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Hospital Bed Capacity Influences Patient Charges in Outpatient Robotic Total Knee Arthroplasty: A Propensity-Matched
Monica Misch1, Reza Katanbaf1, Chase W Smitterberg1
1The Rubin Institute for Advanced Orthopedics, Lifebridge Health, Sinai Hospital of Baltimore, Baltimore, MD, USA.
Background:
The rise of robotic-assisted total knee arthroplasty (RA-TKA) surgeries has correlated with increased outpatient procedures aimed at improving efficiency and outcomes. However, patient charges vary widely due to differences in reimbursement structures, resource utilization, and the higher supply costs associated with robotics. Little is known about the impact of institutional characteristics, specifically hospital bed capacity, limiting understanding of charge variability and cost-control strategies. This study aims to examine whether hospital size affects patient charges for RA-TKA, focusing on (1) total charges and (2) operating room (OR) charges.
Methods:
Outpatient RA-TKA cases from January 1, 2017, to December 31, 2021, were identified from a national database. Hospitals were categorized by bed capacity: <300 beds and ≥ 300 beds. A 1:1 propensity score match controlled for demographics, clinical characteristics, and insurance status, resulting in 464 patients per group. Outcomes included total patient charges and OR (anesthesia, OR block time, and postanesthesia care) charges. Statistical analyses included Chi-square tests and independent t-test, with P < .05 considered significant.
Results:
Hospitals with ≥300 beds showed significantly higher mean total charges ($65,315.6) compared to hospitals with <300 beds ($53,427.5) (P < .001). Mean OR charges were also elevated in larger hospitals ($30,367.2) vs smaller hospitals ($26,000.0) (P < .001).
Conclusions:
Larger hospitals were associated with significantly higher total and OR patient charges for robotic RA-THA, even after matching for clinical and insurance-related factors. These findings suggest that hospital size may be associated with variation in charge profiles beyond patient and payer characteristics.