Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL.
Department of Surgery, OnetoMap Analytics, University of South Florida Morsani College of Medicine, Tampa, FL.
Surgery. 2024 Oct;176(4):1123-1130. doi: 10.1016/j.surg.2024.06.018. Epub 2024 Jul 14.
The cost-to-charge ratio reflects the markup of hospital services. A lower cost-to-charge ratio indicates lower costs and/or greater charges. This study examines factors associated with cost-to-charge ratio trends to determine whether decreasing cost-to-charge ratio is associated with worse surgical outcomes.
The Florida Agency for Healthcare Administration Inpatient database (2018-2020) was queried for common surgical procedures and linked to the Distressed Communities Index, RAND Corporation Hospital data, Center for Medicare Services Cost Reports, and American Hospital Association data. Only hospitals with monotonically increasing or decreasing cost-to-charge ratio were included in the study. Univariable analysis compared these hospitals. Using patient-level data, interpretable machine learning predicted cost-to-charge ratio trend while identifying influential factors.
The cohort had 67 hospitals (27 increasing cost-to-charge ratio and 40 decreasing cost-to-charge ratio) with 35,661 surgeries. Decreasing cost-to-charge ratio hospitals were more often proprietarily owned (78% vs 33%, P = .01) and had greater mean total charges ($134,349 ± $114,510 vs $77,185 ± $82,027, P < .01) with marginally greater mean estimated costs ($14,863 ± $12,343 vs $14,458 ± $15,440, P < .01). Patients from decreasing cost-to-charge ratio hospitals had greater rates of most comorbidities (P < .05) but no difference in mortality or overall complications. Machine-learning models revealed charges rather than clinical factors as most influential in cost-to-charge ratio trend prediction.
Decreasing cost-to-charge ratio hospitals charge vastly more despite minimally greater estimated costs and no difference in outcomes. Although differences in case-mix existed, charges were the predominant differentiators. Patient clinical factors had far less of an impact.
成本与收费比率反映了医院服务的加价情况。较低的成本与收费比率表明成本较低或收费较高。本研究探讨了与成本与收费比率趋势相关的因素，以确定成本与收费比率的降低是否与手术结果恶化有关。
佛罗里达州医疗管理局住院患者数据库（2018-2020 年）被查询了常见的手术程序，并与困境社区指数、兰德公司医院数据、医疗保险服务成本报告和美国医院协会数据相关联。只有成本与收费比率呈单调递增或递减的医院才被纳入研究。单变量分析比较了这些医院。使用患者层面的数据，可解释的机器学习预测了成本与收费比率的趋势，同时确定了有影响力的因素。
该队列共有 67 家医院（27 家成本与收费比率递增，40 家成本与收费比率递减），共进行了 35661 例手术。成本与收费比率递减的医院更有可能是私营所有（78%比 33%，P=.01），且平均总收费更高（$134349±$114510 比 $77185±$82027，P<.01），平均估计成本也略高（$14863±$12343 比 $14458±$15440，P<.01）。来自成本与收费比率递减医院的患者更常见大多数合并症（P<.05），但死亡率或总体并发症无差异。机器学习模型显示，收费而不是临床因素对成本与收费比率趋势预测的影响最大。
尽管估计成本略有增加，但成本与收费比率递减的医院收费要高得多，而结果却没有差异。尽管病例组合存在差异，但收费是主要的区别因素。患者的临床因素影响要小得多。
