Liew Ewilly Jie Ying, Kwok Andrei O J, Koh Sharon G M, Ruslan Shairil R, Hasan M Shahnaz, Poh Yeh Han
Department of Econometrics & Business Statistics, School of Business, Monash University Malaysia, Subang Jaya, Malaysia.
Department of Management, School of Business, Monash University Malaysia, Subang Jaya, Malaysia.
PLoS One. 2025 Jul 1;20(7):e0317954. doi: 10.1371/journal.pone.0317954. eCollection 2025.
Advancements in electronic medical record (EMR) systems raise the demand for doctors' digital and analytical skills to process large-scale healthcare data for evidence-based decisions. The present challenge arises with the need to understand how doctors can develop business analytics capabilities using the EMR system for decision-making from an end user's perspective.
Integrating the technology acceptance model and the business analytics model for healthcare, this study examines how individual doctors' technology perceptions of using an EMR system influence their ability to develop business analytics capabilities for making effective healthcare decisions in intensive care units (ICUs). The research questions are: How do doctors' perceptions of using an EMR system influence their ability to develop business analytics capabilities? and How do doctors' business analytics capabilities affect the effectiveness of their healthcare decisions? This study focuses on the context of using the EMR system as a business analytics-enabled architecture rather than a general information system.
We surveyed a final sample of 130 ICU doctors from public tertiary hospitals in Malaysia, a developing country. This study uses PLS-SEM to analyze two phases, comparing doctors' technology perception and business analytics capabilities before and during the pandemic.
We found significant shifts in ICU doctors' perceptions of using the EMR system (i.e., perceived ease of use and usefulness) influencing the development of their business analytics capabilities (i.e., data aggregation, data analysis, and data interpretation) for decision-making effectiveness. Data analysis was the only capability contributing to decision-making effectiveness during the pandemic. Significant differences in the relationships were observed before and during the COVID-19 pandemic.
We demonstrate that COVID-19 has accelerated favorable technology perceptions and the increasing dependency on developing business analytics capabilities to inform healthcare decisions. Our findings contribute to the critical importance, challenges, and opportunities of using the EMR system for more data-driven decision-making, especially in the post-COVID era.
电子病历(EMR)系统的进步提高了对医生数字和分析技能的需求,以便处理大规模医疗数据以做出基于证据的决策。当前的挑战在于需要从终端用户的角度理解医生如何利用EMR系统发展商业分析能力以进行决策。
本研究将技术接受模型和医疗保健商业分析模型相结合,考察个体医生对使用EMR系统的技术认知如何影响他们在重症监护病房(ICU)发展商业分析能力以做出有效医疗决策的能力。研究问题为:医生对使用EMR系统的认知如何影响他们发展商业分析能力的能力?以及医生的商业分析能力如何影响其医疗决策的有效性?本研究聚焦于将EMR系统用作支持商业分析的架构而非一般信息系统的背景。
我们对来自马来西亚(一个发展中国家)公立三级医院的130名ICU医生进行了最终抽样调查。本研究使用偏最小二乘结构方程模型(PLS-SEM)分析两个阶段,比较疫情前和疫情期间医生的技术认知和商业分析能力。
我们发现ICU医生对使用EMR系统的认知(即感知易用性和有用性)发生了显著变化,这影响了他们为提高决策有效性而发展商业分析能力(即数据聚合、数据分析和数据解释)。在疫情期间,数据分析是唯一对决策有效性有贡献的能力。在新冠疫情之前和期间,这些关系存在显著差异。
我们证明,新冠疫情加速了积极的技术认知以及对发展商业分析能力以指导医疗决策的日益依赖。我们的研究结果有助于凸显使用EMR系统进行更多数据驱动决策的至关重要性、挑战和机遇,尤其是在新冠后时代。