Elevated Length of Stay and Cost of Orthopedic Hospitalization are Associated with Urban Setting, Non-Trauma Diagnosis, and Medicare Enrollment

骨科住院时间延长和费用增加与城市环境、非创伤性诊断和医疗保险参保有关。

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Abstract

PURPOSE: Disparities in orthopedic care delivery across hospital settings and payer types may significantly correlate with length of stay (LOS), cost burden, and care efficiency. This study quantifies the associations between geographic location, case acuity, insurance status and resource utilization in Michigan. METHODS: We conducted a retrospective cohort study using 2018-2020 discharge records from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Database (SID) for Michigan. Orthopedic-related hospitalizations were identified and stratified by hospital location (urban vs rural), injury mechanism (trauma vs non-trauma), and primary payer (Medicare, Medicaid, private, other, uninsured). Outcomes included LOS, per-discharge cost, aggregate hospital-level expenditures, and population-adjusted discharge rates. Statistical comparisons were performed using two-sample t-tests and ANOVA. Independent associations were evaluated via mixed-effects regression models with hospital-level random intercepts. RESULTS: Among 334,756 orthopedic discharges, urban facilities recorded longer average LOS (4.57 vs 4.09 days; P<0.001) and higher mean aggregate costs per hospital ($8.70M vs $1.74M; P<0.001) than rural counterparts. Non-traumatic cases were associated with greater per-stay costs ($19,645 vs $16,630; P<0.001). Uninsured patients experienced the longest LOS (4.70 days), followed by Medicare (4.35 days), Medicaid (3.89 days), private (3.72 days), and other (3.06 days; all P<0.001). Medicare accounted for the largest hospital-level expenditure ($3.28M mean; P<0.001). Mixed-effects models confirmed urban setting, non-trauma diagnosis, and Medicare enrollment as independent factors associated with elevated LOS and cost (P<0.001). CONCLUSION: Orthopedic care patterns demonstrate distinct variations linked to structural, clinical, and financial factors. These findings highlight disparities that may inform future discussions on reimbursement policies and rural capacity planning.

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