Department of Plastic and Reconstructive Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH.
Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH; National Clinician Scholars Program at the Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI.
J Hand Surg Am. 2021 Sep;46(9):731-739.e5. doi: 10.1016/j.jhsa.2021.04.011. Epub 2021 Jun 18.
Digit replantation can improve dexterity, functionality, patient satisfaction, and pain following amputation, but rates continue to fall nationally. This study aimed to describe the effects of travel time and distance as barriers to high-volume hospitals, identify geospatial inefficiencies in the presentation of patients to replantation care, and provide an optimal allocation model in which cases are redistributed to select centers to reduce geospatial redundancies and optimize outcomes.
We reviewed the California Office of Statewide Health Planning and Development hospital discharge database to identify cases of digital amputation and determine outcomes of replantation. Using residential zip codes, risk- and reliability-adjusted multivariable logistic regression was used to assess the relationship of hospital volume and travel time on replantation success. Geospatial analysis assessed the travel burden of patients as they presented for care, and optimal allocation modeling was used to create a model of centralization.
We identified 5,503 patients during the study period; 1,060 underwent replantation with an overall success rate of 70.2%. Ninety-three hospitals were found to perform replantations, of which only 4 were identified as high-volume hospitals. Patients routinely traveled farther to reach high-volume hospitals, and decreasing the travel time predicted a 15% increase in odds of replantation at a low-volume center. Twenty-one percent of patients presented to a low-volume hospital when a high-volume hospital was closer, and differencein payer type and race/ethnicity existed between those who presented to the closest center compared to those who bypassed high-volume centers. The optimal allocation modeling allocated all cases into 8 centers, which increased the median annual volume from 1 case to 9.6 cases and decreased patient travel time.
Travel burden and geospatial inefficiencies serve as barriers to high-quality and high-volume replantation services. Optimized allocation of digital replantation cases into high-quality centers can decrease travel times, increase annual volumes, and potentially improve replantation outcomes.
TYPE OF STUDY/LEVEL OF EVIDENCE: Economic/Decision Analysis III.
断指再植可以提高截肢后的灵活性、功能性、患者满意度和减轻疼痛，但全国的再植率仍在持续下降。本研究旨在描述旅行时间和距离作为通往高容量医院的障碍的影响，确定患者接受再植护理的地理空间效率低下，并提供一个最佳分配模型，通过该模型将病例重新分配到选定的中心，以减少地理空间冗余并优化结果。
我们查阅了加利福尼亚州全州卫生规划和发展办公室的医院出院数据库，以确定数字截肢病例，并确定再植的结果。使用居住邮政编码，采用风险和可靠性调整的多变量逻辑回归来评估医院数量和旅行时间对再植成功率的关系。地理空间分析评估了患者就诊时的旅行负担，最优分配模型用于创建集中化模型。
在研究期间，我们共确定了 5503 名患者；其中 1060 名患者接受了再植手术，总体成功率为 70.2%。发现有 93 家医院进行了再植手术，其中只有 4 家被确定为高容量医院。患者通常需要更远的距离才能到达高容量医院，而且减少旅行时间预测在低容量中心进行再植的几率会增加 15%。21%的患者在距离更近的低容量医院就诊时，选择最近的中心就诊的患者和绕过高容量中心的患者之间存在不同的支付类型和种族/民族差异。最优分配模型将所有病例分配到 8 个中心，将中位数年病例量从 1 例增加到 9.6 例，并减少了患者的旅行时间。
旅行负担和地理空间效率低下是高质量和高容量再植服务的障碍。将数字再植病例优化分配到高质量中心可以减少旅行时间、增加年度数量，并有可能改善再植结果。
研究类型/证据水平：经济/决策分析 III 级。
