Department of Information Systems and Business Analytics, College of Business Administration, Loyola Marymount University, Los Angeles, CA, United States.
Department of Management Science, Lancaster University, Lancaster, United Kingdom.
JMIR Form Res. 2024 Oct 1;8:e51198. doi: 10.2196/51198.
Smart tracking technology (STT) that was applied for clinical use has the potential to reduce 30-day all-cause readmission risk through streamlining clinical workflows with improved accuracy, mobility, and efficiency. However, previously published literature has inadequately addressed the joint effects of STT for clinical use and its complementary health ITs (HITs) in this context. Furthermore, while previous studies have discussed the symbiotic and pooled complementarity effects among different HITs, there is a lack of evidence-based research specifically examining the complementarity effects between STT for clinical use and other relevant HITs.
Through a complementarity theory lens, this study aims to examine the joint effects of STT for clinical use and 3 relevant HITs on 30-day all-cause readmission risk. These HITs are STT for supply chain management, mobile IT, and health information exchange (HIE). Specifically, this study examines whether the pooled complementarity effect exists between STT for clinical use and STT for supply chain management, and whether symbiotic complementarity effects exist between STT for clinical use and mobile IT and between STT for clinical use and HIE.
This study uses a longitudinal in-patient dataset, including 879,122 in-patient hospital admissions for 347,949 patients in 61 hospitals located in Florida and New York in the United States, from 2014 to 2015. Logistic regression was applied to assess the effect of HITs on readmission risks. Time and hospital fixed effects were controlled in the regression model. Robust standard errors (SEs) were used to account for potential heteroskedasticity. These errors were further clustered at the patient level to consider possible correlations within the patient groups.
The interaction between STT for clinical use and STT for supply chain management, mobile IT, and HIE was negatively associated with 30-day readmission risk, with coefficients of -0.0352 (P=.003), -0.0520 (P<.001), and -0.0216 (P=.04), respectively. These results indicate that the pooled complementarity effect exists between STT for clinical use and STT for supply chain management, and symbiotic complementarity effects exist between STT for clinical use and mobile IT and between STT for clinical use and HIE. Furthermore, the joint effects of these HITs varied depending on the hospital affiliation and patients' disease types.
Our results reveal that while individual HIT implementations have varying impacts on 30-day readmission risk, their joint effects are often associated with a reduction in 30-day readmission risk. This study substantially contributes to HIT value literature by quantifying the complementarity effects among 4 different types of HITs: STT for clinical use, STT for supply chain management, mobile IT, and HIE. It further offers practical implications for hospitals to maximize the benefits of their complementary HITs in reducing the 30-day readmission risk in their respective care scenarios.
智能跟踪技术（STT）已应用于临床，通过提高准确性、移动性和效率来简化临床工作流程，从而有可能降低 30 天全因再入院风险。然而，先前发表的文献未能充分探讨 STT 在临床应用及其互补性健康信息技术（HIT）在此背景下的联合效应。此外，虽然先前的研究讨论了不同 HIT 之间的共生和综合互补效应，但缺乏专门研究 STT 在临床应用与其他相关 HIT 之间互补效应的循证研究。
本研究旨在通过互补性理论视角，考察 STT 在临床应用与 3 种相关 HIT（STT 用于供应链管理、移动 IT 和健康信息交换（HIE））联合使用对 30 天全因再入院风险的影响。具体而言，本研究检验了 STT 在临床应用与 STT 用于供应链管理之间是否存在综合互补效应，以及 STT 在临床应用与移动 IT 之间以及 STT 在临床应用与 HIE 之间是否存在共生互补效应。
本研究使用了一项纵向住院患者数据集，其中包括来自美国佛罗里达州和纽约州 61 家医院的 347949 名患者的 879122 例住院患者数据，数据采集时间为 2014 年至 2015 年。本研究采用逻辑回归评估 HIT 对再入院风险的影响。回归模型中控制了时间和医院固定效应。采用稳健标准误差（SE）来考虑潜在的异方差性。这些误差进一步在患者层面进行聚类，以考虑患者群体内部的可能相关性。
STT 在临床应用与 STT 用于供应链管理、移动 IT 和 HIE 之间的相互作用与 30 天再入院风险呈负相关，其系数分别为-0.0352（P=.003）、-0.0520（P<.001）和-0.0216（P=.04）。这些结果表明，STT 在临床应用与 STT 用于供应链管理之间存在综合互补效应，而 STT 在临床应用与移动 IT 之间以及 STT 在临床应用与 HIE 之间存在共生互补效应。此外，这些 HIT 的联合效应因医院隶属关系和患者疾病类型而异。
本研究结果表明，虽然个别 HIT 的实施对 30 天再入院风险有不同的影响，但它们的联合效应往往与降低 30 天再入院风险相关。本研究通过量化 4 种不同类型的 HIT（STT 在临床应用、STT 用于供应链管理、移动 IT 和 HIE）之间的互补效应，为 HIT 价值文献做出了重要贡献。它还为医院提供了实际意义，帮助他们在各自的护理场景中最大限度地发挥互补性 HIT 的效益，降低 30 天再入院风险。
