在医疗保健机构中采用大数据的挑战及其对患者满意度的影响:印度德里的一项实证研究

IF 0.6 Q4 Health Professions
A. Sao, Neetu Sharma, Sakshee Singh, Bharati Vishwas Yelikar, Anoop Bhardwaj
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引用次数: 0

摘要

本研究旨在探讨影响医疗机构采用大数据的障碍和因素,以及其对患者满意度的后续影响。医疗领域的大数据是指对患者临床数据的收集、分析和使用,这些数据过于庞大或复杂,无法用标准的数据处理方法掌握。在医疗保健中采用大数据将使管理人员能够为患者和客户提供满意的服务。然而,在卫生保健部门,企业必须通过采用新技术来克服若干障碍和问题。我们进行了详细的文献综述,以检查与使用大数据相关的许多障碍。以李克特量表编制了一份结构良好的问卷,以找出影响大数据采用的因素及其对患者满意度的影响。为了评估因素,使用SPSS 21进行探索性因素分析,并使用结构方程模型(SEM)评估影响患者满意度的关键显著因素。这些数据是从与医院有关的员工那里收集的。该调查收到了212名参与者的回复。通过对数据的分析,我们发现了影响大数据采用的五大挑战因素。这些是数据集成、数据理解、技术和基础设施、缺乏专家和监管障碍。这些因素解释了70.36%的方差。然而,SEM分析表明,数据整合、数据理解和缺乏专业知识都会显著影响大数据的采用。此外,医院采用大数据将有助于提高患者满意度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining Challenges In The Adoption of Big Data In Health Care Institutions And Its Impact On Patients Satisfaction: An empirical study in Delhi, India
The study aims to investigate the obstacles and factors influencing the adoption of big data in healthcare organizations, and its subsequent impact on patient satisfaction. Big data in healthcare refers to the collecting, analysis, and use of clinical data from patients that is too massive or complex to be grasped by standard data processing methods. Adopting big data in health care will enable manages to render services to patient and customer satisfaction. However, in the health care sector, firms must overcome several hurdles and problems by adopting new technology. A detailed literature review was undertaken to examine many obstacles associated with the use of Big Data. A well-structured questionnaire was prepared in Likert scale to find the elements that influence big data adoption and its impact on patient satisfaction. To evaluate factors, exploratory factor analysis using SPSS 21 was performed, and Structural Equation Modelling (SEM) was performed to assess key significant factors that impact patient satisfaction. The data was gathered from employees associated with the hospitals. The survey received responses from 212 participants. Following the analysis of the data, it was found that five challenging factors influences big data adoption. These are data integration, data understanding, technology and infrastructure, lack of expert and regulation barrier. These factors explained 70.36% of variance. Whereas, SEM analysis indicated that both data integration, data understanding and lack of expertise significantly affect big data adoption Furthermore, big data adoption in hospitals will help in improving patient satisfaction.
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来源期刊
Asia Pacific Journal of Health Management
Asia Pacific Journal of Health Management HEALTH POLICY & SERVICES-
CiteScore
1.10
自引率
16.70%
发文量
51
审稿时长
9 weeks
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