Jin Alan, Chinta Ravi, Raghavan Vijay
Xavier University.
University of District of Columbia.
Hosp Top. 2025 Apr-Jun;103(2):64-71. doi: 10.1080/00185868.2023.2185172. Epub 2023 Feb 28.
The significant and apparent variance in hospital charges and inpatient care in the U.S. has perplexed the general public including many stakeholders such as the healthcare regulators and insurers. While the clinical side of inpatient care has been undergoing tremendous progress and standardization, the overall cost of healthcare has been ballooning. The purpose of this research is to conduct statistical analyses that reveal the sources of variance in hospital charges and inpatient care using the annual data from the AHRQ's (Agency for Healthcare Research and Quality) HCUP's (Hospital Cost and Utilization Project) NIS (National Inpatient Sample) database. Our focus is on non-clinical factors such as patient age, gender, income and race and hospital location data as independent variables to investigate their impact on hospital charges and inpatient care. Our research sample is the liver transplant cases in 2019 sampled in the NIS 2019 database. Our regression results show patient age and gender as well as payer affect the number of diagnoses; and hospital charges are affected by age, payer and hospital location. Number of procedures was not affected by any of these non-clinical factors except the hospital location. Implications suggest that there is more room for standardization of the number of diagnoses and procedures across regions in the US. Results also reveal that race and income do not have any effect on hospital charges and inpatient care. Our study contributes to an empirical understanding of non-clinical factors in the explanation of variance in hospital charges and inpatient care.
美国医院收费和住院护理方面存在显著且明显的差异,这让包括医疗监管机构和保险公司等众多利益相关者在内的普通公众感到困惑。虽然住院护理的临床方面一直在取得巨大进展并实现标准化,但医疗保健的总体成本却一直在飙升。本研究的目的是进行统计分析,利用美国医疗保健研究与质量局(AHRQ)的医院成本与利用项目(HCUP)的国家住院样本(NIS)数据库中的年度数据,揭示医院收费和住院护理差异的来源。我们关注的是非临床因素,如患者年龄、性别、收入和种族以及医院位置数据作为自变量,以研究它们对医院收费和住院护理的影响。我们的研究样本是2019年NIS数据库中抽样的肝移植病例。我们的回归结果表明,患者年龄、性别以及付款人会影响诊断数量;而医院收费受年龄、付款人和医院位置的影响。除医院位置外,手术数量不受这些非临床因素中的任何一个影响。研究结果表明,美国各地区在诊断和手术数量的标准化方面还有更大空间。结果还显示,种族和收入对医院收费和住院护理没有任何影响。我们的研究有助于从实证角度理解非临床因素在解释医院收费和住院护理差异方面的作用。