Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China.
Department of Information Systems and Business Analytics, College of Business Administration, Loyola Marymount University, Los Angeles, CA, United States.
J Med Internet Res. 2022 May 26;24(5):e33742. doi: 10.2196/33742.
Despite the increasing adoption rate of tracking technologies in hospitals in the United States, few empirical studies have examined the factors involved in such adoption within different use contexts (eg, clinical and supply chain use contexts). To date, no study has systematically examined how governance structures impact technology adoption in different use contexts in hospitals. Given that the hospital governance structure fundamentally governs health care workflows and operations, understanding its critical role provides a solid foundation from which to explore factors involved in the adoption of tracking technologies in hospitals.
This study aims to compare critical factors associated with the adoption of tracking technologies for clinical and supply chain uses and examine how governance structure types affect the adoption of tracking technologies in hospitals.
This study was conducted based on a comprehensive and longitudinal national census data set comprising 3623 unique hospitals across 50 states in the United States from 2012 to 2015. Using mixed effects population logistic regression models to account for the effects within and between hospitals, we captured and examined the effects of hospital characteristics, locations, and governance structure on adjustments to the innate development of tracking technology over time.
From 2012 to 2015, we discovered that the proportion of hospitals in which tracking technologies were fully implemented for clinical use increased from 36.34% (782/2152) to 54.63% (1316/2409), and that for supply chain use increased from 28.58% (615/2152) to 41.3% (995/2409). We also discovered that adoption factors impact the clinical and supply chain use contexts differently. In the clinical use context, compared with hospitals located in urban areas, hospitals in rural areas (odds ratio [OR] 0.68, 95% CI 0.56-0.80) are less likely to fully adopt tracking technologies. In the context of supply chain use, the type of governance structure influences tracking technology adoption. Compared with hospitals not affiliated with a health system, implementation rates increased as hospitals affiliated with a more centralized health system-1.9-fold increase (OR 1.87, 95% CI 1.60-2.13) for decentralized or independent hospitals, 2.4-fold increase (OR 2.40, 95% CI 2.07-2.80) for moderately centralized health systems, and 3.1-fold increase for centralized health systems (OR 3.07, 95% CI 2.67-3.53).
As the first of such type of studies, we provided a longitudinal overview of how hospital characteristics and governance structure jointly affect adoption rates of tracking technology in both clinical and supply chain use contexts, which is essential for developing intelligent infrastructure for smart hospital systems. This study informs researchers, health care providers, and policy makers that hospital characteristics, locations, and governance structures have different impacts on the adoption of tracking technologies for clinical and supply chain use and on health resource disparities among hospitals of different sizes, locations, and governance structures.
尽管美国医院采用跟踪技术的比率不断提高，但很少有实证研究在不同的使用环境（如临床和供应链使用环境）中考察这种采用所涉及的因素。迄今为止，尚无研究系统地研究治理结构如何影响医院不同使用环境中的技术采用。鉴于医院治理结构从根本上管理着医疗保健工作流程和运营，了解其关键作用为探索医院跟踪技术采用所涉及的因素提供了坚实的基础。
本研究旨在比较与临床和供应链使用相关的跟踪技术采用的关键因素，并探讨治理结构类型如何影响医院跟踪技术的采用。
本研究基于 2012 年至 2015 年期间涵盖美国 50 个州的 3623 家独特医院的全面和纵向国家普查数据集进行。使用混合效应人口逻辑回归模型来解释医院内和医院间的影响，我们捕获并检查了医院特征、位置和治理结构对跟踪技术固有发展的调整随时间的影响。
2012 年至 2015 年间，我们发现，在临床使用中完全采用跟踪技术的医院比例从 36.34%（782/2152）增加到 54.63%（1316/2409），而在供应链使用中增加了 28.58%（615/2152）至 41.3%（995/2409）。我们还发现，采用因素对临床和供应链使用环境的影响不同。在临床使用环境中，与位于城市地区的医院相比，位于农村地区的医院（优势比[OR]0.68，95%置信区间[CI]0.56-0.80）不太可能完全采用跟踪技术。在供应链使用方面，治理结构类型会影响跟踪技术的采用。与不隶属于医疗系统的医院相比，随着隶属于更加集中的医疗系统的医院-去中心化或独立医院的实施率增加 1.9 倍（OR1.87，95%CI1.60-2.13），中度集中的医疗系统增加 2.4 倍（OR2.40，95%CI2.07-2.80），集中式医疗系统增加 3.1 倍（OR3.07，95%CI2.67-3.53）。
作为此类研究中的第一项，我们提供了一个关于医院特征和治理结构如何共同影响临床和供应链使用环境中跟踪技术采用率的纵向概述，这对于开发智能医院系统的智能基础设施至关重要。本研究为研究人员、医疗保健提供者和政策制定者提供了信息，即医院特征、位置和治理结构对临床和供应链使用的跟踪技术采用以及不同规模、位置和治理结构的医院之间的卫生资源差距有不同的影响。
