of computer-assisted navigation, and routinely sending resected tissue to pathology.

CONCLUSION

We developed and internally validated a supervised ML algorithm that identified operating room time, length of stay, use of computer-assisted navigation, regional primary anesthesia, adjunct periarticular analgesia, and routine surgical pathology as essential cost drivers of UKA. Following external validation, this tool may enable surgeons and health insurance providers optimize the delivery of value-based care to patients receiving outpatient UKA.

LEVEL OF EVIDENCE

III.

Ambulatory Surgery Centers Significantly Decrease Total Health Care Expenditures in Primary Anterior Cruciate Ligament Reconstruction

BACKGROUND

Anterior cruciate ligament reconstruction (ACLR) is a commonly performed orthopaedic procedure. The volume and cost of ACLR procedures are increasing annually, but the drivers of these cost increases are not well described.

PURPOSE

To analyze the modifiable drivers of total health care utilization (THU), immediate procedure reimbursement, and surgeon reimbursement for patients undergoing ACLR using a large national commercial insurance database from 2013 to 2017.

STUDY DESIGN

Descriptive epidemiology study.

METHODS

For this study, the cohort consisted of patients identified in the MarketScan Commercial Claims and Encounters database who underwent outpatient arthroscopic ACLR in the United States from 2013 to 2017. Patients with Current Procedural Terminology code 29888 were included. THU was defined as the sum of any payment related to the ACLR procedure from 90 days preoperatively to 180 days postoperatively. A multivariable model was utilized to describe the patient- and procedure-related drivers of THU, immediate procedure reimbursement, and surgeon reimbursement.

RESULTS

There were 34,862 patients identified. On multivariable analysis, the main driver of THU and immediate procedure reimbursement was an outpatient hospital as the surgical setting (US$6789 increase in THU). The main driver of surgeon reimbursement was an out-of-network surgeon (US$1337 increase). Health maintenance organization as the insurance plan type decreased THU, immediate procedure reimbursement, and surgeon reimbursement (US$955, US$108, and US$38 decrease, respectively, compared with preferred provider organization; P < .05 for all).

CONCLUSION

Performing procedures in more cost-efficient ambulatory surgery centers had the largest effect on decreasing health care expenditures for ACLR. Health maintenance organizations aided in cost-optimization efforts as well, but had a minor effect on surgeon reimbursement. Overall, this study increases transparency into what drives reimbursement and serves as a foundation for how to decrease health care expenditures related to ACLR.