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美国大陆机器人脊柱手术可及性的地理和社会经济差异:一项横断面生态分析。

Geographic and Socioeconomic Disparities in Robotic Spine Surgery Access in the Continental United States: A Cross-Sectional Ecological Analysis.

作者信息

Mastrokostas Paul G, Mastrokostas Leonidas E, Emara Ahmed K, Dalton Jonathan, Narayanan Rajkishen, Kepler Christopher K, Hilibrand Alan S, Vaccaro Alexander R, Bou Monsef Jad, Razi Afshin E, Ng Mitchell K

机构信息

Department of Orthopaedic Surgery, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.

Department of Orthopaedic Surgery, Maimonides Medical Center, Brooklyn, NY, USA.

出版信息

Global Spine J. 2025 Jun 24:21925682251356218. doi: 10.1177/21925682251356218.

Abstract

Study DesignCross-sectional ecological analysis.ObjectivesThis study aims to assess the availability of robotic spine surgery across the United States and identify disparities in access.MethodsWe utilized provider-finding functions from major medical equipment manufacturers to identify robotic spine surgeons and categorized affiliated hospitals. Geospatial analyses combined with socioeconomic indicators, Rural-Urban Continuum Codes, and the Area Deprivation Index (ADI) provided insights into access disparities. Multivariate logistic regression and Student's t-tests were used to identify county-level variables associated with hotspots and coldspots. Statistical significance was set at the < .05 level.ResultsNinety-one robotic spine surgeons were identified. Robotic spine surgeons were predominantly affiliated with nonteaching hospitals (50.55%), followed by minor teaching (38.46%) and major teaching (10.99%) hospitals. Access hotspots are in the Northeast and Southeast, with rural areas showing 22% lower odds of being hotspots (OR = 0.78, < .001). Factors increasing the odds of being a hotspot include higher disability prevalence (OR = 1.19, < .001), lack of insurance (OR = 1.18, < .001), and older median age (OR = 1.17, < .001). Educational attainment and ADI, despite being significant, had lower predictive values for access.ConclusionsDisparities in access to robotic spine surgery are associated with socioeconomic, demographic, and geographic factors. The concentration of surgeons in nonteaching hospitals and higher-income areas may reflect market dynamics. Efforts to improve access should consider regional resources, hospital type, and community disadvantage.

摘要

研究设计

横断面生态分析。

目的

本研究旨在评估美国各地机器人脊柱手术的可及性,并确定可及性方面的差异。

方法

我们利用主要医疗设备制造商的供应商查找功能来识别机器人脊柱外科医生,并对附属医院进行分类。地理空间分析结合社会经济指标、城乡连续体代码和地区贫困指数(ADI),为可及性差异提供了见解。多变量逻辑回归和学生t检验用于识别与热点和冷点相关的县级变量。统计学显著性设定为P <.05水平。

结果

共识别出91名机器人脊柱外科医生。机器人脊柱外科医生主要隶属于非教学医院(50.55%),其次是小型教学医院(38.46%)和大型教学医院(10.99%)。可及性热点地区位于东北部和东南部,农村地区成为热点的几率低22%(OR = 0.78,P <.001)。增加成为热点几率的因素包括较高的残疾患病率(OR = 1.19,P <.001)、缺乏保险(OR = 1.18,P <.001)和较高的年龄中位数(OR = 1.17,P <.001)。尽管教育程度和ADI具有显著性,但对可及性的预测价值较低。

结论

机器人脊柱手术可及性的差异与社会经济、人口统计学和地理因素有关。外科医生集中在非教学医院和高收入地区可能反映了市场动态。改善可及性的努力应考虑区域资源、医院类型和社区劣势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d442/12187716/50f6d8edb670/10.1177_21925682251356218-fig1.jpg

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