Ramkumar Prem N, Navarro Sergio M, Haeberle Heather S, Ricchetti Eric T, Iannotti Joseph P
Department of Orthopedic Surgery, Cleveland Clinic, Cleveland, OH, USA.
Department of Orthopaedic Surgery, Baylor College of Medicine, Houston, TX, USA.
J Shoulder Elbow Surg. 2017 Aug;26(8):1399-1406. doi: 10.1016/j.jse.2017.05.019.
Whereas several studies suggest that high-volume surgeons and hospitals deliver superior patient outcomes with greater cost efficiency, no evidence-based thresholds separating high-volume surgeons and hospitals from those that are low or medium volume exist in shoulder arthroplasty. The objective of this study was to establish meaningful thresholds that take outcomes and cost into consideration for surgeons and hospitals performing shoulder arthroplasty.
Using 9546 patients undergoing primary shoulder arthroplasty for osteoarthritis from an administrative database, we created and applied 4 models using stratum-specific likelihood ratio (SSLR) analysis of a receiver operating characteristic (ROC) curve. We generated 4 sets of thresholds predictive of adverse outcomes, namely, increased length of stay (LOS) and increased cost for both surgeon and hospital volume.
SSLR analysis of the 4 ROC curves by surgeon volume produced 3 volume categories. LOS and cost by annual shoulder arthroplasty surgeon volume produced the same strata: 0-4 (low), 5-14 (medium), and 15 or more (high). LOS and cost by annual shoulder arthroplasty hospital volume produced the same strata: 0-3 (low), 4-14 (medium), and 15 or more (high). LOS and cost decreased significantly (P < .05) in progressively higher volume categories.
Our study validates economies of scale in shoulder arthroplasty by demonstrating a direct relationship between volume and value through SSLR analysis of ROC curves for risk-based volume stratification using meaningful volume definitions for low-, medium-, and high-volume surgeons and hospitals. The described volume-value relationship offers patients, surgeons, hospitals, and other stakeholders meaningful thresholds for the optimal delivery of shoulder arthroplasty.
尽管多项研究表明，手术量大的外科医生和医院能以更高的成本效益提供更优的患者治疗效果，但在肩关节置换术中，尚无基于证据的阈值来区分手术量大的外科医生和医院与手术量低或中等的医生和医院。本研究的目的是建立有意义的阈值，将手术效果和成本纳入接受肩关节置换术的外科医生和医院的考量范围。
利用行政数据库中9546例因骨关节炎接受初次肩关节置换术的患者，我们创建并应用了4种模型，使用受试者工作特征（ROC）曲线的分层特定似然比（SSLR）分析。我们生成了4组预测不良结果的阈值，即住院时间延长（LOS）以及外科医生和医院手术量增加导致的成本增加。
按外科医生手术量对4条ROC曲线进行SSLR分析产生了3个手术量类别。每年肩关节置换术外科医生手术量的LOS和成本产生了相同的分层：0 - 4（低）、5 - 14（中）和15及以上（高）。每年肩关节置换术医院手术量的LOS和成本产生了相同的分层：0 - 3（低）、4 - 14（中）和15及以上（高）。在手术量逐渐增加的类别中，LOS和成本显著降低（P < 0.05）。
我们的研究通过对ROC曲线进行SSLR分析，为低、中、高手术量的外科医生和医院使用有意义的手术量定义进行基于风险的手术量分层，证明了手术量与价值之间的直接关系，从而验证了肩关节置换术中的规模经济。所描述的手术量 - 价值关系为患者、外科医生、医院和其他利益相关者提供了肩关节置换术最佳实施的有意义阈值。
